Highlights
- Pro
Stars
MAD: The first work to explore Multi-Agent Debate with Large Language Models :D
一款跳过B站视频中恰饭片段的浏览器插件,移植自 SponsorBlock。A browser extension to skip sponsored segments in videos on Bilibili.com, ported from the SponsorBlock
🐝 GPTSwarm: LLM agents as (Optimizable) Graphs
🤖 AgentVerse 🪐 is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation
Create Customized Software using Natural Language Idea (through LLM-powered Multi-Agent Collaboration)
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
[EMNLP 2024] CryptoTrade: A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading https://aclanthology.org/2024.emnlp-main.63.pdf
Mixing an audio file with a noise file at any Signal-to-Noise Ratio (SNR)
Start building LLM-empowered multi-agent applications in an easier way.
Large Language Model-based Stock Trading in Simulated Real-world Environments
Raw data and processing scripts of Weather Captioned Dataset in TGTSF
Official implementation of TGTSF in "Beyond Trend and Periodicity: Guiding Time Series Forecasting with Textual Cues"
The repository for ACL 2024 paper "TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models"
Official implementation for "AutoTimes: Autoregressive Time Series Forecasters via Large Language Models"
An example algorithm for a momentum-based day trading strategy.
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
AI chat and search for text, news, images and videos using the DuckDuckGo.com search engine.
FNSPID: A Comprehensive Financial News Dataset in Time Series
Download market data from Yahoo! Finance's API
Reading list for research topics in multimodal machine learning
A syntax-highlighting pager for git, diff, grep, and blame output
Code release for "Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models" https://arxiv.org/abs/2402.03659
The official implementation of the paper: "SST: Multi-Scale Hybrid Mamba-Transformer Experts for Long-Short Range Time Series Forecasting"
Mamba for Multivariate Time Series Forecasting
FITS: Frequency Interpolation Time Series Analysis Baseline