4 papers · 1 filter
Macro: Enhancing Multilingual Counterfactual Explanations through Alignment-as-Preference Optimization
Yilong Wang, Qianli Wang, Bohao Chu +3
Self-generated counterfactual explanations (SCEs) are minimally modified inputs (minimality) generated by large language models (LLMs) that flip their own predictions (validity), o…
eTracer: Towards Traceable Text Generation via Claim-Level Grounding
Bohao Chu, Qianli Wang, Hendrik Damm +5
How can system-generated responses be efficiently verified, especially in the high-stakes biomedical domain? To address this challenge, we introduce eTracer, a plug-and-play framew…
PCoA: A New Benchmark for Medical Aspect-Based Summarization With Phrase-Level Context Attribution
Bohao Chu, Sameh Frihat, Tabea M. G. Pakull +5
Verifying system-generated summaries remains challenging, as effective verification requires precise attribution to the source context, which is especially crucial in high-stakes m…
TracSum: A New Benchmark for Aspect-Based Summarization with Sentence-Level Traceability in Medical Domain
Bohao Chu, Meijie Li, Sameh Frihat +4
While document summarization with LLMs has enhanced access to textual information, concerns about the factual accuracy of these summaries persist, especially in the medical domain.…