Papers by Yating Huang
Revisiting Data Reconstruction Attacks on Real-world Dataset for Federated Natural Language Understanding (2024.lrec-main)
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Zhuo Zhang, Jintao Huang, Xiangjing Hu, Jingyuan Zhang, Yating Zhang, Hui Wang, Yue Yu, Qifan Wang, Lizhen Qu, Zenglin Xu
| Challenge: | Existing DRA methods fail to accurately recover the original text of real-world privacy data. |
| Approach: | They propose to use a real-world privacy dataset to examine the performance of federated learning (FL) methods. |
| Outcome: | The proposed method improves on a real-world privacy dataset and shows that the tokens within a recovery sentence are disordered and intertwined with tokens from other sentences in the same training batch. |
TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice (2026.acl-long)
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| Challenge: | Large Language Models excel in general domains but lack real-world practical capabilities. |
| Approach: | They propose a benchmark for Chinese taxation practice that combines 10 traditional application tasks with 3 pioneering real-world scenarios. |
| Outcome: | The proposed benchmark combines 10 traditional tasks with 3 pioneering real-world scenarios. |
PathoHR: Hierarchical Reasoning for Vision-Language Models in Pathology (2025.findings-emnlp)
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| Challenge: | Current vision-language (VL) models fail to capture complex reasoning required for interpreting structured pathological reports. |
| Approach: | They propose a pathology-specific VL training scheme that generates enhanced and perturbed samples for multimodal contrastive learning. |
| Outcome: | The proposed approach achieves state-of-the-art performance on PathoHR-Bench and six additional pathology datasets, highlighting its effectiveness in fine-grained pathology representation. |