Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency. - Shuhuai Ren; Yihe Deng; Kun He 001; Wanxiang Che (ACL (1), 2019)

Adaptive Wavelet Clustering for Highly Noisy Data. - Zengjian Chen; Jiayi Liu; Yihe Deng; Kun He 001; John E. Hopcroft (ICDE, 2019)

Adversarial Training with Fast Gradient Projection Method against Synonym Substitution Based Text Attacks. - Xiaosen Wang; Yichen Yang 009; Yihe Deng; Kun He 001 (AAAI, 2021)

Towards Understanding the Mixture-of-Experts Layer in Deep Learning. - Zixiang Chen; Yihe Deng; Yue Wu; Quanquan Gu; Yuanzhi Li (NeurIPS, 2022)

Towards Understanding Mixture of Experts in Deep Learning. - Zixiang Chen; Yihe Deng; Yue Wu; Quanquan Gu; Yuanzhi Li (CoRR, 2022)

A Short Text Classification Model Based on Chinese Part-of-Speech Information and Mutual Learning. - Yihe Deng; Zuxu Dai (ICPCSEE (2), 2023)

Robust Learning with Progressive Data Expansion Against Spurious Correlation. - Yihe Deng; Yu Yang 007; Baharan Mirzasoleiman; Quanquan Gu (NeurIPS, 2023)

Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves. - Yihe Deng; Weitong Zhang; Zixiang Chen; Quanquan Gu (CoRR, 2023)

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP. - Zixiang Chen; Yihe Deng; Yuanzhi Li; Quanquan Gu (ICLR, 2024)

Risk Bounds of Accelerated SGD for Overparameterized Linear Regression. - Xuheng Li; Yihe Deng; Jingfeng Wu; Dongruo Zhou; Quanquan Gu (ICLR, 2024)

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models. - Zixiang Chen; Yihe Deng; Huizhuo Yuan; Kaixuan Ji; Quanquan Gu (ICML, 2024)

GraphVis: Boosting LLMs with Visual Knowledge Graph Integration. - Yihe Deng; Chenchen Ye 001; Zijie Huang 002; Mingyu Derek Ma; Yiwen Kou; Wei Wang 010 (NeurIPS, 2024)

Enhancing Large Vision Language Models with Self-Training on Image Comprehension. - Yihe Deng; Pan Lu; Fan Yin; Ziniu Hu; Sheng Shen 001; Quanquan Gu; James Y. Zou; Kai-Wei Chang; Wei Wang 010 (NeurIPS, 2024)

Mitigating Object Hallucination in Large Vision-Language Models via Classifier-Free Guidance. - Linxi Zhao; Yihe Deng; Weitong Zhang; Quanquan Gu (CoRR, 2024)

Enhancing Large Vision Language Models with Self-Training on Image Comprehension. - Yihe Deng; Pan Lu; Fan Yin; Ziniu Hu; Sheng Shen 001; James Zou 001; Kai-Wei Chang; Wei Wang 010 (CoRR, 2024)

MIRAI: Evaluating LLM Agents for Event Forecasting. - Chenchen Ye 001; Ziniu Hu; Yihe Deng; Zijie Huang 002; Mingyu Derek Ma; Yanqiao Zhu 001; Wei Wang 010 (CoRR, 2024)

Flow-DPO: Improving LLM Mathematical Reasoning through Online Multi-Agent Learning. - Yihe Deng; Paul Mineiro (CoRR, 2024)

Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning. - Yihe Deng; Ruochi Zhang; Pan Xu 002; Jian Ma 004; Quanquan Gu (Trans. Mach. Learn. Res., 2024)

On the Power of Multitask Representation Learning with Gradient Descent. - Qiaobo Li; Zixiang Chen; Yihe Deng; Yiwen Kou; Yuan Cao 006; Quanquan Gu (AISTATS, 2025)

DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM Guardrails. - Yihe Deng; Yu Yang; Junkai Zhang; Wei Wang; Bo Li (CoRR, 2025)

OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement. - Yihe Deng; Hritik Bansal; Fan Yin; Nanyun Peng 001; Wei Wang 010; Kai-Wei Chang (CoRR, 2025)

Entropy-Based Adaptive Weighting for Self-Training. - Xiaoxuan Wang; Yihe Deng; Mingyu Derek Ma; Wei Wang 010 (CoRR, 2025)

More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment. - Yifan Wang; Runjin Chen; Bolian Li; David Cho; Yihe Deng; Ruqi Zhang; Tianlong Chen 001; Zhangyang Wang; Ananth Grama; Junyuan Hong (CoRR, 2025)