Publications

Please refer to my Google Scholar for up-to-date information.

Language Models

A Theoretical Perspective for Speculative Decoding Algorithm
Ming Yin, Minshuo Chen, Kaixuan Huang, and Mengdi Wang
NeurIPS 2024 [link]
SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths
Kaixuan Huang, Xudong Guo, Mengdi Wang
COLM 2025; ICML 2024 workshop on Efficient Systems for Foundation Models (ES-FoMo) [link] [Code]
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments
Kaixuan Huang*, Yuanhao Qu*, Henry Cousins, William A. Johnson, Di Yin, Mihir Shah, Denny Zhou, Russ Altman, Mengdi Wang, Le Cong
to appear in Nature Biomedical Engineering [link]
Embodied LLM Agents Learn to Cooperate in Organized Teams
Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L. Griffiths, Mengdi Wang
arXiv preprint [link]

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang
ICML 2025 [link] [Website]
Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
Yukang Yang, Declan Campbell, Kaixuan Huang, Mengdi Wang, Jonathan Cohen, Taylor Webb
ICML 2025 [link]

SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors
Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal
ICLR 2025 [link] [Website]
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
Boyi Wei*, Kaixuan Huang*, Yangsibo Huang*, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson
ICML 2024 [link] [Code]
Visual Adversarial Examples Jailbreak Large Language Models
Xiangyu Qi*, Kaixuan Huang*, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal
AAAI 2024 ( Oral ) ICML2023 Adv ML workshop. (Oral) [link] [Code]
AI Risk Management Should Incorporate Both Safety and Security
Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang , Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal
arXiv preprint [link]

Scaling In-Context Demonstrations with Structured Attention
Tianle Cai*, Kaixuan Huang*, Jason D. Lee, Mengdi Wang
ICML 2023 Workshop on Efficient Systems for Foundation Models. [link]

Latent Diffusion Models for Controllable RNA Sequence Generation
Kaixuan Huang*, Yukang Yang*, Kaidi Fu, Yanyi Chu, Le Cong, Mengdi Wang
NeurIPS 2024 Workshop on AI for New Drug Modalities [link]
Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement
Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang
In Advances in Neural Information Processing Systems (NeurIPS), 2023. [link] [Code]
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
Minshuo Chen*, Kaixuan Huang*, Tuo Zhao, Mengdi Wang
In International Conference on Machine Learning (ICML), 2023. [link]

Latent Diffusion Models for Controllable RNA Sequence Generation
Kaixuan Huang*, Yukang Yang*, Kaidi Fu, Yanyi Chu, Le Cong, Mengdi Wang
NeurIPS 2024 Workshop on AI for New Drug Modalities [link]
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments
Kaixuan Huang*, Yuanhao Qu*, Henry Cousins, William A. Johnson, Di Yin, Mihir Shah, Denny Zhou, Russ Altman, Mengdi Wang, Le Cong
arXiv preprint [link]
A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions
Yanyi Chu*, Dan Yu*, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, Mengdi Wang
Nature Machine Intelligence (2024) [link]
Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources
Yikuan Li*, Chengsheng Mao*, Kaixuan Huang*, Hanyin Wang*, Zheng Yu*, Mengdi Wang, Yuan Luo
arxiv preprint [link]
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
Zheng Yu*, Yikuan Li*, Joseph Kim*, Kaixuan Huang*, Yuan Luo, Mengdi Wang
In International Conference on Learning Representations (ICLR), 2023. [link]

Going Beyond Linear RL: Sample Efficient Neural Function Approximation
Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang (alphabetical)
In Advances in Neural Information Processing Systems (NeurIPS), 2021. [link]
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang (alphabetical)
In Advances in Neural Information Processing Systems (NeurIPS), 2021. [link]
A Short Note on the Relationship of Information Gain and Eluder Dimension
Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei (alphabetical)
ICML2021 Workshop on Reinforcement Learning Theory. [link]
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
Xinran Gu*, Kaixuan Huang*, Jingzhao Zhang, Longbo Huang
In Advances in Neural Information Processing Systems (NeurIPS), 2021. [link]
Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- A Neural Tangent Kernel Perspective
Kaixuan Huang*, Yuqing Wang*, Molei Tao, Tuo Zhao
In Advances in Neural Information Processing Systems (NeurIPS), 2020. [link]
On the Convergence of FedAvg on Non-IID Data
Xiang Li*, Kaixuan Huang*, Wenhao Yang*, Shusen Wang, Zhihua Zhang
In International Conference on Learning Representations (ICLR), 2020. (Oral Presentation) [link]