Robust Deep Learning via Reverse Cross-Entropy Training and Thresholding Test. - Tianyu Pang; Chao Du; Jun Zhu 001 (CoRR, 2017)

Discovering Adversarial Examples with Momentum. - Yinpeng Dong; Fangzhou Liao; Tianyu Pang; Xiaolin Hu 001; Jun Zhu 001 (CoRR, 2017)

Boosting Adversarial Attacks With Momentum. - Yinpeng Dong; Fangzhou Liao; Tianyu Pang; Hang Su 006; Jun Zhu 001; Xiaolin Hu 001; Jianguo Li (CVPR, 2018)

Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser. - Fangzhou Liao; Ming Liang; Yinpeng Dong; Tianyu Pang; Xiaolin Hu 001; Jun Zhu 001 (CVPR, 2018)

Max-Mahalanobis Linear Discriminant Analysis Networks. - Tianyu Pang; Chao Du; Jun Zhu 001 (ICML, 2018)

Towards Robust Detection of Adversarial Examples. - Tianyu Pang; Chao Du; Yinpeng Dong; Jun Zhu 001 (NeurIPS, 2018)

Detection of DGA Domains Based on Support Vector Machine. - Yu Chen; Sheng Yan; Tianyu Pang; Rui Chen (SSIC, 2018)

Adversarial Attacks and Defences Competition. - Alexey Kurakin; Ian J. Goodfellow; Samy Bengio; Yinpeng Dong; Fangzhou Liao; Ming Liang; Tianyu Pang; Jun Zhu 001; Xiaolin Hu 001; Cihang Xie; Jianyu Wang 001; Zhishuai Zhang; et al. (CoRR, 2018)

Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks. - Yinpeng Dong; Tianyu Pang; Hang Su 006; Jun Zhu 001 (CVPR, 2019)

Improving Adversarial Robustness via Promoting Ensemble Diversity. - Tianyu Pang; Kun Xu 004; Chao Du; Ning Chen 002; Jun Zhu 001 (ICML, 2019)

Improving Black-box Adversarial Attacks with a Transfer-based Prior. - Shuyu Cheng; Yinpeng Dong; Tianyu Pang; Hang Su 006; Jun Zhu 001 (NeurIPS, 2019)

Benchmarking Adversarial Robustness. - Yinpeng Dong; Qi-An Fu; Xiao Yang; Tianyu Pang; Hang Su 006; Zihao Xiao 002; Jun Zhu 001 (CoRR, 2019)

Benchmarking Adversarial Robustness on Image Classification. - Yinpeng Dong; Qi-An Fu; Xiao Yang; Tianyu Pang; Hang Su 006; Zihao Xiao 002; Jun Zhu 001 (CVPR, 2020)

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness. - Tianyu Pang; Kun Xu 004; Yinpeng Dong; Chao Du; Ning Chen 002; Jun Zhu 001 (ICLR, 2020)

Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks. - Tianyu Pang; Kun Xu 004; Jun Zhu 001 (ICLR, 2020)

Adversarial Distributional Training for Robust Deep Learning. - Yinpeng Dong; Zhijie Deng; Tianyu Pang; Jun Zhu 001; Hang Su 006 (NeurIPS, 2020)

Efficient Learning of Generative Models via Finite-Difference Score Matching. - Tianyu Pang; Taufik Xu; Chongxuan Li; Yang Song 011; Stefano Ermon; Jun Zhu 001 (NeurIPS, 2020)

Boosting Adversarial Training with Hypersphere Embedding. - Tianyu Pang; Xiao Yang; Yinpeng Dong; Taufik Xu; Jun Zhu 001; Hang Su 006 (NeurIPS, 2020)

Boosting Adversarial Training with Hypersphere Embedding. - Tianyu Pang; Xiao Yang; Yinpeng Dong; Kun Xu 004; Hang Su 006; Jun Zhu 001 (CoRR, 2020)

