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Zhen Fang

32 papers · 2020–2026 · 10 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (10) 🏃 Academic Marathon (5) 🌉 Interdisciplinary Bridge
🐣 Hot Topic Early Bird 🌍 Conference Polyglot (10) 🏃 Academic Marathon (5) 🤝 Dynamic Duo (11) 👑 Triple Crown 🏆 Grand Slam 🏆 Keyword Champion (2) 💎 Century Club (30) The Questioner (3) Prolific Year (9) 🗃️ Keyword Collector (95) 🔥 Unstoppable (6)

Conferences

ICLR (7) NIPS (7) ICML (5) ACL (3) ICCV (3) CVPR (2) EMNLP (2) AAAI (1) IJCAI (1) JMLR (1)

Papers

Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated Reasoning ACL 2026 UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision ACL 2026 Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach ICML 2025 Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer ICLR 2025 Deep Kernel Relative Test for Machine-generated Text Detection ICLR 2025 On the Provable Importance of Gradients for Autonomous Language-Assisted Image Clustering ICCV 2025 CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios EMNLP 2025 A Semi-supervised Scalable Unified Framework for E-commerce Query Classification ACL 2025 NLPrompt: Noise-Label Prompt Learning for Vision-Language Models CVPR 2025 Negative Label Guided OOD Detection with Pretrained Vision-Language Models ICLR 2024 Learning to Shape In-distribution Feature Space for Out-of-distribution Detection NIPS 2024 ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection ICLR 2024 NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation ICLR 2024 Out-of-Distribution Detection with Negative Prompts ICLR 2024 How Does Unlabeled Data Provably Help Out-of-Distribution Detection? ICLR 2024 Knowledge Distillation with Auxiliary Variable ICML 2024 On the Learnability of Out-of-distribution Detection JMLR 2024 SODA: Robust Training of Test-Time Data Adaptors NIPS 2023 Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources NIPS 2023 Learning to Augment Distributions for Out-of-distribution Detection NIPS 2023 Moderately Distributional Exploration for Domain Generalization ICML 2023 Detecting Out-of-distribution Data through In-distribution Class Prior ICML 2023 Continual Named Entity Recognition without Catastrophic Forgetting EMNLP 2023 KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection ICCV 2023 Meta OOD Learning For Continuously Adaptive OOD Detection ICCV 2023 Invariant Learning via Probability of Sufficient and Necessary Causes NIPS 2023 Is Out-of-Distribution Detection Learnable? NIPS 2022 Federated Class-Incremental Learning CVPR 2022 How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? AAAI 2021 Confident Anchor-Induced Multi-Source Free Domain Adaptation NIPS 2021 Learning Bounds for Open-Set Learning ICML 2021 Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation IJCAI 2020