Papers by Jincenzi Wu
Depression Detection in Clinical Interviews with LLM-Empowered Structural Element Graph (2024.naacl-long)
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| Challenge: | Existing methods for assessing depression only capture part of relevant elements . scarcity of participant data constrains interview modeling due to privacy concerns . |
| Approach: | They propose a structural element graph (SEGA) that transforms clinical interviews into an expertise-inspired directed acyclic graph for comprehensive modeling. |
| Outcome: | The proposed model outperforms baseline methods and powerful LLMs on two real-world clinical datasets. |
SocialCC: Interactive Evaluation for Cultural Competence in Language Agents (2025.acl-long)
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| Challenge: | Existing studies have evaluated cultural knowledge of large language models, but they fail to assess dynamic cultural competence. |
| Approach: | They propose a benchmark to assess cultural competence through intercultural scenarios that span 60 countries across six continents. |
| Outcome: | The proposed benchmark measures the ability of large language models to apply cultural knowledge effectively in cross-cultural interactions. |
InSerter: Speech Instruction Following with Unsupervised Interleaved Pre-training (2025.acl-long)
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Dingdong Wang, Jin Xu, Ruihang Chu, Zhifang Guo, Xiong Wang, Jincenzi Wu, Dongchao Yang, Shengpeng Ji, Junyang Lin
| Challenge: | Recent advances in speech large language models exhibit suboptimal performance in adhering to speech instructions. |
| Approach: | They propose a method to pre-train large-scale unsupervised speech-text sequences . they use text-to-speech conversion to generate textual continuations corresponding to provided speech segments . |
| Outcome: | The proposed model achieves superior or competitive results across diverse speech processing tasks. |