Huishuai Zhang
助理教授
Researches natural language processing, machine learning and optimization of large models.
Huishuai Zhang's lab at Peking works on large language models and learning theory & optimization. 35 papers since 2023, 33 at top venues, mostly ICML and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 94%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 7 · collecting
- 11 papers2025 · T1 11
- 5 papers2024 · T1 5
- 11 papers2023 · T1 10
T1 venuesOtherVenues: ICML, NeurIPS, EMNLP, ICLR, ACL
Research focuspaper titles that use each topic's words
- Large language models8 papers
- Learning theory & optimization5 papers
- researches natural0 papers
- wangxuan0 papers
- wangxuan institute0 papers
Paper list
From the lab homepage.
20268 papers
- ACL (T1)De-Anonymization at Scale: Authorship Attribution via Sequential Progression
- ACL (T1)Deep Sparse Embedding: Pushing the Sparsity Frontier of Large Language Models with Lookup Operation
- ICML (T1)Do LLMs ``Feel''? Emotion Circuits Discovery and Control
- ICLR (T1)FREAK: A Fine-grained Hallucination Evaluation Benchmark for Advanced MLLMs
- ICLR (T1)MMDuet2: Enhancing Proactive Interaction of Video MLLMs with Multi-Turn Reinforcement Learning
- ICML (T1)OLion: Approaching the Hadamard Ideal by Intersecting Spectral and Implicit Biases
- Findings of the Association for Computational LinguisticsShorten After You are Right: Lazy Length Penalties for Reasoning RL
- ICML (T1)Swe-minisandbox: Container-free reinforcement learning for building software engineering agents
202511 papers
- EMNLP (T1)AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training
- ACL (T1)Efficient Domain Continual Pretraining by Mitigating the Stability Gap
- EMNLP (T1)English as Defense Proxy: Mitigating Multilingual Jailbreak via Eliciting English Safety Knowledge
- ICML (T1)Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
- TMLR (T1)Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model
- NAACL (T1)ReasVQA: Advancing VideoQA with Imperfect Reasoning Process
- EMNLP (T1)ReMamba: Equip Mamba with Effective Long-Sequence Modeling
- NeurIPS (T1)Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
- ICML (T1)Understanding Nonlinear Implicit Bias via Region Counts in Input Space
- IJCAI (T1)Understanding Visual Detail Hallucinations of Large Vision-Language Models
- EMNLP (T1)VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction Format
20245 papers
- ICML (T1)Differentially Private Synthetic Data via Foundation Model APIs 2: Text
- TMLR (T1)Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
- KDD (T1)Randomly-reshuffled Adam can provably converge under non-uniform smoothness
- TMLR (T1)Selective Pre-training for Private Fine-tuning
- NeurIPS (T1)xRAG: Extreme Context Compression for Retrieval-Augmented Generation with One Token
202311 papers
- AISTATS (T1)Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
- NeurIPS (T1)Closing the gap between the upper bound and lower bound of Adam's iteration complexity
- COLT (T1)Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions
- ICLR (T1)Denoising Masked AutoEncoders are Certifiable Robust Vision Learners
- NeurIPS (T1)DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
- ICLR (T1)Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
- NeurIPS (T1)FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
- NeurIPS WorkshopLarge Catapults in Momentum Gradient Descent with Warmup: An Empirical Study
- NeurIPS (T1)On the Generalization Properties of Diffusion Models
- AAAI (T1)Similarity Distribution based Membership Inference Attack on Person Re-identification
- ICDE (T1)UADB: Unsupervised Anomaly Detection Booster
Where alumni went
Alumni are not listed on the lab homepage.
Apply to PekingFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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