papers.json

{"source-free": {"What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context": "|**2024-12-18**|**What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context**|Jing Wang et.al|[paper](https://arxiv.org/abs/2412.14301)|-|<details><summary>detail</summary>ICLR 2025</details>|\n", "Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data": "|**2024-12-18**|**Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data**|Junki Mori et.al|[paper](https://arxiv.org/abs/2412.13757)|-|<details><summary>detail</summary>Accepted by WACV 2025</details>|\n", "Bridge then Begin Anew: Generating Target-relevant Intermediate Model for Source-free Visual Emotion Adaptation": "|**2024-12-18**|**Bridge then Begin Anew: Generating Target-relevant Intermediate Model for Source-free Visual Emotion Adaptation**|Jiankun Zhu et.al|[paper](https://arxiv.org/abs/2412.13577)|-|<details><summary>detail</summary>Accepted by AAAI2025</details>|\n", "Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation": "|**2024-12-15**|**Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation**|Ziyang Chen et.al|[paper](https://arxiv.org/abs/2410.13472)|-|-|\n", "Personalized Sleep Staging Leveraging Source-free Unsupervised Domain Adaptation": "|**2024-12-11**|**Personalized Sleep Staging Leveraging Source-free Unsupervised Domain Adaptation**|Yangxuan Zhou et.al|[paper](https://arxiv.org/abs/2412.12159)|-|-|\n", "Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting": "|**2024-12-1**|**Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting**|Linhai Zhuo et.al|[paper](https://arxiv.org/abs/2412.00767)|-|-|\n", "Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification": "|**2024-11-29**|**Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification**|Ruimin Peng et.al|[paper](https://arxiv.org/abs/2411.19502)|-|<details><summary>detail</summary>Journal ref:IEEE Int'l Conf</details>|\n", "SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG": "|**2024-11-28**|**SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG**|Shanglin Li et.al|[paper](https://arxiv.org/abs/2411.07249)|-|<details><summary>detail</summary>ACM Class:I</details>|\n", "Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation": "|**2024-11-24**|**Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation**|Peihua Deng et.al|[paper](https://arxiv.org/abs/2411.16064)|-|-|\n", "DRIVE: Dual-Robustness via Information Variability and Entropic Consistency in Source-Free Unsupervised Domain Adaptation": "|**2024-11-24**|**DRIVE: Dual-Robustness via Information Variability and Entropic Consistency in Source-Free Unsupervised Domain Adaptation**|Ruiqiang Xiao et.al|[paper](https://arxiv.org/abs/2411.15976)|-|-|\n", "Unveiling the Superior Paradigm: A Comparative Study of Source-Free Domain Adaptation and Unsupervised Domain Adaptation": "|**2024-11-24**|**Unveiling the Superior Paradigm: A Comparative Study of Source-Free Domain Adaptation and Unsupervised Domain Adaptation**|Fan Wang et.al|[paper](https://arxiv.org/abs/2411.15844)|-|<details><summary>detail</summary>Under review</details>|\n", "Collision-free Source Seeking Control Methods for Unicycle Robots": "|**2024-11-20**|**Collision-free Source Seeking Control Methods for Unicycle Robots**|Tinghua Li et.al|[paper](https://arxiv.org/abs/2212.07203)|-|<details><summary>detail</summary>Published in IEEE Transactions on Automatic Control</details>|\n", "Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework": "|**2024-11-19**|**Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework**|Ismail Nejjar et.al|[paper](https://arxiv.org/abs/2411.12558)|-|-|\n", "Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning": "|**2024-11-15**|**Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning**|Huali Xu et.al|[paper](https://arxiv.org/abs/2411.10070)|[code](https://github.com/xuhuali-mxj/StepSPT)|-|\n", "Memory-Efficient Pseudo-Labeling for Online Source-Free Universal Domain Adaptation using a Gaussian Mixture Model": "|**2024-11-12**|**Memory-Efficient Pseudo-Labeling for Online Source-Free Universal Domain Adaptation using a Gaussian Mixture Model**|Pascal Schlachter et.al|[paper](https://arxiv.org/abs/2407.14208)|[code](https://github.com/pascalschlachter/GMM.)|<details><summary>detail</summary>IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2025</details>|\n", "Source-Free Domain Adaptation for Speaker Verification in Data-Scarce Languages and Noisy Channels": "|**2024-12-17**|**Source-Free Domain Adaptation for Speaker Verification in Data-Scarce Languages and Noisy Channels**|S Salo Elia et.al|[paper](https://ui.adsabs.harvard.edu/abs/2024arXiv240605863S/abstract)|[code](https://paperswithcode.com/paper/source-free-domain-adaptation-for-speaker)|-|\n", "Global self-sustaining and local inheritance for source-free unsupervised domain adaptation": "|**2024-12-16**|**Global self-sustaining and local inheritance for source-free unsupervised domain adaptation**|L Peng et.al|[paper](https://www.sciencedirect.com/science/article/pii/S0031320324004308)|-|<details><summary>detail</summary>Pattern Recognition, 2024 Elsevier</details>|\n", "Unveiling the Unknown: Unleashing the Power of Unknown to Known in Open-Set Source-Free Domain Adaptation": "|**2024-12-15**|**Unveiling