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Xiong Zhou

18 papers · 2019–2026 · 9 conferences · across top CS/AI conferences

Achievements

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+9 more ↓ πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird
πŸ—ΊοΈ Taxonomy Completionist (31) 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (6) 🀝 Dynamic Duo (11) πŸ† Grand Slam πŸ”₯ Unstoppable (5) πŸ’Ž Century Club (17) ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (65)

Conferences

ICLR (4) ICML (4) ICCV (3) AAAI (2) CVPR (1) ECCV (1) EMNLP (1) JMLR (1) NIPS (1)

Research topics

Papers

Variation-Bounded Loss for Noise-Tolerant Learning AAAI 2026 Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents ICML 2025 Robust Test-Time Adaptation for Single Image Denoising Using Deep Gaussian Prior ICCV 2025 Joint Asymmetric Loss for Learning with Noisy Labels ICCV 2025 Neural Field Classifiers via Target Encoding and Classification Loss ICLR 2024 ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling ECCV 2024 Socratic Human Feedback (SoHF): Expert Steering Strategies for LLM Code Generation EMNLP 2024 $\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise NIPS 2024 Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs ICLR 2024 Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data ICLR 2024 On the Dynamics Under the Unhinged Loss and Beyond JMLR 2023 No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation ICML 2023 Prototype-Anchored Learning for Learning with Imperfect Annotations ICML 2022 Learning Towards The Largest Margins ICLR 2022 Exploiting Invariance in Training Deep Neural Networks AAAI 2022 Asymmetric Loss Functions for Learning with Noisy Labels ICML 2021 Learning With Noisy Labels via Sparse Regularization ICCV 2021 d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding CVPR 2019