Papers by Yafei Zhao
CroAno : A Crowd Annotation Platform for Improving Label Consistency of Chinese NER Dataset (2021.emnlp-demo)
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Baoli Zhang, Zhucong Li, Zhen Gan, Yubo Chen, Jing Wan, Kang Liu, Jun Zhao, Shengping Liu, Yafei Shi
| Challenge: | Existing crowd annotation tools for named entity recognition (NER) focus on efficiency and don't consider consistency of datasets. |
| Approach: | They propose a crowd annotation platform for Chinese named entity recognition (NER) CroAno provides a systematic solution for improving label consistency of Chinese NER datasets. |
| Outcome: | The proposed platform improves label consistency of Chinese NER datasets. |
Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management (2021.naacl-main)
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| Challenge: | Existing research on taskoriented dialog systems mainly includes pipeline and end-to-end methods due to its non-differentiable nature. |
| Approach: | They propose a multi-level reward modeling approach that factorizes a reward into a three-level hierarchy: domain, act, and slot. |
| Outcome: | The proposed approach significantly improves performance and speed of training in a wide range of dialog systems. |
Biomedical Concept Normalization by Leveraging Hypernyms (2021.emnlp-main)
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| Challenge: | Biomedical Concept Normalization (BCN) is widely used in biomedical text processing . despite numerous surface variants of biomedically-defined concepts, it remains challenging and unsolved. |
| Approach: | They propose a framework that uses hypernyms and synonyms to facilitate BCN . they use list-wise training to make use of both hypernies and synonym entities . |
| Outcome: | The proposed framework outperforms the state-of-the-art model on the NCBI dataset. |
ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs (2026.acl-long)
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| Challenge: | NVFP4 supports fine-grained block isolation, 4-bit quantization errors and mixed-precision approaches . ARCQuant boosts NVFO4 performance via Augmented Residual Channels . |
| Approach: | They propose a framework that boosts NVFP4 performance via Augmented Residual Channels. |
| Outcome: | ARCQuant boosts NVFP4 performance via Augmented Residual Channels . the proposed framework achieves state-of-the-art accuracy comparable to full-precision baselines compared to FP16 . |