the Unknown: Unleashing the Power of Unknown to Known in Open-Set Source-Free Domain Adaptation**|F Wan et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/html/Wan_Unveiling_the_Unknown_Unleashing_the_Power_of_Unknown_to_Known_CVPR_2024_paper.html)|[code](https://paperswithcode.com/paper/unveiling-the-unknown-unleashing-the-power-of)|<details><summary>detail</summary>Proceedings of the IEEE\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "Discriminative Pattern Calibration Mechanism for Source-Free Domain Adaptation": "|**2024-12-15**|**Discriminative Pattern Calibration Mechanism for Source-Free Domain Adaptation**|H Xia et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/html/Xia_Discriminative_Pattern_Calibration_Mechanism_for_Source-Free_Domain_Adaptation_CVPR_2024_paper.html)|[code](https://paperswithcode.com/paper/discriminative-pattern-calibration-mechanism)|<details><summary>detail</summary>\u2026\u00a0of the IEEE/CVF Conference on\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective": "|**2024-12-15**|**Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective**|Y Mitsuzumi et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/html/Mitsuzumi_Understanding_and_Improving_Source-free_Domain_Adaptation_from_a_Theoretical_Perspective_CVPR_2024_paper.html)|[code](https://paperswithcode.com/paper/understanding-and-improving-source-free)|<details><summary>detail</summary>Proceedings of the IEEE\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "Semantics, Distortion, and Style Matter: Towards Source-free UDA for Panoramic Segmentation\u2013Supplementary Material\u2013": "|**2024-12-15**|**Semantics, Distortion, and Style Matter: Towards Source-free UDA for Panoramic Segmentation\u2013Supplementary Material\u2013**|X Zheng et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Zheng_Semantics_Distortion_and_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>openaccess.thecvf.com</details>|\n", "LEAD: Learning Decomposition for Source-free Universal Domain Adaptation\u2014Supplementary Material": "|**2024-12-15**|**LEAD: Learning Decomposition for Source-free Universal Domain Adaptation\u2014Supplementary Material**|S Qu et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Qu_LEAD_Learning_Decomposition_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>Integration openaccess.thecvf.com</details>|\n", "Stable Neighbor Denoising for Source-free Domain Adaptive Segmentation (Supplementary Material)": "|**2024-12-15**|**Stable Neighbor Denoising for Source-free Domain Adaptive Segmentation (Supplementary Material)**|D Zhao et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Zhao_Stable_Neighbor_Denoising_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>openaccess.thecvf.com</details>|\n", "EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition\u2013Supplementray Material\u2013": "|**2024-12-15**|**EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition\u2013Supplementray Material\u2013**|X Zheng et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Zheng_EventDance_Unsupervised_Source-free_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>openaccess.thecvf.com</details>|\n", "MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection\u2014Supplementary Material": "|**2024-12-15**|**MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection\u2014Supplementary Material**|B Peng et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Peng_MAP_MAsk-Pruning_for_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>openaccess.thecvf.com</details>|\n"}, "object detection": {"Union-over-Intersections: Object Detection beyond Winner-Takes-All": "|**2024-12-19**|**Union-over-Intersections: Object Detection beyond Winner-Takes-All**|Aritra Bhowmik et.al|[paper](https://arxiv.org/abs/2311.18512)|-|-|\n", "A Light-Weight Framework for Open-Set Object Detection with Decoupled Feature Alignment in Joint Space": "|**2024-12-19**|**A Light-Weight Framework for Open-Set Object Detection with Decoupled Feature Alignment in Joint Space**|Yonghao He et.al|[paper](https://arxiv.org/abs/2412.14680)|[code](https://github.com/D-Robotics-AI-Lab/DOSOD.)|-|\n", "PoLaRIS Dataset: A Maritime Object Detection and Tracking Dataset in Pohang Canal": "|**2024-12-19**|**PoLaRIS Dataset: A Maritime Object Detection and Tracking Dataset in Pohang Canal**|Jiwon Choi et.al|[paper](https://arxiv.org/abs/2412.06192)|[code](https://sites.google.com/view/polaris-dataset.)|-|\n", "Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties": "|**2024-12-19**|**Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties**|Wenqiao Li et.al|[paper](https://arxiv.org/abs/2412.14592)|-|-|\n", "Alignment-Free RGB-T Salient Object Detection: A Large-scale Dataset and Progressive Correlation Network": "|**2024-12-19**|**Alignment-Free RGB-T Salient Object Detection: A Large-scale Dataset and Progressive Correlation Network**|Kunpeng Wang et.al|[paper](https://arxiv.org/abs/2412.14576)|[code](https://github.com/Angknpng/PCNet.)|<details><summary>detail</summary>Accepted by AAAI 2025</details>|\n", "SCKD: Semi-Supervised Cross-Modality Knowledge Distillation for 4D Radar Object Detection": "|**2024-12-19**|**SCKD: Semi-Supervised Cross-Modality Knowledge Distillation for 4D Radar Object Detection**|Ruoyu Xu et.al|[paper](https://arxiv.org/abs/2412.14571)|[code](https://github.com/Ruoyu-Xu/SCKD.)