--- license: cc-by-4.0 pretty_name: Paper2Profile — Papers + Extraction Results tags: [time-series, foundation-models, paper-parsing, information-extraction] --- # Paper2Profile One bucket, two parts: - **`papers/`** — source PDFs (100) + MinerU-2.5 **VLM** parses (markdown with HTML table grids, `content_list.json` with bbox/page_idx, pre-cropped block images) + `manifest.jsonl`. - **`result/`** — structured, paper-only, **verifiable-by-construction** extractions (66 papers): per-paper 3-topic CSVs (`components_architecture`, `accuracy_efficiency[_traced]`, `computational`), `combined/*_ALL.csv`, and `case_studies/` (reliability evidence pack). Pipeline: `PDF → MinerU 2.5 VLM → clean table grids → hybrid LLM structure-ID + deterministic grid-read → CSVs`. The LLM only identifies table structure; deterministic code reads `grid[row][col]`, so every value traces to an exact cell (with `table,row,col` coords). Unstated computational fields are `not_reported` (never fabricated). Reliability (grid-oracle over accuracy cells): **100% dataset-correct, 0 miss, ~82% full (dataset+model)**; schema-valid 100%; 0 fabricated numbers. See `result/case_studies/README.md`. ## Reproduce The pipeline lives in the `parse_extract/` package of the code repo. Install + run: ```bash # EXTRACT-only (no GPU) — re-run extraction on already-parsed papers: pip install openai==2.44.0 pyyaml==6.0.3 # FULL parse+extract (CUDA-13 GPU): conda env create -f parse_extract/environment.yml conda activate paper2profile uv pip install -r parse_extract/requirements.txt --index-strategy unsafe-best-match --torch-backend=cu130 # start the extract LLM server, then run the stage: GPU=0 bash rightsizing/engine/serve_qwen.sh & # Qwen3-14B on :8001 GPU=1 bash parse_extract/run.sh --config parse_extract/configs/full.yaml \ --steps parse,extract,verify,assemble # -> data/extracted//*.csv ``` Models: `opendatalab/MinerU2.5-Pro-2605-1.2B` (parse VLM) · `Qwen/Qwen3-14B` (extract structure-ID). Verified installable + runnable from a clean environment.