Iadh Ounis

Triplet-Structured Knowledge Integration for Interactive Medical Question Answering

SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoning

Biomedical multi-hop question answering (QA) requires models to connect evidence across intermediate entities such as diseases, drugs, proteins, and phenotypes. Existing agents typically rely on static retrieval workflows or coarse-grained prompt rewriting, which can lead to instruction drift when reasoning procedures need to be updated. We propose SSE-Bio, a structured self-evolving agent with an agentic retrieval policy for multi-hop biomedical reasoning. Instead of globally rewriting agent instructions, SSE-Bio maintains a structured state, selectively retrieves knowledge triplets and prior templates through a trainable proxy policy, and improves its reasoning memory through fine-grained template editing. To optimise retrieval decisions, we introduce a proxy-training strategy based on group relative policy optimization, where the proxy is improved through decision-contrastive groups over alternative retrieval choices. Experiments on three biomedical multi-hop QA benchmarks show that SSE-Bio consistently outperforms existing baselines, achieving an improvement of 6.56 absolute points over the strongest self-evolving baseline on BioHopR.

APR: Adaptive Personalised Reranking For Conversational Search

Adaptive Personalised Reranking (APR) is proposed, a framework that routes queries based on intent that uses efficient similarity-based reranking for simple queries and dynamically generates tailored instructions to guide an instruction-following reranker for constraint-heavy contexts.

Interpretable Uncertainty for Adaptive Retrieval and Reasoning in Question Answering

This work proposes an uncertainty-aware framework for adaptive QA based on explicit signals derived from LLM internal representations that distinguish between knowledge insufficiency and knowledge ambiguity or conflict, and efficiently estimate these from hidden states in a single forward pass.