Papers by Guanqiao Chen
FaithLens: Detecting and Explaining Faithfulness Hallucination (2026.findings-acl)
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Shuzheng Si, Qingyi Wang, Haozhe Zhao, Yuzhuo Bai, Guanqiao Chen, Kangyang Luo, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun
| Challenge: | Recent progress in large language models (LLMs) has revolutionized text generation. |
| Approach: | They propose a faithfulness hallucination detection model that can provide binary predictions and corresponding explanations to improve trustworthiness. |
| Outcome: | The proposed model outperforms advanced models on 12 diverse tasks. |
Learning Diverse Responses with Prefix-Conditioned Supervised Fine-Tuning (2026.acl-long)
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| Challenge: | Large language models exhibit highly homogeneous, repetitive responses, resulting in inefficient exploration. |
| Approach: | They propose a method that constructs semantically consistent yet distributionally distinct prior contents to different responses and decouple the one-to-many mapping. |
| Outcome: | The proposed method improves absolute performance by 5.3% and increases generation diversity by 198.3% on average while significantly enhancing output diversity and test-time scaling. |