Papers by Yuhan Pu

2 papers
SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness (2026.acl-long)

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Challenge: SDiaReward is an end-to-end spoken dialogue system that integrates paralinguistic nuances and spontaneous nature of human conversation.
Approach: They propose an end-to-end multi-turn reward model trained on SDiaReward-Dataset . it is a collection of episode-level preference pairs targeting modality and colloquiality gaps .
Outcome: The proposed model outperforms general-purpose audio LLMs in episode-level evaluation.
OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models (2026.findings-acl)

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Challenge: Existing benchmarks for MU are limited by a lack of image diversity and coarse-grained unlearning targets.
Approach: They propose a benchmark to evaluate misinformation unlearning in MLLMs . OFFSIDE supports advanced unlearning targets such as fine-grained unlearning and visual rumor removal.
Outcome: OFFSIDE supports advanced unlearning targets, such as fine-grained unlearning and visual rumor removal.

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