Towards Privacy Protection by Generating Adversarial Identity Masks. - Xiao Yang; Yinpeng Dong; Tianyu Pang; Jun Zhu 001; Hang Su 006 (CoRR, 2020)

Efficient Learning of Generative Models via Finite-Difference Score Matching. - Tianyu Pang; Kun Xu 004; Chongxuan Li; Yang Song 011; Stefano Ermon; Jun Zhu 001 (CoRR, 2020)

Black-box Detection of Backdoor Attacks with Limited Information and Data. - Yinpeng Dong; Xiao Yang; Zhijie Deng; Tianyu Pang; Zihao Xiao 002; Hang Su 006; Jun Zhu 001 (ICCV, 2021)

Towards Face Encryption by Generating Adversarial Identity Masks. - Xiao Yang; Yinpeng Dong; Tianyu Pang; Hang Su 006; Jun Zhu 001; Yuefeng Chen; Hui Xue 001 (ICCV, 2021)

Bag of Tricks for Adversarial Training. - Tianyu Pang; Xiao Yang; Yinpeng Dong; Hang Su 006; Jun Zhu 001 (ICLR, 2021)

Accumulative Poisoning Attacks on Real-time Data. - Tianyu Pang; Xiao Yang; Yinpeng Dong; Hang Su 006; Jun Zhu 001 (NeurIPS, 2021)

Adversarial Training with Rectified Rejection. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CoRR, 2021)

Adversarial Attacks on ML Defense Models Competition. - Yinpeng Dong; Qi-An Fu; Xiao Yang; Wenzhao Xiang 001; Tianyu Pang; Hang Su 006; Jun Zhu 001; Jiayu Tang; Yuefeng Chen; Xiaofeng Mao; Yuan He 011; Hui Xue 001; et al. (CoRR, 2021)

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness. - Xiao Yang; Yinpeng Dong; Wenzhao Xiang 001; Tianyu Pang; Hang Su 006; Jun Zhu 001 (CoRR, 2021)

Unrestricted Adversarial Attacks on ImageNet Competition. - Yuefeng Chen; Xiaofeng Mao; Yuan He 011; Hui Xue 001; Chao Li; Yinpeng Dong; Qi-An Fu; Xiao Yang; Wenzhao Xiang 001; Tianyu Pang; Hang Su 006; Jun Zhu 001; et al. (CoRR, 2021)

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CVPR, 2022)

Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks. - Xiao Yang; Yinpeng Dong; Tianyu Pang; Hang Su 006; Jun Zhu 001 (ECCV (4), 2022)

Exploring Memorization in Adversarial Training. - Yinpeng Dong; Ke Xu; Xiao Yang; Tianyu Pang; Zhijie Deng; Hang Su 006; Jun Zhu 001 (ICLR, 2022)

Robustness and Accuracy Could Be Reconcilable by (Proper) Definition. - Tianyu Pang; Min Lin; Xiao Yang; Jun Zhu 001; Shuicheng Yan (ICML, 2022)

A Closer Look at the Adversarial Robustness of Deep Equilibrium Models. - Zonghan Yang; Tianyu Pang; Yang Liu 005 (NeurIPS, 2022)

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition. - Xiao Yang; Yinpeng Dong; Tianyu Pang; Zihao Xiao 002; Hang Su 006; Jun Zhu 001 (CoRR, 2022)

O(N2) Universal Antisymmetry in Fermionic Neural Networks. - Tianyu Pang; Shuicheng Yan; Min Lin (CoRR, 2022)

Query-Efficient Black-Box Adversarial Attacks Guided by a Transfer-Based Prior. - Yinpeng Dong; Shuyu Cheng; Tianyu Pang; Hang Su 006; Jun Zhu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Exploring Incompatible Knowledge Transfer in Few-shot Image Generation. - Yunqing Zhao; Chao Du; Milad Abdollahzadeh; Tianyu Pang; Min Lin; Shuicheng Yan; Ngai-Man Cheung (CVPR, 2023)

Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows. - Chao Du; Tianbo Li; Tianyu Pang; Shuicheng Yan; Min Lin (ICML, 2023)

Better Diffusion Models Further Improve Adversarial Training. - Zekai Wang; Tianyu Pang; Chao Du; Min Lin; Weiwei Liu 003; Shuicheng Yan (ICML, 2023)

Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics. - Zonghan Yang; Peng Li 030; Tianyu Pang; Yang Liu 005 (ICML, 2023)

Bag of Tricks for Training Data Extraction from Language Models. - Weichen Yu; Tianyu Pang; Qian Liu 012; Chao Du; Bingyi Kang; Yan Huang; Min Lin; Shuicheng Yan (ICML, 2023)

Gaussian Mixture Solvers for Diffusion Models. - Hanzhong Guo; Cheng Lu 011; Fan Bao; Tianyu Pang; Shuicheng Yan; Chao Du; Chongxuan Li (NeurIPS, 2023)

Efficient Diffusion Policies For Offline Reinforcement Learning. - Bingyi Kang; Xiao Ma 006; Chao Du; Tianyu Pang; Shuicheng Yan (NeurIPS, 2023)

On Calibrating Diffusion Probabilistic Models. - Tianyu Pang; Cheng Lu 011; Chao Du; Min Lin; Shuicheng Yan; Zhijie Deng (NeurIPS, 2023)

On Evaluating Adversarial Robustness of Large Vision-Language Models. - Yunqing Zhao; Tianyu Pang; Chao Du; Xiao Yang; Chongxuan Li; Ngai-Man Cheung; Min Lin (NeurIPS, 2023)

Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training. - Yefan Zhou; Tianyu Pang; Keqin Liu; Charles H. Martin; Michael W. Mahoney; Yaoqing Yang (NeurIPS, 2023)

Does Federated Learning Really Need Backpropagation? - Haozhe Feng; Tianyu Pang; Chao Du; Wei Chen 001; Shuicheng Yan; Min Lin (CoRR, 2023)

A Recipe for Watermarking Diffusion Models. - Yunqing Zhao; Tianyu Pang; Chao Du; Xiao Yang; Ngai-Man Cheung; Min Lin (CoRR, 2023)

CoSDA: Continual Source-Free Domain Adaptation. - Haozhe Feng; Zhaorui Yang; Hesun Chen; Tianyu Pang; Chao Du; Minfeng Zhu 001; Wei Chen 001; Shuicheng Yan (CoRR, 2023)

Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics. - Zonghan Yang; Peng Li 030; Tianyu Pang; Yang Liu 005 (CoRR, 2023)

LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition. - Chengsong Huang; Qian Liu 012; Bill Yuchen Lin; Tianyu Pang; Chao Du; Min Lin (CoRR, 2023)

Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning. - Zhaorui Yang; Tianyu Pang; Haozhe Feng; Han Wang; Wei Chen 001; Minfeng Zhu 001; Qian Liu 012 (ACL (1), 2024)

BAFFLE: A Baseline of Backpropagation-Free Federated Learning. - Haozhe Feng; Tianyu Pang; Chao Du; Wei Chen 001; Shuicheng Yan; Min Lin (ECCV (75), 2024)

Model Balancing Helps Low-data Training and Fine-tuning. - Zihang Liu; Yuanzhe Hu; Tianyu Pang; Yefan Zhou; Pu Ren; Yaoqing Yang (EMNLP, 2024)

Finetuning Text-to-Image Diffusion Models for Fairness. - Xudong Shen; Chao Du; Tianyu Pang; Min Lin; Yongkang Wong; Mohan S. Kankanhalli (ICLR, 2024)

Intriguing Properties of Data Attribution on Diffusion Models. - Xiaosen Zheng; Tianyu Pang; Chao Du; Jing Jiang 001; Min Lin (ICLR, 2024)

Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast. - Xiangming Gu; Xiaosen Zheng; Tianyu Pang; Chao Du; Qian Liu 012; Ye Wang 007; Jing Jiang 001; Min Lin (ICML, 2024)

