DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments (2025 · 113 citations)
LLM agents that search the web are promising for deep research. Existing open methods either depend on fragile hand-written prompts or train with RL against fixed local corpora, which do not reflect the messy, changing open web. DeepResearcher is a framework for training such agents end-to-end with reinforcement…
ParaCook: On Time-Efficient Planning for Multi-Agent Systems (2026)
Most LLM agent benchmarks check whether a task gets done, not how quickly. They ignore idle time, blocking and contention for shared resources when work runs in parallel or asynchronously. ParaCook fills this gap with a benchmark for time-efficient planning in multi-agent systems. It is inspired by Overcooked and set…

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Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 92 times (of the 149,439 papers whose bibliographies we read); 33 citing papers with a page here →.

Updated 2 November 2026