Papers by Xinrong Hu
[MASK] Insertion: a robust method for anti-adversarial attacks (2023.findings-eacl)
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| Challenge: | Existing studies have focused on adversarial defenses against pretrained language models. |
| Approach: | They propose an adversarial defensing algorithm that inserts tokens into input sequences . they show an improvement in accuracy between 3.2 and 11.1 absolute points . |
| Outcome: | The proposed algorithm improves model accuracy on clean and polluted inputs compared with state-of-the-art models . |
Seeing the wood for the trees: a contrastive regularization method for the low-resource Knowledge Base Question Answering (2022.findings-naacl)
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| Challenge: | Existing methods for Knowledge Base Question Answering rely on semantic parsing and information retrieval. |
| Approach: | They propose a contrastive regularization based method to extract correct answer entities from a context knowledge base and a corresponding question. |
| Outcome: | The proposed method achieves state-of-the-art performance on the WebQuestionsSP dataset and the effectiveness of proposed modules is also evaluated. |
Beyond the Turn-Based Game: Enabling Real-Time Conversations with Duplex Models (2024.emnlp-main)
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Xinrong Zhang, Yingfa Chen, Shengding Hu, Xu Han, Zihang Xu, Yuanwei Xu, Weilin Zhao, Maosong Sun, Zhiyuan Liu
| Challenge: | Large language models (LLMs) are increasingly permeating daily lives and require real-time interactions that mirror human conversations. |
| Approach: | They propose to use time-division-multiplexing to process queries and responses pseudo-simultaneously. |
| Outcome: | The proposed model can listen to users while generating output and adjust to provide instant feedback. |
DNASpeech: A Contextualized and Situated Text-to-Speech Dataset with Dialogues, Narratives and Actions (2025.acl-long)
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| Challenge: | Existing TTS datasets lack situated descriptive prompts aligned with speech data. |
| Approach: | They propose a contextualized and situated text-to-speech task to promote more accurate and customized speech generation using DNA prompts. |
| Outcome: | The proposed task promotes more accurate and customized speech generation using DNA prompts. |