Papers by Wynne Hsu
Improving Evidence Retrieval for Automated Explainable Fact-Checking (2021.naacl-demos)
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| Challenge: | Automated fact-checking on a large scale is time consuming and intractable. |
| Approach: | They propose a three-stage automated fact-checking system using evidence retrieval and selection methods to improve evidence recall in a noisy environment. |
| Outcome: | The proposed system can verify open-domain claims using results from web search engines. |
Time Matters: An End-to-End Solution for Temporal Claim Verification (2024.emnlp-industry)
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| Challenge: | despite growing interest, the verification of temporal claims has not received much attention in the digital space. |
| Approach: | They propose an end-to-end solution that takes cues of temporal information and extracts relevant evidence sentences from temporal claims. |
| Outcome: | The proposed method significantly improves accuracy of temporal claim verification. |
Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve Framework (2025.acl-long)
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Jundong Xu, Hao Fei, Meng Luo, Qian Liu, Liangming Pan, William Yang Wang, Preslav Nakov, Mong-Li Lee, Wynne Hsu
| Challenge: | Existing systems fail to fully leverage the structure of logical tasks throughout the reasoning process, causing bottlenecks in efficiency and efficacy. |
| Approach: | They propose a logic-complete reasoning framework, Aristotle, which integrates symbolic expressions and logical rules into the entire reasoning process. |
| Outcome: | The proposed framework outperforms state-of-the-art reasoning frameworks in accuracy and efficiency. |
From Personas to Talks: Revisiting the Impact of Personas on LLM-Synthesized Emotional Support Conversations (2025.emnlp-main)
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| Challenge: | Experimental results show that LLMs can infer persona traits and subtle shifts in emotionality and extraversion occur . scalable solutions with reduced costs and enhanced data privacy are needed . |
| Approach: | They explore the role of personas in the creation of emotional support conversations by LLMs. |
| Outcome: | The proposed model can infer persona traits and maintain key persona characteristics while revealing shifts in emotionality and extraversion. |
TRUST-VL: An Explainable News Assistant for General Multimodal Misinformation Detection (2025.emnlp-main)
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| Challenge: | Existing methods focus on a single type of distortion and struggle to generalize to unseen scenarios. |
| Approach: | They propose a vision-language model that combines a question-aware visual amplifier module with a large-scale instruction dataset to support training. |
| Outcome: | The proposed model is able to generalize to multiple distortion types while requiring task-specific skills. |
Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment (2026.acl-long)
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| Challenge: | Large Language Models (LLMs) have enabled the development of powerful autonomous systems. |
| Approach: | They propose a model trained through dialectical alignment to enforce perspective-invariant reasoning. |
| Outcome: | The proposed model mitigates attribution inconsistency and significantly improves fault resolution rates in ambiguous scenarios. |
Faithful Logical Reasoning via Symbolic Chain-of-Thought (2024.acl-long)
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| Challenge: | SymbCoT is a framework that integrates symbolic expressions and logic rules with CoT prompting. |
| Approach: | They propose a Symbolic Chain-of-Thought framework that integrates symbolic expressions and logic rules with CoT prompting. |
| Outcome: | The proposed framework improves on 5 standard datasets with symbolic expressions and rules . it shows that it is more faithful, flexible, and explainable than the current method . |