57 citations · 180 across the 49 of their papers we have counts for
50 papers
SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoning
Zhaohan Meng, Zaiqiao Meng, Siwei Liu +3
Biomedical multi-hop question answering (QA) requires models to connect evidence across intermediate entities such as diseases, drugs, proteins, and phenotypes. Existing agents typ…
Explaining When PRF Fails: Participatory Auditing for Selective Query Expansion
Zeyan Liang, Graham McDonald, Iadh Ounis
Pseudo-Relevance Feedback (PRF) improves retrieval effectiveness on average, but harms a substantial fraction of queries through query drift, an asymmetry hidden by aggregate offli…
Interpretable Uncertainty for Adaptive Retrieval and Reasoning in Question Answering
Ritajit Dey, Iadh Ounis, Graham McDonald
Large language models (LLMs) achieve a strong performance in question answering (QA), but remain prone to hallucinations and suffer from limited transparency. Retrieval-augmented g…
URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios
Giuseppe Spillo, Zixuan Yi, Aleksandr Petrov +3
Training state-of-the-art recommendation models on large-scale industrial datasets can be a challenging task due to the high number of users and items which are typically represent…
Certifiable Semantic Agreement Among LLM Agents: What the Admissibility Instrument Decides
Haoran Xu, Lei Zhang, Iadh Ounis +1
Can a committee of LLM agents reach agreement that is certifiable at the level of meaning, not only at the level of a label? We build a protocol to find out. H-CSC emits one of thr…
A Large-Scale Dataset and Benchmark: Do Protein-Ligand Models Learn Binding Sites or Just Binding Likelihood?
Zhaohan Meng, Zhen Bai, Ke Yuan +4
Protein-ligand modeling underpins computational drug discovery and molecular design. Existing protein-ligand benchmarks typically evaluate whether a protein and ligand interact and…