Papers by Chengfu Huo

2 papers
How Do Answer Tokens Read Reasoning Traces? Self-Reading Patterns in Thinking LLMs for Quantitative Reasoning (2026.findings-acl)

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Challenge: Prior work on activation steering has focused on shaping reasoning traces, but it remains unclear how answer tokens actually read and integrate the reasoning to produce reliable outcomes.
Approach: They propose a training-free steering method that uses self-reading quality scores to guide inference toward benign self-readiness and away from uncertain and disorganized reading.
Outcome: The proposed method yields consistent accuracy gains in the reasoning traces generated by thinking LLMs.
Implicit Relation Linking for Question Answering over Knowledge Graph (2022.findings-acl)

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Challenge: Existing methods rely on textual similarities between NL and KG to build relation links.
Approach: They propose an implicit relation linking method called ImRL which links relation phrases in NL to relation paths in KG.
Outcome: The proposed method significantly outperforms state-of-the-art methods on two benchmarks and a newly-created datasets.

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