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Yan Zhu

17 papers · 2013–2025 · 9 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (12) 🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (38)
🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (12) ⚑ Prolific Year (6) πŸš€ Conference Pioneer πŸ’Ž Century Club (17) πŸ—ƒοΈ Keyword Collector (65) ❓ The Questioner

Conferences

AAAI (3) CVPR (3) IJCAI (3) MICCAI (2) NAACL (2) AISTATS (1) EMNLP (1) ICML (1) NIPS (1)

Papers

Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements ICML 2025 Overview of EvaHan2025: The First International Evaluation on Ancient Chinese Named Entity Recognition NAACL 2025 Exploring Task-Level Optimal Prompts for Visual In-Context Learning AAAI 2025 Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model AAAI 2025 Endo-CLIP: Progressive Self-Supervised Pre-training on Raw Colonoscopy Records MICCAI 2025 Exact: Exploring Space-Time Perceptive Clues for Weakly Supervised Satellite Image Time Series Semantic Segmentation CVPR 2025 MaskClustering: View Consensus based Mask Graph Clustering for Open-Vocabulary 3D Instance Segmentation CVPR 2024 MISA: MIning Saliency-Aware Semantic Prior for Box Supervised Instance Segmentation IJCAI 2024 SportQA: A Benchmark for Sports Understanding in Large Language Models NAACL 2024 EndoFinder: Online Image Retrieval for Explainable Colorectal Polyp Diagnosis MICCAI 2024 Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? NIPS 2023 Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning AAAI 2022 Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder EMNLP 2020 Time Series Chains: A Novel Tool for Time Series Data Mining IJCAI 2018 Semantic Amodal Segmentation CVPR 2017 Semi-Universal Portfolios with Transaction Costs IJCAI 2015 Computing the M Most Probable Modes of a Graphical Model AISTATS 2013