|<details><summary>detail</summary>Accepted by AAAI 2025</details>|\n", "RT-DETRv3: Real-time End-to-End Object Detection with Hierarchical Dense Positive Supervision": "|**2024-12-18**|**RT-DETRv3: Real-time End-to-End Object Detection with Hierarchical Dense Positive Supervision**|Shuo Wang et.al|[paper](https://arxiv.org/abs/2409.08475)|[code](https://github.com/clxia12/RT-DETRv3.)|-|\n", "HA-RDet: Hybrid Anchor Rotation Detector for Oriented Object Detection": "|**2024-12-18**|**HA-RDet: Hybrid Anchor Rotation Detector for Oriented Object Detection**|Phuc D. A. Nguyen et.al|[paper](https://arxiv.org/abs/2412.14379)|-|<details><summary>detail</summary>Bachelor thesis</details>|\n", "CREST: An Efficient Conjointly-trained Spike-driven Framework for Event-based Object Detection Exploiting Spatiotemporal Dynamics": "|**2024-12-18**|**CREST: An Efficient Conjointly-trained Spike-driven Framework for Event-based Object Detection Exploiting Spatiotemporal Dynamics**|Ruixin Mao et.al|[paper](https://arxiv.org/abs/2412.12525)|-|<details><summary>detail</summary>Accepted by AAAI 2025</details>|\n", "Object Style Diffusion for Generalized Object Detection in Urban Scene": "|**2024-12-18**|**Object Style Diffusion for Generalized Object Detection in Urban Scene**|Hao Li et.al|[paper](https://arxiv.org/abs/2412.13815)|-|-|\n", "Deep Learning and Machine Learning -- Object Detection and Semantic Segmentation: From Theory to Applications": "|**2024-12-18**|**Deep Learning and Machine Learning -- Object Detection and Semantic Segmentation: From Theory to Applications**|Jintao Ren et.al|[paper](https://arxiv.org/abs/2410.15584)|-|-|\n", "No Annotations for Object Detection in Art through Stable Diffusion": "|**2024-12-17**|**No Annotations for Object Detection in Art through Stable Diffusion**|Patrick Ramos et.al|[paper](https://arxiv.org/abs/2412.06286)|[code](https://github.com/patrick-john-ramos/nada)|-|\n", "Improving Generalization Performance of YOLOv8 for Camera Trap Object Detection": "|**2024-12-17**|**Improving Generalization Performance of YOLOv8 for Camera Trap Object Detection**|Aroj Subedi et.al|[paper](https://arxiv.org/abs/2412.14211)|-|<details><summary>detail</summary>Master's thesis</details>|\n", "A New Adversarial Perspective for LiDAR-based 3D Object Detection": "|**2024-12-17**|**A New Adversarial Perspective for LiDAR-based 3D Object Detection**|Shijun Zheng et.al|[paper](https://arxiv.org/abs/2412.13017)|-|-|\n", "What is YOLOv6? A Deep Insight into the Object Detection Model": "|**2024-12-17**|**What is YOLOv6? A Deep Insight into the Object Detection Model**|Athulya Sundaresan Geetha et.al|[paper](https://arxiv.org/abs/2412.13006)|-|-|\n", "Masked Feature Compression for Object Detection": "|**2024-12-18**|**Masked Feature Compression for Object Detection**|C Dai et.al|[paper](https://www.mdpi.com/2227-7390/12/12/1848)|[code](https://github.com/bosszhe/emiff)|<details><summary>detail</summary>Mathematics, 2024 mdpi.com</details>|\n", "Enhanced Object Detection: A Study on Vast Vocabulary Object Detection Track for V3Det Challenge 2024": "|**2024-12-17**|**Enhanced Object Detection: A Study on Vast Vocabulary Object Detection Track for V3Det Challenge 2024**|P Wu et.al|[paper](https://arxiv.org/abs/2406.09201)|[code](https://paperswithcode.com/paper/enhanced-object-detection-a-study-on-vast)|-|\n", "\u041f\u0420\u0418\u041c\u0415\u041d\u0415\u041d\u0418\u0415 MULTI-LABEL \u041a\u041b\u0410\u0421\u0421\u0418\u0424\u0418\u041a\u0410\u0426\u0418\u0418 \u0418 OBJECT DETECTION \u0414\u041b\u042f \u041a\u0422-\u0421\u041d\u0418\u041c\u041a\u041e\u0412": "|**2024-12-17**|**\u041f\u0420\u0418\u041c\u0415\u041d\u0415\u041d\u0418\u0415 MULTI-LABEL \u041a\u041b\u0410\u0421\u0421\u0418\u0424\u0418\u041a\u0410\u0426\u0418\u0418 \u0418 OBJECT DETECTION \u0414\u041b\u042f \u041a\u0422-\u0421\u041d\u0418\u041c\u041a\u041e\u0412**|\u041f\u0410 \u0421\u0443\u0445\u043e\u0432 et.al|[paper](https://cyberleninka.ru/article/n/primenenie-multi-label-klassifikatsii-i-object-detection-dlya-kt-snimkov)|-|<details><summary>detail</summary>\u0412\u0435\u0441\u0442\u043d\u0438\u043a \u043d\u0430\u0443\u043a\u0438, 2024 cyberleninka.ru</details>|\n", "Environmentally adaptive fast object detection in UAV images": "|**2024-12-17**|**Environmentally adaptive fast object detection in UAV images**|M Sang et.al|[paper](https://www.sciencedirect.com/science/article/pii/S0262885624002075)|-|<details><summary>detail</summary>Image and Vision Computing, 2024 Elsevier</details>|\n", "Highway Abandoned Objects Recognition Based on Open Vocabulary Object Detection Approach": "|**2024-12-17**|**Highway Abandoned Objects Recognition Based on Open Vocabulary Object Detection Approach**|S Liu et.al|[paper](https://ascelibrary.org/doi/abs/10.1061/9780784485514.045)|-|<details><summary>detail</summary>\u2026\u00a0on Transportation and\u00a0\u2026, 2024 ascelibrary.org</details>|\n", "SAM-PM: Enhancing Video Camouflaged Object Detection using Spatio-Temporal Attention": "|**2024-12-17**|**SAM-PM: Enhancing Video Camouflaged Object Detection using Spatio-Temporal Attention**|M Nawfal Meeran