ChronoMedKG builds a temporal biomedical KG with 460k evidence-linked triples across 13k diseases using LLM consensus and introduces the ChronoTQA benchmark showing RAG gains on time-sensitive questions.
An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition.BMC Bioinformatics, 16:138
6 Pith papers cite this work, alongside 578 external citations. Polarity classification is still indexing.
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CHI-Bench shows current AI agents achieve at most 28% success on long-horizon healthcare workflows that require dense policy adherence, multi-role handoffs, and multi-turn interactions.
CHR improves medical QA retrieval by generating a target hypothesis H+ and a mimic hypothesis H-, then scoring documents by cosine similarity to H+ minus cosine similarity to H-, beating five RAG baselines on three benchmarks.
Introduces a reproducible benchmark and hybrid sparse-dense retrieval framework for evidence-grounded access to silicon detector literature, reporting Hit@5 of 0.917 on core queries.
A question-type-specific LLM ensemble and multi-agent pipeline achieved competitive results on BioASQ 14b Task B, including first place in the factoid subtask of Batch 4.
A hybrid RAG system with retrieval, Cohere reranking, and claim-level LLM judgment achieves 100% grounding accuracy on 200 claims from 25 biomedical queries in a pilot study.
citing papers explorer
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ChronoMedKG: A Temporally-Grounded Biomedical Knowledge Graph and Benchmark for Clinical Reasoning
ChronoMedKG builds a temporal biomedical KG with 460k evidence-linked triples across 13k diseases using LLM consensus and introduces the ChronoTQA benchmark showing RAG gains on time-sensitive questions.
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CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?
CHI-Bench shows current AI agents achieve at most 28% success on long-horizon healthcare workflows that require dense policy adherence, multi-role handoffs, and multi-turn interactions.
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Ruling Out to Rule In: Contrastive Hypothesis Retrieval for Medical Question Answering
CHR improves medical QA retrieval by generating a target hypothesis H+ and a mimic hypothesis H-, then scoring documents by cosine similarity to H+ minus cosine similarity to H-, beating five RAG baselines on three benchmarks.
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A Reproducible Benchmark and Evidence-Retrieval Software Framework for Silicon Detector R&D Literature
Introduces a reproducible benchmark and hybrid sparse-dense retrieval framework for evidence-grounded access to silicon detector literature, reporting Hit@5 of 0.917 on core queries.
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From Voting to Agent Collaboration: Answer-Type-Aware LLM Pipelines for BioASQ 14b
A question-type-specific LLM ensemble and multi-agent pipeline achieved competitive results on BioASQ 14b Task B, including first place in the factoid subtask of Batch 4.
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A Hybrid Retrieval and Reranking Framework for Evidence-Grounded Retrieval-Augmented Generation
A hybrid RAG system with retrieval, Cohere reranking, and claim-level LLM judgment achieves 100% grounding accuracy on 200 claims from 25 biomedical queries in a pilot study.