Papers by Qingqing Zhao
A Unified Framework for Synaesthesia Analysis (2023.findings-emnlp)
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| Challenge: | Synaesthesia is a cognitive phenomenon structuring human thought and action, which makes understanding it challenging. |
| Approach: | They propose a framework for annotating synaesthetic elements and exploring their relationship . they propose to include sensory modalities, cues and stimuli in the framework . |
| Outcome: | The proposed framework yields state-of-the-art results, demonstrating its effectiveness. |
Convert Language Model into a Value-based Strategic Planner (2025.acl-industry)
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| Challenge: | Emotional support conversation (ESC) aims to alleviate the emotional distress of individuals through effective conversations. |
| Approach: | They propose a framework that bootstraps the planning during ESC and determines the optimal strategy based on long-term returns. |
| Outcome: | The proposed framework outperforms baseline models on ESC datasets and can be used to guide the LLM to response. |
Combining Curriculum Learning and Knowledge Distillation for Dialogue Generation (2021.findings-emnlp)
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| Challenge: | Existing studies have shown that curriculum learning facilitates dialogue generation tasks while knowledge distillation can yield significant performance boosts for student models. |
| Approach: | They propose a combination of curriculum learning and knowledge distillation for dialogue generation models . they cluster training cases according to their complexity and employ an adversarial training strategy . |
| Outcome: | The proposed model improves compared with baselines. |
Chinese Synesthesia Detection: New Dataset and Models (2022.findings-acl)
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| Challenge: | Synesthesia refers to the description of perceptions in one sensory modality through concepts from other modalities. |
| Approach: | They propose a task called synesthesia detection to extract the sensory word of a sentence and predict the original and synesthetic sensory modalities of the corresponding sensory word. |
| Outcome: | The proposed model achieves state-of-the-art on the Chinese synesthesia dataset. |
Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling (2025.findings-emnlp)
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Yue Zhao, Xiaoyu Wang, Dan Wang, Zhonglin Jiang, Qingqing Gu, Teng Chen, Ningyuan Xi, Jinxian Qu, Yong Chen, Luo Ji
| Challenge: | a framework for constructing dialogue world models for natural language tasks is currently lacking. |
| Approach: | They propose a framework that can be used to train a dialogue world model. |
| Outcome: | The proposed framework can predict future utterances and user beliefs . it can achieve state-of-the-art performance on emotion classification and sentiment identification . |