Librarian Agents paper: letting agents organize long contexts themselves to improve retrieval performance
Chelsea Finn retweeted a new paper, Librarian Agents, by Anikait Singh and others, which studies whether agents can adapt to large amounts of unstructured context in specialized domains by organizing their own long-context workspaces and anticipating queries. She notes that agentic search can scale to information of any size but tends to miss relevant content, while optimizing information organization for downstream use can also bring 30+% improvements in OOD domains. The tweet includes links to the paper and code.
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This tweet points to a paper about agents organizing their own long-context workspaces, and provides data showing 30+% improvement in cross-domain scenarios.
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View original postLLMs deployed in specialized domains, from enterprise codebases to law firms, dig through a mountain of unstructured context! Our new paper, Librarian Agents, asks: can an agent adapt by curating its own long-context workspace, anticipating queries before they arrive? 🧵⬇️
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LLMs deployed in specialized domains, from enterprise codebases to law firms, dig through a mountain of unstructured context! Our new paper, Librarian Agents, asks: can an agent adapt by curating its own long-context workspace, anticipating queries before they arrive? 🧵⬇️
Body
How do we scale up the context of LLMs?
Agentic search scales to arbitrarily large amounts of info, but can easily miss relevant info.
Idea💡: Optimize organization of info for downstream utility. Leads to 30+% gains even on OOD domains