How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
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…
Aligning Text and Embodied Environments for Interactive Learning Mohit Shridhar, Xingdi (Eric) Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew Hausknecht ICLR 2021
This repository contains the official implementation for the paper "AutoLogi: Automated Generation of Logic Puzzles for Evaluating Reasoning Abilities of Large Language Models".
G1: Bootstrapping Perception and Reasoning Abilities of Vision-Language Model via Reinforcement Learning
The main features of chenllliang/g1 are: Reasoning Environments.
Projects with overlapping indexed features include: agent-rl/recall — We introduce ReCall, a novel framework that trains LLMs to Reason with Tool Call via reinforcement learning—without… alfworld/alfworld — Aligning Text and Embodied Environments for Interactive Learning Mohit Shridhar, Xingdi (Eric) Yuan, Marc-Alexandre… allenai/scienceworld — ScienceWorld. bytedtsinghua-sia/enigmata — We introduce Enigmata, the first comprehensive suite tailored for improving LLMs with puzzle reasoning skills, which… facebookresearch/mlgym — MLGym A New Framework and Benchmark for Advancing AI Research Agents. 8188zq/autologi — This repository contains the official implementation for the paper "AutoLogi: Automated Generation of Logic Puzzles…
