An in-the-wild benchmark for AI agents in the OpenClaw Environment.

AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading

Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services

TradingAgents: Multi-Agents LLM Financial Trading Framework

The repo is finally unlocked. enjoy the party! The fastest repo in history to surpass 100K stars ⭐. Join Discord: https://discord.gg/5TUQKqFWd Built in Rust using oh-my-codex.

A tremendous feat of documentation, this guide covers Claude Code from beginner to power user, with production-ready templates for Claude Code features, guides on agentic workflows, and a lot of gr…

A series of work towards achieving ACV.

A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes…

🔥 A collection of the newest Claude Code open source

Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster through natural language commands. Rebuilt from leaked source.

[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.

《动手学大模型Dive into LLMs》系列编程实践教程

The official GitHub page for the survey paper "A Survey of Large Language Models".

Benchmarking Generalized Out-of-Distribution Detection

source code for NeurIPS'22 paper "SIREN: Shaping Representations for Detecting Out-of-Distribution Objects"

Code from PLDI '21 paper "Provable Repair of Deep Neural Networks."

Beyond Accuracy: Behavioral Testing of NLP models with CheckList

Microsoft Bonsai Simulink Toolbox and sample models

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

A paper list of lane detection.

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

This is the implement repository of our upcoming ESEC/FSE 2020 paper: Deep Learning Library Testing via Effective Model Generation.

An uncertainty-based random sampling algorithm for data augmentation

NLP-Conferences-Code (ACL、EMNL、NAACL、COLING、AAAI、IJCAI)