et.al|[paper](https://ui.adsabs.harvard.edu/abs/2024arXiv240605802N/abstract)|[code](https://github.com/spidernitt/sam-pm)|-|\n", "OV-DAR: Open-Vocabulary Object Detection and Attributes Recognition": "|**2024-12-17**|**OV-DAR: Open-Vocabulary Object Detection and Attributes Recognition**|K Chen et.al|[paper](https://link.springer.com/article/10.1007/s11263-024-02144-1)|-|<details><summary>detail</summary>International Journal of\u00a0\u2026, 2024 Springer</details>|\n", "Advanced Object Detection and Decision Making in Autonomous Medical Response Systems": "|**2024-12-17**|**Advanced Object Detection and Decision Making in Autonomous Medical Response Systems**|J Needhi - 2024 - preprints.org et.al|[paper](https://www.preprints.org/manuscript/202406.0811)|-|<details><summary>detail</summary>2024 preprints.org</details>|\n", "A Three-Stage Model for Camouflaged Object Detection": "|**2024-12-16**|**A Three-Stage Model for Camouflaged Object Detection**|T Chen et.al|[paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4862341)|[code](https://github.com/rmcong/fpnet_acmmm23)|<details><summary>detail</summary>Available at SSRN 4862341 papers.ssrn.com</details>|\n", "Multi-Scale Features Extraction and Cross-Stage Features Fusion Network for Small Object Detection (Mcfn)": "|**2024-12-16**|**Multi-Scale Features Extraction and Cross-Stage Features Fusion Network for Small Object Detection (Mcfn)**|D Bian et.al|[paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4862981)|-|<details><summary>detail</summary>Available at SSRN\u00a0\u2026 papers.ssrn.com</details>|\n"}, "domain adaptation": {"Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation": "|**2024-12-19**|**Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation**|Wei Chen et.al|[paper](https://arxiv.org/abs/2412.11654)|[code](https://github.com/cwei01/TDSS.)|-|\n", "Robust and Communication-Efficient Federated Domain Adaptation via Random Features": "|**2024-12-18**|**Robust and Communication-Efficient Federated Domain Adaptation via Random Features**|Zhanbo Feng et.al|[paper](https://arxiv.org/abs/2311.04686)|-|-|\n", "ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study": "|**2024-12-18**|**ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study**|Eric Modesitt et.al|[paper](https://arxiv.org/abs/2412.14436)|[code](https://github.com/ModeEric/ORBIT-Llama)|-|\n", "What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context": "|**2024-12-18**|**What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context**|Jing Wang et.al|[paper](https://arxiv.org/abs/2412.14301)|-|<details><summary>detail</summary>ICLR 2025</details>|\n", "Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali": "|**2024-12-18**|**Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali**|Sharad Duwal et.al|[paper](https://arxiv.org/abs/2412.13860)|-|-|\n", "Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data": "|**2024-12-18**|**Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data**|Junki Mori et.al|[paper](https://arxiv.org/abs/2412.13757)|-|<details><summary>detail</summary>Accepted by WACV 2025</details>|\n", "One for Dozens: Adaptive REcommendation for All Domains with Counterfactual Augmentation": "|**2024-12-17**|**One for Dozens: Adaptive REcommendation for All Domains with Counterfactual Augmentation**|Huishi Luo et.al|[paper](https://arxiv.org/abs/2412.11905)|[code](https://github.com/Chrissie-Law/AREAD-Multi-Domain-Recommendation.)|<details><summary>detail</summary>Extended version accepted by AAAI 2025</details>|\n", "Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm": "|**2024-12-17**|**Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm**|Thai-Hoang Pham et.al|[paper](https://arxiv.org/abs/2412.13036)|[code](https://github.com/pth1993/OSHeDA)|<details><summary>detail</summary>Accepted by AAAI 2025</details>|\n", "Differential Alignment for Domain Adaptive Object Detection": "|**2024-12-17**|**Differential Alignment for Domain Adaptive Object Detection**|Xinyu He et.al|[paper](https://arxiv.org/abs/2412.12830)|[code](https://github.com/EstrellaXyu/Differential-Alignment-for-DAOD.)|-|\n", "COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation": "|**2024-12-16**|**COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation**|Munish Monga et.al|[paper](https://arxiv.org/abs/2409.00397)|[code](https://github.com/munish30monga/COSMo)|<details><summary>detail</summary>Accepted in BMVC 2024</details>|\n", "HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation": "|**2024-12-16**|**HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation**|Ba Hung Ngo et.al|[paper](https://arxiv.org/abs/2412.11819)|-|<details><summary>detail</summary>Accepted for presentation at AAAI2025</details>|\n", "CLDA-YOLO: Visual Contrastive Learning Based Domain Adaptive YOLO Detector": "|**2024-12-16**|**CLDA-YOLO: Visual Contrastive Learning Based Domain Adaptive YOLO Detector**|Tianheng Qiu et.al|[paper](https://arxiv.org/abs/2412.11812)|-|-|\n", "Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition": "|**2024-12-16**|**Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition**|Thejan Rajapakshe et.al|[paper](https://arxiv.org/abs/2207.12248)|-|-|\n", "Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment": "|**2024-12-15**|**Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment**|Yuanfan Zheng et.al|[paper](https://arxiv.org/abs/2412.11443)|[code](https://github.com/zyfone/DPA)|<details><summary>detail</summary>This work is accepted by AAAI 2025</details>|\n", "Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment": "|**2024-12-15**|**Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment**|Jiayi Guo et.al|[paper](https://arxiv.org/abs/2406.04295)|[code](https://github.com/SHI-Labs/Diffusion-Driven-Test-Time-Adaptation-via-Synthetic-Domain-Alignment.)