Bin Hu

44 papers · 2017–2026 · 16 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (9) 🐝 Cross-Pollinator (14) 🗺️ Taxonomy Completionist (14) 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (15) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🧬 Topic Evolution 🏆 Keyword Champion (4) 🏆 Grand Slam 🗃️ Keyword Collector (171) 🚀 Conference Pioneer 💎 Century Club (40) 🔥 Unstoppable (10) 📈 Trend Setter ⚡ Prolific Year (8)

Conferences

AAAI (7) NIPS (7) ICML (6) ICLR (5) IJCAI (4) INTERSPEECH (3) L4DC (3) ACL (1) COLT (1) CVPR (1) EACL (1) EMNLP (1) ICCV (1) MICCAI (1) NSDI (1) WACV (1)

Top co-authors

Alexandre Araujo (6) Aaron J Havens (5) Xingang Guo (4) Huan Zhang (4) Xiping Hu (3) Kaiqing Zhang (3) Tamer Basar (3) Chenyang Zhao (2) Fa Zhang (2) Haocong Rao (2)

Keywords

robust control (4) self-supervised learning (4) large language model (3) h-infinity control (3) diffusion model (3) graph neural network (2) dissipativity theory (2) gait recognition (2) convergence rate (2) derivative-free optimization (2) sample complexity (2) reinforcement learning (2) skeleton datum (2) person re-identification (2) semidefinite program (2) policy optimization (2) knowledge distillation (2) multimodal learning (2) non-convex optimization (1) finite-sum optimization (1)

Papers

Strong Memory, Weak Control: An Empirical Study of Executive Functioning in LLMs EACL 2026

Venom: Liquid Diffusion-Guided Gradient Inversion for Breaking Differential Privacy in Federated Learning AAAI 2026

SOLAR: Switchable Output Layer for Accuracy and Robustness in Once-for-All Training WACV 2026

ST-LLM: Spatial Transcriptomics Embedding with Large Language Models AAAI 2026

Cyto-SSL: A Self-Supervised Pretraining Framework for Cytology Foundation Model AAAI 2026

External Memory Matters: Generalizable Object-Action Memory for Retrieval-Augmented Long-Term Video Understanding IJCAI 2025

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching ICML 2025

PhysDiff: Physiology-based Dynamicity Disentangled Diffusion Model for Remote Physiological Measurement AAAI 2025

How LLMs Comprehend Temporal Meaning in Narratives: A Case Study in Cognitive Evaluation of LLMs ACL 2025

VLASCD: A Visual Language Action Model for Simultaneous Chatting and Decision Making EMNLP 2025

Surface Vision Mamba: Leveraging Bidirectional State Space Model for Efficient Spherical Manifold Representation MICCAI 2025

Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems L4DC 2025

DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models ICLR 2025

NN-Defined Modulator: Reconfigurable and Portable Software Modulator on IoT Gateways NSDI 2024

Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations ICLR 2024

Study Selectively: An Adaptive Knowledge Distillation based on a Voting Network for Heart Sound Classification INTERSPEECH 2024

E-ODN: An Emotion Open Deep Network for Generalised and Adaptive Speech Emotion Recognition INTERSPEECH 2024

Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents IJCAI 2024

Focus Stacking with High Fidelity and Superior Visual Effects AAAI 2024

Structural Information Enhanced Graph Representation for Link Prediction AAAI 2024

COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability ICML 2024

On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks ICLR 2024

Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention ICML 2024

Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control NIPS 2023

Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability NIPS 2023

Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models NIPS 2023

See Your Emotion from Gait Using Unlabeled Skeleton Data AAAI 2023

A Unified Algebraic Perspective on Lipschitz Neural Networks ICLR 2023

JAMFN: Joint Attention Multi-Scale Fusion Network for Depression Detection INTERSPEECH 2023

Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out ICML 2022

Global Convergence of Direct Policy Search for State-Feedback $\mathcal{H}_\infty$ Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential NIPS 2022

Multi-Level Graph Encoding with Structural-Collaborative Relation Learning for Skeleton-Based Person Re-Identification IJCAI 2021

Weakly-Supervised Instance Segmentation via Class-Agnostic Learning With Salient Images CVPR 2021

Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity NIPS 2021

Self-Supervised Gait Encoding with Locality-Aware Attention for Person Re-Identification IJCAI 2020

On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems NIPS 2020

Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence L4DC 2020

Policy Learning of MDPs with Mixed Continuous/Discrete Variables: A Case Study on Model-Free Control of Markovian Jump Systems L4DC 2020

Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory NIPS 2019

Learning Intrinsic Sparse Structures within Long Short-Term Memory ICLR 2018

Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs ICML 2018

A Joint Intrinsic-Extrinsic Prior Model for Retinex ICCV 2017

A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints COLT 2017

Dissipativity Theory for Nesterov’s Accelerated Method ICML 2017