Papers by Jiaying Zhou
What’s Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews (2026.acl-long)
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| Challenge: | Existing efforts to detect factually incorrect content are omitted by creators who subtly reshape impressions by omitting crucial background context. |
| Approach: | They propose a multi-stage pipeline that simulates preview-based and context-based understanding and a OMGuard pipeline that combines interpretation-aware fine-tuning and rationale-guided misleading content correction. |
| Outcome: | The proposed framework lifts an 8B model’s detection accuracy to the level of a 235B LVLM while delivering stronger end-to-end correction. |
Stable Language Guidance for Vision–Language–Action Models (2026.acl-long)
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| Challenge: | Existing vision-Language-Action models are notoriously brittle to linguistic perturbations. |
| Approach: | They propose a probabilistic framework that disentangles physical affordance from semantic execution. |
| Outcome: | The proposed framework disentangles physical affordance from semantic execution. |
CMIE: Combining MLLM Insights with External Evidence for Explainable Out-of-Context Misinformation Detection (2025.findings-acl)
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| Challenge: | Multimodal large language models have demonstrated impressive capabilities in visual reasoning and text generation. |
| Approach: | They propose a multimodal large language model that captures deeper relationships between images and text . they propose CMIE, which uses a Coexistence Relationship Generation strategy and an AS mechanism to detect misinformation. |
| Outcome: | The proposed framework outperforms existing methods in detecting out-of-context misinformation. |
Clues Before Answers: Generation-Enhanced Multiple-Choice QA (2022.naacl-main)
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| Challenge: | Multiple-choice question answering (MCQA) uses text-to-text framework . but, there is an under-utilization of the decoder and knowledge that can be decoded . |
| Approach: | They propose a generative multiple-choice question answering model which generates a clue from the question and leverages it to enhance a reader for MCQA. |
| Outcome: | The proposed model outperforms text-to-text models on multiple MCQA datasets. |
SAS: Dialogue State Tracking via Slot Attention and Slot Information Sharing (2020.acl-main)
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| Challenge: | Existing models with excessive information are inefficient and costly . |
| Approach: | They propose to integrate a Dialogue State Tracker with Slot Attention and Slot Information Sharing to reduce redundant information’s interference and improve long dialogue context tracking. |
| Outcome: | The proposed model significantly outperforms existing models on the MultiWOZ dataset. |