|<details><summary>detail</summary>GitHub: https://github</details>|\n", "Confidence sharing adaptation for out-of-domain human pose and shape estimation": "|**2024-12-18**|**Confidence sharing adaptation for out-of-domain human pose and shape estimation**|T Yue et.al|[paper](https://www.sciencedirect.com/science/article/pii/S1077314224001322)|-|<details><summary>detail</summary>Computer Vision and Image\u00a0\u2026, 2024 Elsevier</details>|\n", "\u2026\u00a0Carbon Content and Temperature in Bof Steelmaking Based on Adaptive Balanced Joint Distribution Alignment Domain Adaptation with Variational Autoencoder": "|**2024-12-17**|**\u2026\u00a0Carbon Content and Temperature in Bof Steelmaking Based on Adaptive Balanced Joint Distribution Alignment Domain Adaptation with Variational Autoencoder**|Z Liu et.al|[paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4863841)|-|<details><summary>detail</summary>Available at SSRN 4863841 papers.ssrn.com</details>|\n", "POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning": "|**2024-12-17**|**POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning**|J Wang et.al|[paper](https://www.researchgate.net/profile/Junxiang-Wang-3/publication/381225385_POND_Multi-Source_Time_Series_Domain_Adaptation_with_Information-Aware_Prompt_Tuning/links/6663974e85a4ee7261ae011e/POND-Multi-Source-Time-Series-Domain-Adaptation-with-Information-Aware-Prompt-Tuning.pdf)|[code](https://paperswithcode.com/paper/prompt-based-domain-discrimination-for-multi)|<details><summary>detail</summary>2024 researchgate.net</details>|\n", "Continuous Test-time Domain Adaptation for Efficient Fault Detection under Evolving Operating Conditions": "|**2024-12-17**|**Continuous Test-time Domain Adaptation for Efficient Fault Detection under Evolving Operating Conditions**|H Sun et.al|[paper](https://ui.adsabs.harvard.edu/abs/2024arXiv240606607S/abstract)|[code](https://paperswithcode.com/paper/continuous-test-time-domain-adaptation-for)|-|\n", "Source-Free Domain Adaptation for Speaker Verification in Data-Scarce Languages and Noisy Channels": "|**2024-12-17**|**Source-Free Domain Adaptation for Speaker Verification in Data-Scarce Languages and Noisy Channels**|S Salo Elia et.al|[paper](https://ui.adsabs.harvard.edu/abs/2024arXiv240605863S/abstract)|[code](https://paperswithcode.com/paper/source-free-domain-adaptation-for-speaker)|-|\n", "Cross-Domain Classification Based on Frequency Component Adaptation for Remote Sensing Images": "|**2024-12-17**|**Cross-Domain Classification Based on Frequency Component Adaptation for Remote Sensing Images**|P Zhu et.al|[paper](https://www.mdpi.com/2072-4292/16/12/2134)|-|<details><summary>detail</summary>Remote Sensing, 2024 mdpi.com</details>|\n", "TSFAN: Tensorized spatial-frequency attention network with domain adaptation for cross-session EEG-based biometric recognition": "|**2024-12-17**|**TSFAN: Tensorized spatial-frequency attention network with domain adaptation for cross-session EEG-based biometric recognition**|X Jin et.al|[paper](https://automatedtest.iopscience.iop.org/article/10.1088/1741-2552/ad5761)|-|<details><summary>detail</summary>Journal of\u00a0\u2026, 2024 automatedtest.iopscience.iop.org</details>|\n", "SE/BN Adapter: Parametric Efficient Domain Adaptation for Speaker Recognition": "|**2024-12-17**|**SE/BN Adapter: Parametric Efficient Domain Adaptation for Speaker Recognition**|T Wang et.al|[paper](https://arxiv.org/abs/2406.07832)|-|-|\n", "Novel Deep Learning Domain Adaptation Approach for Object Detection Using Semi-Self Building Dataset and Modified YOLOv4": "|**2024-12-16**|**Novel Deep Learning Domain Adaptation Approach for Object Detection Using Semi-Self Building Dataset and Modified YOLOv4**|A Gomaa et.al|[paper](https://www.mdpi.com/2032-6653/15/6/255)|-|<details><summary>detail</summary>World Electric Vehicle Journal, 2024 mdpi.com</details>|\n", "Global self-sustaining and local inheritance for source-free unsupervised domain adaptation": "|**2024-12-16**|**Global self-sustaining and local inheritance for source-free unsupervised domain adaptation**|L Peng et.al|[paper](https://www.sciencedirect.com/science/article/pii/S0031320324004308)|-|<details><summary>detail</summary>Pattern Recognition, 2024 Elsevier</details>|\n"}, "domain generalization": {"FDS: Feedback-guided Domain Synthesis with Multi-Source Conditional Diffusion Models for Domain Generalization": "|**2024-12-18**|**FDS: Feedback-guided Domain Synthesis with Multi-Source Conditional Diffusion Models for Domain Generalization**|Mehrdad Noori et.al|[paper](https://arxiv.org/abs/2407.03588)|[code](https://github.com/Mehrdad-Noori/FDS.git)|<details><summary>detail</summary>WACV 2025</details>|\n", "Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes": "|**2024-12-18**|**Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes**|Aodi