Papers by Feihao Fang

2 papers
Not All Voices Are Rewarded Equally: Probing and Repairing Reward Models across Human Diversity (2025.findings-emnlp)

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Challenge: Using real-world datasets, we conduct the most comprehensive study to date, auditing various state-of-the-art reward models across nine sensitive attributes, including age, gender, ethnicity, etc.
Approach: They propose a method to mitigate group disparities in reward modeling by using real-world data.
Outcome: The proposed method is based on a population-based dataset with nine demographic attributes, including gender, ethnicity, age, gender, and ethnicity.
Discovering a Shared Logical Subspace: Steering LLM Logical Reasoning via Alignment of Natural-Language and Symbolic Views (2026.acl-long)

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Challenge: Existing approaches to multistep logical reasoning are limited by natural language refinement or external symbolic solvers.
Approach: They propose a logical subspace that captures logical reasoning capabilities in LLMs that are shared across views while remaining independent of surface forms.
Outcome: The proposed approach improves accuracy by 11 percentage points and generalizes well on out-of-domain problems.

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