TREC 2025 Proceedings
lucerank
Submission Details
- Organization
- digsci
- Track
- Retrieval-Augmented Generation
- Task
- Retrieval Only Task
- Date
- 2025-08-18
Run Description
- Is this a manual (human intervention) or automatic run?
- automatic
- Does this run leverage neural networks?
- yes
- Does this run leverage proprietary models in any step of the retrieval pipeline?
- yes
- Does this run leverage open-weight LLMs (> 5B parameters) in any step of the retrieval pipeline?
- no
- Does this run leverage smaller open-weight language models in any step of the retrieval pipeline?
- no
- Was this run padded with results from a baseline run?
- no
- What would you categorize this run as?
- Generation-in-the-loop Pipeline
- Please provide a short description of this run
- Lucerank is a reranking strategy that leverages highly parallelized LLM calls (gpt‑4.1‑mini in this case) on small random subsets of candidates, and then aggregates them via Luce Spectral Ranking to produce calibrated relevance scores.
- Please give this run a priority for inclusion in manual assessments.
- 1 (top)
Evaluation Files