Agent S: an open agentic framework that uses computers like a human
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Updated
Sep 5, 2026 - Python
Agent S: an open agentic framework that uses computers like a human
Keras based framework for neuro-symbolic LM systems
[EMNLP 2026] Official code for "SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization"
Awesome In-Context RL: A curated list of In-Context Reinforcement Learning - - —
Official Implementation for "In-Context Reinforcement Learning for Variable Action Spaces"
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning - - — ICLR 2025
Vintix: Action Model via In-Context Reinforcement Learning - - — ICML 2025
Official Implementation for "In-Context Reinforcement Learning from Noise Distillation"
Next-gen Foundation Model for Embodied AI
[NeurIPS 2025] Official codebase for T2MIR: Mixture-of-Experts Meets In-Context Reinforcement Learning.
Benchmarking general decision-making with open & random worlds
A repo for enhancing spatial reasoning in VLMs using CoT and VoT prompting for 3D visual environments
Toy meta-RL environments for testing algorithms implementations
Explore the "frp_rl" repository to discover the Free Random Projection technique for in-context reinforcement learning. This project offers a JAX-based implementation that helps agents adapt and learn in diverse environments. 🐙🌟
Code for our paper HeXA: Hierarchical Experimentalist Agents
Grouped-Tied Attention by Zadouri, Strauss, Dao (2025).
Source code for reproducing free random projection
ICLE is a multi-agent AI framework that dynamically trains and orchestrates specialized Expert Agents to solve complex, multi-step tasks.
Testing hypotheses of distillation of a learning algorithm on multiple environments
Repository Switched To Xenoverse (https://github.com/FutureAGI/Xenoverse)
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