Graph Diffusion Policy Optimization. - Yijing Liu; Chao Du; Tianyu Pang; Chongxuan Li; Min Lin; Wei Chen 001 (NeurIPS, 2024)

Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs. - Xuan Zhang; Chao Du; Tianyu Pang; Qian Liu 012; Wei Gao; Min Lin (NeurIPS, 2024)

Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses. - Xiaosen Zheng; Tianyu Pang; Chao Du; Qian Liu 012; Jing Jiang 001; Min Lin (NeurIPS, 2024)

Benchmarking Large Multimodal Models against Common Corruptions. - Jiawei Zhang; Tianyu Pang; Chao Du; Yi Ren; Bo Li; Min Lin (CoRR, 2024)

Weak-to-Strong Jailbreaking on Large Language Models. - Xuandong Zhao; Xianjun Yang; Tianyu Pang; Chao Du; Lei Li 005; Yu-Xiang Wang 003; William Yang Wang (CoRR, 2024)

Test-Time Backdoor Attacks on Multimodal Large Language Models. - Dong Lu; Tianyu Pang; Chao Du; Qian Liu 012; Xianjun Yang; Min Lin (CoRR, 2024)

Your Large Language Model is Secretly a Fairness Proponent and You Should Prompt it Like One. - Tianlin Li; Xiaoyu Zhang 013; Chao Du; Tianyu Pang; Qian Liu 012; Qing Guo 005; Chao Shen 001; Yang Liu 003 (CoRR, 2024)

Purifying Large Language Models by Ensembling a Small Language Model. - Tianlin Li; Qian Liu 012; Tianyu Pang; Chao Du; Qing Guo 005; Yang Liu 003; Min Lin (CoRR, 2024)

Crafting Heavy-Tails in Weight Matrix Spectrum without Gradient Noise. - Vignesh Kothapalli; Tianyu Pang; Shenyang Deng; Zongmin Liu; Yaoqing Yang (CoRR, 2024)

Revisiting Backdoor Attacks against Large Vision-Language Models. - Siyuan Liang; Jiawei Liang; Tianyu Pang; Chao Du; Aishan Liu; Ee-Chien Chang; Xiaochun Cao (CoRR, 2024)

Denial-of-Service Poisoning Attacks against Large Language Models. - Kuofeng Gao; Tianyu Pang; Chao Du; Yong Yang 001; Shu-Tao Xia; Min Lin (CoRR, 2024)

Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts. - Hongcheng Gao; Tianyu Pang; Chao Du; Taihang Hu; Zhijie Deng; Min Lin (CoRR, 2024)

SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction. - Xuan Zhang; Cunxiao Du; Chao Du; Tianyu Pang; Wei Gao; Min Lin (CoRR, 2024)

Real-time Identity Defenses against Malicious Personalization of Diffusion Models. - Hanzhong Guo; Shen Nie; Chao Du; Tianyu Pang; Hao Sun; Chongxuan Li (CoRR, 2024)

Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models. - Zehan Wang 001; Ziang Zhang; Tianyu Pang; Chao Du; Hengshuang Zhao; Zhou Zhao 001 (CoRR, 2024)

Revisiting Backdoor Attacks against Large Vision-Language Models from Domain Shift. - Siyuan Liang; Jiawei Liang; Tianyu Pang; Chao Du; Aishan Liu; Mingli Zhu; Xiaochun Cao; Dacheng Tao (CVPR, 2025)

Towards Learning on Vertically Partitioned Data with Distributed Differential Privacy. - Ergute Bao; Fei Wei; Yin Yang 001; Xiaokui Xiao; Tianyu Pang; Chao Du (ICDE, 2025)

Bootstrapping Language Models with DPO Implicit Rewards. - Changyu Chen; Zichen Liu; Chao Du; Tianyu Pang; Qian Liu 012; Arunesh Sinha; Pradeep Varakantham; Min Lin (ICLR, 2025)

