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This repository contains the official implementation for the paper "AutoLogi: Automated Generation of Logic Puzzles for Evaluating Reasoning Abilities of Large Language Models".
We introduce ReCall, a novel framework that trains LLMs to Reason with Tool Call via reinforcement learning—without requiring any supervised data on tool use trajectories or reasoning steps. ReCall empowers LLMs to agentically use and combine arbitrary tools like OpenAI o3, offering an…
OpenAGI: When LLM Meets Domain Experts
MLGym A New Framework and Benchmark for Advancing AI Research Agents
The main features of facebookresearch/mlgym are: General Agent Benchmarks, Reasoning Environments, Reinforcement Learning.
Open-source alternatives to facebookresearch/mlgym include: 8188zq/autologi — This repository contains the official implementation for the paper "AutoLogi: Automated Generation of Logic Puzzles… agent-rl/recall — We introduce ReCall, a novel framework that trains LLMs to Reason with Tool Call via reinforcement learning—without… agiresearch/openagi — OpenAGI: When LLM Meets Domain Experts. ai4co/rl4co. ai4finance-foundation/finrl — FinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated… 2toinf/uniact — [Project Page] [Paper].