Li et.al|[paper](https://arxiv.org/abs/2412.13573)|-|-|\n", "Rethinking Multi-domain Generalization with A General Learning Objective": "|**2024-12-18**|**Rethinking Multi-domain Generalization with A General Learning Objective**|Zhaorui Tan et.al|[paper](https://arxiv.org/abs/2402.18853)|-|<details><summary>detail</summary>Accepted by CVPR24</details>|\n", "Process-Supervised Reward Models for Clinical Note Generation: A Scalable Approach Guided by Domain Expertise": "|**2024-12-17**|**Process-Supervised Reward Models for Clinical Note Generation: A Scalable Approach Guided by Domain Expertise**|Hanyin Wang et.al|[paper](https://arxiv.org/abs/2412.12583)|-|-|\n", "BioRAGent: A Retrieval-Augmented Generation System for Showcasing Generative Query Expansion and Domain-Specific Search for Scientific Q&A": "|**2024-12-16**|**BioRAGent: A Retrieval-Augmented Generation System for Showcasing Generative Query Expansion and Domain-Specific Search for Scientific Q&A**|Samy Ateia et.al|[paper](https://arxiv.org/abs/2412.12358)|-|<details><summary>detail</summary>Version as accepted at the Demo Track at ECIR 2025</details>|\n", "Domain Generalization in Autonomous Driving: Evaluating YOLOv8s, RT-DETR, and YOLO-NAS with the ROAD-Almaty Dataset": "|**2024-12-16**|**Domain Generalization in Autonomous Driving: Evaluating YOLOv8s, RT-DETR, and YOLO-NAS with the ROAD-Almaty Dataset**|Madiyar Alimov et.al|[paper](https://arxiv.org/abs/2412.12349)|-|-|\n", "Exploring Semantic Consistency and Style Diversity for Domain Generalized Semantic Segmentation": "|**2024-12-16**|**Exploring Semantic Consistency and Style Diversity for Domain Generalized Semantic Segmentation**|Hongwei Niu et.al|[paper](https://arxiv.org/abs/2412.12050)|[code](https://github.com/nhw649/SCSD.)|<details><summary>detail</summary>Accepted by AAAI 2025</details>|\n", "PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection": "|**2024-12-16**|**PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection**|Xiaoran Xu et.al|[paper](https://arxiv.org/abs/2412.11807)|-|-|\n", "Meta Curvature-Aware Minimization for Domain Generalization": "|**2024-12-16**|**Meta Curvature-Aware Minimization for Domain Generalization**|Ziyang Chen et.al|[paper](https://arxiv.org/abs/2412.11542)|-|-|\n", "Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training": "|**2024-12-15**|**Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training**|Milad Soltany et.al|[paper](https://arxiv.org/abs/2412.11408)|-|-|\n", "Learning Latent Spaces for Domain Generalization in Time Series Forecasting": "|**2024-12-15**|**Learning Latent Spaces for Domain Generalization in Time Series Forecasting**|Songgaojun Deng et.al|[paper](https://arxiv.org/abs/2412.11171)|-|-|\n", "Guidance Not Obstruction: A Conjugate Consistent Enhanced Strategy for Domain Generalization": "|**2024-12-13**|**Guidance Not Obstruction: A Conjugate Consistent Enhanced Strategy for Domain Generalization**|Meng Cao et.al|[paper](https://arxiv.org/abs/2412.10089)|-|-|\n", "Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator": "|**2024-12-12**|**Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator**|Chengyuan Liu et.al|[paper](https://arxiv.org/abs/2412.09280)|-|<details><summary>detail</summary>Under review</details>|\n", "DomCLP: Domain-wise Contrastive Learning with Prototype Mixup for Unsupervised Domain Generalization": "|**2024-12-12**|**DomCLP: Domain-wise Contrastive Learning with Prototype Mixup for Unsupervised Domain Generalization**|Jin-Seop Lee et.al|[paper](https://arxiv.org/abs/2412.09074)|[code](https://github.com/jinsuby/DomCLP.)|<details><summary>detail</summary>Code page: https://github</details>|\n", "CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization": "|**2024-12-11**|**CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization**|Sumaiya Zoha et.al|[paper](https://arxiv.org/abs/2412.08479)|-|-|\n", "Entity-centric multi-domain transformer for improving generalization in fake news detection": "|**2024-12-18**|**Entity-centric multi-domain transformer for improving generalization in fake news detection**|P Bazmi et.al|[paper](https://www.sciencedirect.com/science/article/pii/S0306457324001663)|-|<details><summary>detail</summary>Information Processing &\u00a0\u2026, 2024 Elsevier</details>|\n", "Fine-Grained Domain Generalization with Feature Structuralization": "|**2024-12-17**|**Fine-Grained Domain Generalization with Feature Structuralization**|W Yu et.al|[paper](https://arxiv.org/abs/2406.09166)|[code](https://github.com/ValeevGroup/tiledarray)|-|\n", "Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification": "|**2024-12-15**|**Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification**|S Addepalli et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/html/Addepalli_Leveraging_Vision-Language_Models_for_Improving_Domain_Generalization_in_Image_Classification_CVPR_2024_paper.html)|[code](https://github.com/val-iisc/VL2V-ADiP)|<details><summary>detail</summary>Proceedings of the\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "Disentangled Prompt Representation for Domain Generalization": "|**2024-12-15**|**Disentangled Prompt Representation for Domain Generalization**|D