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Bairu Hou
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2020 – today
- 2024
- [j2]Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang:
A Survey on Data Selection for Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [j1]Jiabao Ji, Guanhua Zhang, Zhaowen Wang, Bairu Hou, Zhifei Zhang, Brian L. Price, Shiyu Chang:
Improving Diffusion Models for Scene Text Editing with Dual Encoders. Trans. Mach. Learn. Res. 2024 (2024) - [c6]Bairu Hou, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang:
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling. ICML 2024 - [c5]Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang:
Advancing the Robustness of Large Language Models through Self-Denoised Smoothing. NAACL (Short Papers) 2024: 246-257 - [i11]Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang:
Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing. CoRR abs/2402.16192 (2024) - [i10]Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang:
A Survey on Data Selection for Language Models. CoRR abs/2402.16827 (2024) - [i9]Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang:
Advancing the Robustness of Large Language Models through Self-Denoised Smoothing. CoRR abs/2404.12274 (2024) - [i8]Bairu Hou, Yang Zhang, Jacob Andreas, Shiyu Chang:
A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation. CoRR abs/2406.06950 (2024) - 2023
- [c4]Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang:
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. ICLR 2023 - [c3]Bairu Hou, Joe O'Connor, Jacob Andreas, Shiyu Chang, Yang Zhang:
PromptBoosting: Black-Box Text Classification with Ten Forward Passes. ICML 2023: 13309-13324 - [i7]Jiabao Ji, Guanhua Zhang, Zhaowen Wang, Bairu Hou, Zhifei Zhang, Brian L. Price, Shiyu Chang:
Improving Diffusion Models for Scene Text Editing with Dual Encoders. CoRR abs/2304.05568 (2023) - [i6]Zhen Zhang, Guanhua Zhang, Bairu Hou, Wenqi Fan, Qing Li, Sijia Liu, Yang Zhang, Shiyu Chang:
Certified Robustness for Large Language Models with Self-Denoising. CoRR abs/2307.07171 (2023) - [i5]Bairu Hou, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang:
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling. CoRR abs/2311.08718 (2023) - 2022
- [i4]Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang:
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. CoRR abs/2212.09254 (2022) - [i3]Bairu Hou, Joe O'Connor, Jacob Andreas, Shiyu Chang, Yang Zhang:
PromptBoosting: Black-Box Text Classification with Ten Forward Passes. CoRR abs/2212.09257 (2022) - 2021
- [c2]Guoyang Zeng, Fanchao Qi, Qianrui Zhou, Tingji Zhang, Zixian Ma, Bairu Hou, Yuan Zang, Zhiyuan Liu, Maosong Sun:
OpenAttack: An Open-source Textual Adversarial Attack Toolkit. ACL (demo) 2021: 363-371 - 2020
- [c1]Bairu Hou, Fanchao Qi, Yuan Zang, Xurui Zhang, Zhiyuan Liu, Maosong Sun:
Try to Substitute: An Unsupervised Chinese Word Sense Disambiguation Method Based on HowNet. COLING 2020: 1752-1757 - [i2]Guoyang Zeng, Fanchao Qi, Qianrui Zhou, Tingji Zhang, Bairu Hou, Yuan Zang, Zhiyuan Liu, Maosong Sun:
OpenAttack: An Open-source Textual Adversarial Attack Toolkit. CoRR abs/2009.09191 (2020) - [i1]Yuan Zang, Bairu Hou, Fanchao Qi, Zhiyuan Liu, Xiaojun Meng, Maosong Sun:
Learning to Attack: Towards Textual Adversarial Attacking in Real-world Situations. CoRR abs/2009.09192 (2020)
Coauthor Index
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last updated on 2024-10-07 21:24 CEST by the dblp team
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