When Attention Sink Emerges in Language Models: An Empirical View. - Xiangming Gu; Tianyu Pang; Chao Du; Qian Liu 012; Fengzhuo Zhang; Cunxiao Du; Ye Wang 007; Min Lin (ICLR, 2025)

Improved Techniques for Optimization-Based Jailbreaking on Large Language Models. - Xiaojun Jia; Tianyu Pang; Chao Du; Yihao Huang 001; Jindong Gu; Yang Liu 003; Xiaochun Cao; Min Lin (ICLR, 2025)

Improving Long-Text Alignment for Text-to-Image Diffusion Models. - Luping Liu; Chao Du; Tianyu Pang; Zehan Wang 001; Chongxuan Li; Dong Xu (ICLR, 2025)

RegMix: Data Mixture as Regression for Language Model Pre-training. - Qian Liu 012; Xiaosen Zheng; Niklas Muennighoff; Guangtao Zeng; Longxu Dou; Tianyu Pang; Jing Jiang 001; Min Lin (ICLR, 2025)

Scaling up Masked Diffusion Models on Text. - Shen Nie; Fengqi Zhu; Chao Du; Tianyu Pang; Qian Liu 012; Guangtao Zeng; Min Lin; Chongxuan Li (ICLR, 2025)

A Closer Look at Machine Unlearning for Large Language Models. - Xiaojian Yuan; Tianyu Pang; Chao Du; Kejiang Chen; Weiming Zhang 001; Min Lin (ICLR, 2025)

Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates. - Xiaosen Zheng; Tianyu Pang; Chao Du; Qian Liu 012; Jing Jiang 001; Min Lin (ICLR, 2025)

DSAC-T Based Resource Allocation Strategy for Delay Minimization in RIS-Aided MEC Networks. - Tianyu Pang; Fuhao Liu; Xinpei Chen; Jiansong Miao; Junsheng Mu; Zaodi Song (WCNC, 2025)

On Memorization in Diffusion Models. - Xiangming Gu; Chao Du; Tianyu Pang; Chongxuan Li; Min Lin; Ye Wang 007 (Trans. Mach. Learn. Res., 2025)

From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks. - Vignesh Kothapalli; Tianyu Pang; Shenyang Deng; Zongmin Liu; Yaoqing Yang (Trans. Mach. Learn. Res., 2025)

When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training. - Haonan Wang; Qian Liu 012; Chao Du; Tongyao Zhu; Cunxiao Du; Kenji Kawaguchi; Tianyu Pang (Trans. Mach. Learn. Res., 2025)

Improving Your Model Ranking on Chatbot Arena by Vote Rigging. - Rui Min; Tianyu Pang; Chao Du; Qian Liu 012; Minhao Cheng; Min Lin (CoRR, 2025)

Face3DAdv: Exploiting Robust Adversarial 3D Patches on Physical Face Recognition. - Xiao Yang; Longlong Xu; Tianyu Pang; Yinpeng Dong; Yikai Wang 001; Hang Su 006; Jun Zhu 001 (Int. J. Comput. Vis., 2025)

Safety at Scale: A Comprehensive Survey of Large Model Safety. - Xingjun Ma; Yifeng Gao; Yixu Wang; Ruofan Wang; Xin Wang; Ye Sun; Yifan Ding; Hengyuan Xu; Yunhao Chen; Yunhan Zhao; Hanxun Huang; Yige Li; et al. (CoRR, 2025)

Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs. - Longxu Dou; Qian Liu 012; Fan Zhou; Changyu Chen; Zili Wang; Ziqi Jin; Zichen Liu; Tongyao Zhu; Cunxiao Du; Penghui Yang 001; Haonan Wang; Jiaheng Liu; et al. (CoRR, 2025)

LongSpec: Long-Context Speculative Decoding with Efficient Drafting and Verification. - Penghui Yang 001; Cunxiao Du; Fengzhuo Zhang; Haonan Wang; Tianyu Pang; Chao Du; Bo An 001 (CoRR, 2025)

