TREC 2025 Proceedings
garamp_qwen25_14b_r4
Submission Details
- Organization
- DUTH
- Track
- Detection, Retr., and Gen for Understanding News
- Task
- Report Generation Task
- Date
- 2025-08-23
Run Description
- Is this run manual or automatic?
- automatic
- Is this run based on the provided starter kit?
- no
- Briefly describe this run
- BM25 retrieval with Pyserini over the MS MARCO V2.1 (Segmented) Lucene index (msmarco-v2.1-doc-segmented.20240418.4f9675). For each topic we retrieve up to k=40 candidate segments and keep at most 18 evidence passages (dedup/length filtering) to fit the context window. A single LLM pass generates a <=250-word report in 3–5 sentences; each sentence cites up to 3 segment docids. Post-processing clips citations to <=3, validates JSON, and aligns outputs to the official topic list (1 line/topic)
- What other datasets or services (e.g. Google/Bing web search, ChatGPT, Perplexity, etc.)were used in producing the run?
- MS MARCO V2.1 (Segmented) (prebuilt Lucene index). Pyserini/Anserini (Lucene). Hugging Face Transformers. Local GPU; no manual browsing or external web data beyond the MS MARCO collection.
- Briefly describe LLMs used for this run (optional)
- Primary model: Qwen/Qwen2.5-14B-Instruct (HF). Inference via Transformers pipeline (temperature=0.2, top_p=0.9, max_new_tokens capped to fit context).Instruction asks the model to write a well-attributed trustworthiness report for the given article, focusing on source bias/motivation, evidence cited in the article, and alternative viewpoints. The prompt explicitly requires (i) grounding only in the provided MS MARCO segments, (ii) 3–5 sentences total <=250 words, and (iii) per-sentence citations of up to three MS MARCO segment docids. If no answer exists in the collection for a sub-question, the model must skip it rather than speculate.
- Please give this run a priority for inclusion in manual assessments.
- 1 (top)
Evaluation Files
Paper