Zi Wang

39 papers · 2013–2026 · 13 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🏃 Academic Marathon (12) 🌍 Conference Polyglot (13) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (13) 🏃 Academic Marathon (12) 🐺 Lone Wolf (3) 🏆 Grand Slam 🗃️ Keyword Collector (175) 📈 Trend Setter 💎 Century Club (36) 🔥 Unstoppable (5) ⚡ Prolific Year (5)

Conferences

NIPS (8) AAAI (7) ICML (5) CVPR (3) ICCV (3) ICLR (3) WACV (3) AISTATS (2) ACL (1) ECCV (1) EMNLP (1) JMLR (1) RSS (1)

Top co-authors

Aihua Zheng (5) Stefanie Jegelka (4) Jin Tang (4) Somesh Jha (3) Chengcheng Li (3) Chansoo Lee (2) Chenglong Li (2) Zhang Li (2) Yudong Chen (2) Ran He (2)

Keywords

gaussian process (8) bayesian optimization (6) knowledge distillation (5) person re-identification (4) model compression (4) regret bound (3) student network (3) autonomous driving (3) online learning (2) teacher network (2) class imbalance (2) gibbs sampling (2) image synthesis (2) filter pruning (2) uncertainty quantification (2) feature extraction (2) metric learning (2) high-dimensional optimization (2) multi-task learning (2) large language model (2)

Papers

DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning AAAI 2026 Semantic-Driven Visual Progressive Refinement for Aerial-Ground Person ReID: A Challenging Large-Scale Benchmark AAAI 2026 Progressive Multi-modal Knowledge Distillation for Multi-spectral Object Re-identification AAAI 2026 Select-Then-Decompose: From Empirical Analysis to Adaptive Selection Strategy for Task Decomposition in Large Language Models EMNLP 2025 Dataset Distillation via Vision-Language Category Prototype ICCV 2025 Deterministic Object Pose Confidence Region Estimation ICCV 2025 Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks ICLR 2025 Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty ICML 2025 ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills RSS 2025 Pre-trained Gaussian Processes for Bayesian Optimization JMLR 2024 Heterogeneous Test-Time Training for Multi-Modal Person Re-identification AAAI 2024 REDUCR: Robust Data Downsampling using Class Priority Reweighting NIPS 2024 Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox NIPS 2024 Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents CVPR 2024 Multi-scale Cross Distillation for Object Detection in Aerial Images ECCV 2024 On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks ICLR 2024 TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving CVPR 2023 Gaussian Process Probes (GPP) for Uncertainty-Aware Probing NIPS 2023 Grammar Prompting for Domain-Specific Language Generation with Large Language Models NIPS 2023 Enhancing Non-line-of-sight Imaging via Learnable Inverse Kernel and Attention Mechanisms ICCV 2023 On Evaluating Multilingual Compositional Generalization with Translated Datasets ACL 2023 Channel Pruning via Lookahead Search Guided Reinforcement Learning WACV 2022 Interact, Embed, and EnlargE: Boosting Modality-Specific Representations for Multi-Modal Person Re-identification AAAI 2022 A Quantitative Geometric Approach to Neural-Network Smoothness NIPS 2022 Online Knowledge Distillation by Temporal-Spatial Boosting WACV 2022 Towards Learning Universal Hyperparameter Optimizers with Transformers NIPS 2022 Robust Multi-Modality Person Re-identification AAAI 2021 Convolutional Neural Network Pruning With Structural Redundancy Reduction CVPR 2021 Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model ICML 2021 Learning Fast Converging, Effective Conditional Generative Adversarial Networks With a Mirrored Auxiliary Classifier WACV 2021 Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis AAAI 2021 Learning sparse relational transition models ICLR 2019 Batched Large-scale Bayesian Optimization in High-dimensional Spaces AISTATS 2018 Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior NIPS 2018 Max-value Entropy Search for Efficient Bayesian Optimization ICML 2017 Batched High-dimensional Bayesian Optimization via Structural Kernel Learning ICML 2017 Optimization as Estimation with Gaussian Processes in Bandit Settings AISTATS 2016 An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization ICML 2015 Scalable Inference for Logistic-Normal Topic Models NIPS 2013