Cheng et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/html/Cheng_Disentangled_Prompt_Representation_for_Domain_Generalization_CVPR_2024_paper.html)|[code](https://github.com/henry123-boy/SpaTracker)|<details><summary>detail</summary>Proceedings of the\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "Supplementary Materials: Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential in Open Domain Generalization": "|**2024-12-15**|**Supplementary Materials: Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential in Open Domain Generalization**|M Singha et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Singha_Unknown_Prompt_the_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>openaccess.thecvf.com</details>|\n", "Supplementary Material for DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning": "|**2024-12-15**|**Supplementary Material for DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning**|B Dataset - openaccess.thecvf.com et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Bai_DiPrompT_Disentangled_Prompt_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>openaccess.thecvf.com</details>|\n", "Supplementary Material for Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization": "|**2024-12-15**|**Supplementary Material for Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization**|K Le et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024/supplemental/Le_Efficiently_Assemble_Normalization_CVPR_2024_supplemental.pdf)|-|<details><summary>detail</summary>Phuoc, KS Wong openaccess.thecvf.com</details>|\n", "Domain Generalization for Crop Segmentation with Standardized Ensemble Knowledge Distillation": "|**2024-12-15**|**Domain Generalization for Crop Segmentation with Standardized Ensemble Knowledge Distillation**|S Angarano et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024W/Vision4Ag/html/Angarano_Domain_Generalization_for_Crop_Segmentation_with_Standardized_Ensemble_Knowledge_Distillation_CVPRW_2024_paper.html)|[code](https://paperswithcode.com/paper/domain-generalization-for-crop-segmentation)|<details><summary>detail</summary>Proceedings of the\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "MixStyle-Based Contrastive Test-Time Adaptation: Pathway to Domain Generalization": "|**2024-12-15**|**MixStyle-Based Contrastive Test-Time Adaptation: Pathway to Domain Generalization**|K Yamashita et.al|[paper](https://openaccess.thecvf.com/content/CVPR2024W/MAT/html/Yamashita_MixStyle-Based_Contrastive_Test-Time_Adaptation_Pathway_to_Domain_Generalization_CVPRW_2024_paper.html)|-|<details><summary>detail</summary>\u2026\u00a0of the IEEE/CVF Conference on\u00a0\u2026, 2024 openaccess.thecvf.com</details>|\n", "Fault vibration model driven fault-aware domain generalization framework for bearing fault diagnosis": "|**2024-12-15**|**Fault vibration model driven fault-aware domain generalization framework for bearing fault diagnosis**|B Pang et.al|[paper](https://www.sciencedirect.com/science/article/pii/S1474034624002684)|-|<details><summary>detail</summary>Advanced Engineering\u00a0\u2026, 2024 Elsevier</details>|\n"}, "vision language": {"VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis": "|**2024-12-19**|**VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis**|Chao Pang et.al|[paper](https://arxiv.org/abs/2403.20213)|[code](https://github.com/opendatalab/VHM)|<details><summary>detail</summary>Equal contribution: Chao Pang</details>|\n", "FiVL: A Framework for Improved Vision-Language Alignment": "|**2024-12-19**|**FiVL: A Framework for Improved Vision-Language Alignment**|Estelle Aflalo et.al|[paper](https://arxiv.org/abs/2412.14672)|[code](https://github.com/IntelLabs/fivl.)|-|\n", "HarmonicEval: Multi-modal, Multi-task, Multi-criteria Automatic Evaluation Using a Vision Language Model": "|**2024-12-19**|**HarmonicEval: Multi-modal, Multi-task, Multi-criteria Automatic Evaluation Using a Vision Language Model**|Masanari Ohi et.al|[paper](https://arxiv.org/abs/2412.14613)|-|-|\n", "Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models": "|**2024-12-19**|**Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models**|Quang-Hung Le et.al|[paper](https://arxiv.org/abs/2412.08125)|[code](https://github.com/lqh52/PromViL.)|-|\n", "Doubly-Universal Adversarial Perturbations: Deceiving Vision-Language Models Across Both Images and Text with a Single Perturbation": "|**2024-12-19**|**Doubly-Universal Adversarial Perturbations: Deceiving Vision-Language Models Across Both Images and Text with a Single Perturbation**|Hee-Seon Kim et.al|[paper](https://arxiv.org/abs/2412.08108)|-|-|\n", "VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision": "|**2024-12-18**|**VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision**|Yi Xu et.al|[paper](https://arxiv.org/abs/2412.14446)|-|-|\n", "Surrealistic-like Image Generation with Vision-Language Models": "|**2024-12-18**|**Surrealistic-like Image Generation with Vision-Language Models**|Elif Ayten et.al|[paper](https://arxiv.org/abs/2412.14366)|-|<details><summary>detail</summary>2023 Joint international Scientific conferences on AI and Machine Learning (BNAIC-BeNeLearn)</details>|\n", "A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation": "|**2024-12-18**|**A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation**|Zhihong