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lit-builder

ICLR / NeurIPS literature builder with keyword + LLM relevance scoring.

Pulls ML conference paper lists, filters them through a research lens, and produces an annotated, browsable literature base. Built for the Sutro Group energy-efficient training agenda — generalizes to any lens via configs/keywords.yaml.

What's published

Venue Total papers Keyword-passed LLM-scored Score 3 Score 2 Score 1
ICLR 2026 19,813 4,842 4,842 40 25 134

Score 3 = directly advances Sutro Group priorities (energy-efficient training, sparsity, low-precision, data movement, communication efficiency, training alternatives).

→ Browse all 40 score-3 papers

How it works

fetch  →  ingest  →  filter  →  score  →  deepen  →  render
   │          │          │         │          │           │
papercopilot  SQLite     keyword   LLM       on-demand   markdown
paperlists                pre-filter (0–3 + reason)       + mkdocs

Each stage is a CLI subcommand. Output lives in data/db/lit.sqlite. The site is generated from the DB.

LLM providers

Two providers, swap with LIT_PROVIDER:

Anthropic

  • Default model: claude-haiku-4-5-20251001
  • Set ANTHROPIC_API_KEY
  • Override with LIT_MODEL

Ollama (cloud or local)

  • Cloud: set OLLAMA_API_KEY against https://ollama.com
  • Local: set OLLAMA_HOST=http://localhost:11434
  • Default model: deepseek-v4-pro:cloud

Solid Ollama Cloud models (any swap-in via LIT_MODEL):

Model Notes
deepseek-v4-pro:cloud Default. Reasoning model; ~5s per paper at 200-token limit.
deepseek-v4-flash:cloud Faster, lower latency, slightly less robust on edge cases.
gpt-oss:120b Strong general scorer. Slightly heavier than deepseek-v4-pro.
qwen3:235b-cloud Largest. Best for the deepen stage on borderline papers.
llama3.1:70b Solid baseline; available locally too.

Local examples:

LIT_PROVIDER=ollama OLLAMA_HOST=http://localhost:11434 LIT_MODEL=llama3.1:8b
LIT_PROVIDER=ollama OLLAMA_HOST=http://localhost:11434 LIT_MODEL=qwen3:14b

Quickstart

pip install -e .
# or with uv: uv sync && uv run lit ...

lit fetch  iclr2026
lit ingest iclr2026
lit filter iclr2026                    # keyword pre-filter
lit score  iclr2026 --limit 200        # LLM triage on survivors
lit list   iclr2026 --min-score 2      # browse high-relevance
lit deepen iclr2026 <paper_id>         # structured digest on demand
lit render iclr2026                    # write markdown + mkdocs nav
lit serve                              # local mkdocs preview

See the README on GitHub for full setup.

CLI as a tool

The CLI is designed to be called by other coding agents (Codex, Claude Code, Gemini CLI). Every command takes positional args, exits non-zero on error, and prints structured key=value output.

lit --help
lit score --help

Source

github.com/0bserver07/iclr-lit-builder