★ A UC Berkeley research project · by Nico Bauer

Stop drowning in papers.
Read the ones that matter.

Literature Assistant fetches the newest research for your topic, has an LLM summarise and score every paper for relevance, and learns from your feedback to surface what you should read next.

Invite-only · Accounts are gated by a registration key.

Daily Brief — today
Ranked for your topic12 new
Deep RL for safe motion planning5/5
Graph neural networks: a survey3/5
Off-topic preprint1/5
Millions
Papers across journals, IEEE, ACM & arXiv
Latest
Powered by OpenAI's newest models
Instant
Ranking on demand — whenever you want, no batch wait
1–5
LLM relevance score per paper

Two ways to work through the literature

One tool, two modes — whether you want a daily pulse on a field or to systematically mine it.

Daily Brief

Pulls the most relevant new papers, has an LLM summarise and rate each 1–5, and shows a ranked list so you only read the top ones.

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Research Assistant

Takes the papers you've liked and suggests the closest new matches across the whole literature, ranked by your own learned taste.

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Built-in evaluation

Is the LLM actually worth it? It benchmarks LLM scores against TF-IDF and embeddings on the papers you label — with precision & ranking metrics.

How it works

From a research question to a ranked reading list in minutes.

Describe your topic. Write a precise research question — the LLM turns it into an academic search query.
Fetch & rate. The tool pulls a broad pool of candidate papers and scores each for relevance, with reasoning.
Label what's relevant. Mark papers relevant / not relevant — your labels become the answer key.
It learns & improves. The Research Assistant refines its search from your taste; the evaluation shows whether it's working.

Built to answer a real question

Is an LLM genuinely better at triaging research than simple keyword or embedding methods? This tool measures it — and helps you keep up with your field along the way.

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