Cost-Pragmatic Quality Gating and Selection-Fusion Multi-Model Combiners for BioASQ Phases A+ and B
Not on the map. Why?
Abstract (arXiv)
We describe our BioASQ Task 14B 2026 system. The work centers on two design decisions: how aggressively to re-retrieve when first-stage retrieval is weak, and how to combine multiple language-model answers. Retrieval unions two parallel pipelines - a hybrid first stage (dense BGE + BM25 + RRF, reaching R@200 = 99.3% on the BioASQ-13b historical archive) and an agent-driven pipeline that decomposes the question over PubMed, Europe PMC, and iCite - with a BGE cross-encoder quality gate flagging weakly-supported questions for selective re-retrieval. On Task 12B 2024 validation, a cost-pragmatic re-retrieval policy beats a skill-strict baseline significantly on list F1 and list precision, at 12% lower re-retrieval cost. Holding prompt and model fixed across val and test 13B (different question sets), list F1 rises by +0.132 absolute on the BioASQ-released gold-input pool, consistent with substantial retrieval-side headroom. For Phase B answering we decompose multi-model ensemble lift into a selection component bounded by the per-question oracle and a fusion component that aggregators can exceed. The decomposition predicts before any experiment that LLM-as-judge wins on selection-dominated metrics (yes/no, multi-reference ROUGE) but is structurally insufficient on the recall component of fusion-friendly metrics (factoid rank-1, list recall). On Task 13B 2025 our synonym-union resolver wins list recall on every head, while GPT-5.5 solo retains the list-F1 lead because the resolver's wider item set costs precision. On the Task 14B 2026 preliminary leaderboard our team places first on the combined-exact aggregate on three of the eight (phase x batch) leaderboards, wins four individual question-type cells, and takes #1 on Phase B b3 ideal.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 34 of its 50 references that are in the map. First posted on arXiv 15 Jul 2026.
Builds on
34 of 50 references.
References · 34
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2022Training language models to follow instructions with human feedbackcited by 15,971
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
- 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
- 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
22 more
- 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
- 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
- 2022Large Language Models Encode Clinical Knowledgecited by 1,830
- 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
- 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
- 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
- 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,288
- 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,252
- 2021Unsupervised Dense Information Retrieval with Contrastive Learningcited by 1,216
- 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
- 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,178
- 2024M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillationcited by 1,073
- 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 1,009
- 2016Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphscited by 861
- 2023C-Pack: Packed Resources For General Chinese Embeddingscited by 578
- 2023LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusioncited by 564
- 2022BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Miningcited by 538
- 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 376
- 2023Chain-of-Verification Reduces Hallucination in Large Language Modelscited by 324
- 2023MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrievalcited by 185
- 2023LM vs LM: Detecting Factual Errors via Cross Examinationcited by 156
- 2025Overview of BioASQ 2024: The twelfth BioASQ challenge on Large-Scale Biomedical Semantic Indexing and Question Answeringcited by 4
Built on by
Citing papers per year: 2026: 1.
1 paper.