A language agent gym with challenging scientific tasks
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Updated
Oct 25, 2026 - Python
A language agent gym with challenging scientific tasks
[NeurIPS 2024] Official implementation for paper "Can Graph Learning Improve Planning in LLM-based Agents?"
Benchmark for LLM-based Agents in Computational Biology
Framework enabling modular interchange of language agents, environments, and optimizers
Using VLM-based visual question answering to perceive scenes and control robots in MuJoCo simulation.
Optimal stopping agents powered by generative large language models
Execution-time action control for ReAct language agents with stage-aware guards, wrong-object prevention, and action redirection in ALFWorld.
Bounded-staleness asynchronous evolution strategies for long-horizon language-agent training. An active research release.
Investigating whether a persistent caregiver–child relationship improves knowledge transfer in language agents.
OpenAgents: An Open Platform for Language Agents in the Wild
Experiments on generative and cognitive agents from my MSc thesis: purely generative (LLM-based), CoALA-inspired and symbolic (ASTRA) agents compared in a dynamic, partially observable, stochastic environment
Cognitive AutoGen (CoAG) extends Microsoft AutoGen with a CoALA-inspired cognitive layer — structured working memory, RAG long-term memory and a 6-phase deliberative cycle
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