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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".
⚙️ Algorithm Flow • 📊 Results ✨ Getting Started • 🏋️ Training • 🔧 Usage • 📃 Evaluation 🎈 Citation • 🌻 Acknowledgement • 📧 Contact • 📈 Star History
The main features of leaplabthu/absolute-zero-reasoner are: Reasoning Environments, Unsupervised Reward Methods.
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… chengsong-huang/r-zero — Check out our paper or webpage for the details. 8188zq/autologi — This repository contains the official implementation for the paper "AutoLogi: Automated Generation of Logic Puzzles…