Unnatural Languages Are Not Bugs but Features for LLMs. - Keyu Duan; Yiran Zhao 006; Zhili Feng; Jinjie Ni; Tianyu Pang; Qian Liu 012; Tianle Cai; Longxu Dou; Kenji Kawaguchi; Anirudh Goyal; J. Zico Kolter; Michael Qizhe Shieh (CoRR, 2025)

Error Analyses of Auto-Regressive Video Diffusion Models: A Unified Framework. - Jing Wang 060; Fengzhuo Zhang; Xiaoli Li 001; Vincent Y. F. Tan; Tianyu Pang; Chao Du; Aixin Sun; Zhuoran Yang (CoRR, 2025)

SkyLadder: Better and Faster Pretraining via Context Window Scheduling. - Tongyao Zhu; Qian Liu 012; Haonan Wang; Shiqi Chen; Xiangming Gu; Tianyu Pang; Min-Yen Kan (CoRR, 2025)

Understanding R1-Zero-Like Training: A Critical Perspective. - Zichen Liu; Changyu Chen; Wenjun Li; Penghui Qi; Tianyu Pang; Chao Du; Wee Sun Lee; Min Lin (CoRR, 2025)

Efficient Process Reward Model Training via Active Learning. - Keyu Duan; Zichen Liu; Xin Mao; Tianyu Pang; Changyu Chen; Qiguang Chen; Michael Qizhe Shieh; Longxu Dou (CoRR, 2025)

NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation. - Xiangyan Liu; Jinjie Ni; Zijian Wu 003; Chao Du; Longxu Dou; Haonan Wang; Tianyu Pang; Michael Qizhe Shieh (CoRR, 2025)

FlowReasoner: Reinforcing Query-Level Meta-Agents. - Hongcheng Gao; Yue Liu 008; Yufei He; Longxu Dou; Chao Du; Zhijie Deng; Bryan Hooi; Min Lin; Tianyu Pang (CoRR, 2025)

Optimizing Anytime Reasoning via Budget Relative Policy Optimization. - Penghui Qi; Zichen Liu; Tianyu Pang; Chao Du; Wee Sun Lee; Min Lin (CoRR, 2025)

BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms. - Yunlong Hou 001; Fengzhuo Zhang; Cunxiao Du; Xuan Zhang; Jiachun Pan; Tianyu Pang; Chao Du; Vincent Y. F. Tan; Zhuoran Yang (CoRR, 2025)

QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design. - Benjamin Schneider; Dongfu Jiang; Chao Du; Tianyu Pang; Wenhu Chen (CoRR, 2025)

Lifelong Safety Alignment for Language Models. - Haoyu Wang; Zeyu Qin; Yifei Zhao; Chao Du; Min Lin; Xueqian Wang; Tianyu Pang (CoRR, 2025)

Reinforcing General Reasoning without Verifiers. - Xiangxin Zhou; Zichen Liu; Anya Sims; Haonan Wang; Tianyu Pang; Chongxuan Li; Liang Wang; Min Lin; Chao Du (CoRR, 2025)

Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment. - Xiaojun Jia; Sensen Gao; Simeng Qin; Tianyu Pang; Chao Du; Yihao Huang 001; Xinfeng Li; Yiming Li 004; Bo Li; Yang Liu 003 (CoRR, 2025)

Fostering Video Reasoning via Next-Event Prediction. - Haonan Wang; Hongfu Liu 002; Xiangyan Liu; Chao Du; Kenji Kawaguchi; Ye Wang 007; Tianyu Pang (CoRR, 2025)

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning. - Zihang Liu; Tianyu Pang; Oleg Balabanov; Chaoqun Yang; Tianjin Huang; Lu Yin 006; Yaoqing Yang; Shiwei Liu 003 (CoRR, 2025)

Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets. - Lei Hsiung; Tianyu Pang; Yung-Chen Tang; Linyue Song; Tsung-Yi Ho; Pin-Yu Chen; Yaoqing Yang (CoRR, 2025)