Papers by Ziyao Tang

2 papers
Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis (P19-1)

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Challenge: Experimental results show that our proposed approach yields better attention mechanisms . dominant ASC models are mostly discriminative classifiers based on manual feature engineering .
Approach: They propose a self-supervised approach to aspect-level sentiment classification that mines useful attention supervision information from a training corpus to refine attention mechanisms.
Outcome: The proposed approach yields better attention mechanisms on multiple datasets.
Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models (2026.findings-acl)

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Challenge: Existing Vid-LLMs lack robust mechanisms for maintaining grounded spatiotemporal beliefs under conversational feedback.
Approach: They propose a negation-based gaslighting evaluation framework and introduce a benchmark to investigate spatiotemporal sycophancy.
Outcome: The proposed framework evaluates state-of-the-art Vid-LLMs across video understanding tasks.

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