Chen et.al|[paper](https://arxiv.org/abs/2401.12208)|-|-|\n", "Performance Gap in Entity Knowledge Extraction Across Modalities in Vision Language Models": "|**2024-12-18**|**Performance Gap in Entity Knowledge Extraction Across Modalities in Vision Language Models**|Ido Cohen et.al|[paper](https://arxiv.org/abs/2412.14133)|-|-|\n", "Towards Generalist Robot Policies: What Matters in Building Vision-Language-Action Models": "|**2024-12-18**|**Towards Generalist Robot Policies: What Matters in Building Vision-Language-Action Models**|Xinghang Li et.al|[paper](https://arxiv.org/abs/2412.14058)|-|<details><summary>detail</summary>Project page: robovlms</details>|\n", "HandsOnVLM: Vision-Language Models for Hand-Object Interaction Prediction": "|**2024-12-18**|**HandsOnVLM: Vision-Language Models for Hand-Object Interaction Prediction**|Chen Bao et.al|[paper](https://arxiv.org/abs/2412.13187)|[code](https://www.chenbao.tech/handsonvlm/)|<details><summary>detail</summary>Preprint</details>|\n", "Nullu: Mitigating Object Hallucinations in Large Vision-Language Models via HalluSpace Projection": "|**2024-12-18**|**Nullu: Mitigating Object Hallucinations in Large Vision-Language Models via HalluSpace Projection**|Le Yang et.al|[paper](https://arxiv.org/abs/2412.13817)|[code](https://github.com/Ziwei-Zheng/Nullu)|<details><summary>detail</summary>Under review</details>|\n", "ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification": "|**2024-12-18**|**ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification**|Yefei He et.al|[paper](https://arxiv.org/abs/2410.08584)|-|-|\n", "Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation": "|**2024-12-18**|**Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation**|Changsun Lee et.al|[paper](https://arxiv.org/abs/2412.13558)|-|-|\n", "Benchmarking and Improving Large Vision-Language Models for Fundamental Visual Graph Understanding and Reasoning": "|**2024-12-18**|**Benchmarking and Improving Large Vision-Language Models for Fundamental Visual Graph Understanding and Reasoning**|Yingjie Zhu et.al|[paper](https://arxiv.org/abs/2412.13540)|-|-|\n", "Towards Vision-Language Geo-Foundation Model: A Survey": "|**2024-12-18**|**Towards Vision-Language Geo-Foundation Model: A Survey**|Y Zhou et.al|[paper](https://www.researchgate.net/profile/Yue-Zhou-139/publication/381403816_Towards_Vision-Language_Geo-Foundation_Model_A_Survey/links/666ba71ea54c5f0b9464c544/Towards-Vision-Language-Geo-Foundation-Model-A-Survey.pdf)|[code](https://github.com/zytx121/awesome-vlgfm)|<details><summary>detail</summary>researchgate.net</details>|\n", "VLind-Bench: Measuring Language Priors in Large Vision-Language Models": "|**2024-12-17**|**VLind-Bench: Measuring Language Priors in Large Vision-Language Models**|K Lee et.al|[paper](https://arxiv.org/abs/2406.08702)|[code](https://github.com/klee972/vlind-bench)|-|\n", "How structured are the representations in transformer-based vision encoders? An analysis of multi-object representations in vision-language models": "|**2024-12-17**|**How structured are the representations in transformer-based vision encoders? An analysis of multi-object representations in vision-language models**|T Khajuria et.al|[paper](https://arxiv.org/abs/2406.09067)|[code](https://paperswithcode.com/paper/how-structured-are-the-representations-in)|-|\n", "AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models": "|**2024-12-17**|**AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models**|Y Wu et.al|[paper](https://arxiv.org/abs/2406.09295)|[code](https://paperswithcode.com/paper/alignmmbench-evaluating-chinese-multimodal)|-|\n", "MirrorCheck: Efficient Adversarial Defense for Vision-Language Models": "|**2024-12-17**|**MirrorCheck: Efficient Adversarial Defense for Vision-Language Models**|S Fares et.al|[paper](https://arxiv.org/abs/2406.09250)|[code](https://paperswithcode.com/paper/mirrorcheck-efficient-adversarial-defense-for)|-|\n", "LLAVIDAL: Benchmarking Large Language Vision Models for Daily Activities of Living": "|**2024-12-17**|**LLAVIDAL: Benchmarking Large Language Vision Models for Daily Activities of Living**|R Chakraborty et.al|[paper](https://arxiv.org/abs/2406.09390)|-|-|\n", "OpenVLA: An Open-Source Vision-Language-Action Model": "|**2024-12-17**|**OpenVLA: An Open-Source Vision-Language-Action Model**|MJ Kim et.al|[paper](https://arxiv.org/abs/2406.09246)|[code](https://github.com/openvla/openvla)|-|\n", "Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model": "|**2024-12-17**|**Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model**|M Wong et.al|[paper](https://arxiv.org/abs/2406.09143)|[code](https://paperswithcode.com/paper/generative-ai-based-prompt-evolution)|-|\n", "VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks": "|**2024-12-16**|**VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks**|J Wu et.al|[paper](https://arxiv.org/abs/2406.08394)|[code](https://github.com/opengvlab/visionllm)|-|\n", "RWKV-CLIP: A Robust Vision-Language Representation Learner": "|**2024-12-16**|**RWKV-CLIP: A Robust Vision-Language Representation Learner**|T Gu et.al|[paper](https://arxiv.org/abs/2406.06973)|[code](https://github.com/deepglint/rwkv-clip)|-|\n"}}