most citedTracSum: A New Benchmark for Aspect-Based Summarization with Sentence-Level Traceability in Medical Domain

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cs.CL2026

Locally Sound, Globally Insufficient: The Local-Global Gap in Multi-Hop Reasoning

Bohao Chu, Hendrik Damm, Qianli Wang +4

Reliable multi-hop reasoning requires more than locally supported steps: a trace can be sound at every reasoning step yet still fail to answer the question as a whole. We call this…

cs.CL2026

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…

cs.CL2026

eTracer: Polarity-Aware Evidence Grounding

Bohao Chu, Qianli Wang, Hendrik Damm +8

Evidence grounding makes generated content verifiable by linking statements to their sources. However, effective verifiability requires two properties that existing methods fail to…

cs.CL2026

MAPLE: Medical Aspect-Based Summarization with Phrase-Level Evidence

Bohao Chu, Sameh Frihat, Tabea M. G. Pakull +7

Trustworthy clinical summarization requires every claim to be traceable to its evidence, yet existing attribution often resolves only to the sentence or document, leaving clinician…

cs.CL2025★ 1 cited

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.…