Weiran Huang

27 papers · 2018–2025 · 10 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🌍 Conference Polyglot (10) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (7)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (7) 🏆 Grand Slam 👑 Triple Crown 🗃️ Keyword Collector (83) ⚡ Prolific Year (7) 🚀 Conference Pioneer 💎 Century Club (27) ❓ The Questioner

Conferences

ICML (8) NIPS (6) AAAI (3) ICLR (3) ICCV (2) AISTATS (1) CVPR (1) ECCV (1) IJCAI (1) NAACL (1)

Top co-authors

Zhiquan Tan (7) Zhenguo Li (4) Xuyang Zhao (4) Kaipeng Zheng (3) Liwei Wang (3) Liang Li (2) Jingqin Yang (2) Jun Yao (2) Aoxue Li (2) Bochao Zou (2)

Research topics

Differential Privacy (1) Optimization & Theory (1)

Keywords

few-shot learning (4) transfer learning (3) multi-armed bandit (3) feature alignment (2) pre-trained model (2) contrastive learning (2) noisy label (2) sample complexity (2) metric learning (2) representation learning (2) large language model (2) regret bound (2) domain generalization (1) online learning (1) feature learning (1) prior learning (1) attention mechanism (1) semi-supervised learning (1) self-supervised learning (1) multivariate gaussian (1)

Papers

FinLLM-B: When Large Language Models Meet Financial Breakout Trading NAACL 2025 Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization ICML 2025 Unveiling the Dynamics of Information Interplay in Supervised Learning ICML 2024 Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models NIPS 2024 SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models NIPS 2024 A Statistical Theory of Regularization-Based Continual Learning ICML 2024 Matrix Information Theory for Self-Supervised Learning ICML 2024 Provable Contrastive Continual Learning ICML 2024 AutoEval-Video: An Automatic Benchmark for Assessing Large Vision Language Models in Open-Ended Video Question Answering ECCV 2024 OTMatch: Improving Semi-Supervised Learning with Optimal Transport ICML 2024 Information Flow in Self-Supervised Learning ICML 2024 When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method ICCV 2023 FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning NIPS 2023 DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation NIPS 2023 Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding ICLR 2023 ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations ICLR 2023 Towards the Generalization of Contrastive Self-Supervised Learning ICLR 2023 Rethinking Weak Supervision in Helping Contrastive Learning ICML 2023 Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis AISTATS 2022 Boosting Few-Shot Learning With Adaptive Margin Loss CVPR 2020 Locally Differentially Private (Contextual) Bandits Learning NIPS 2020 New Interpretations of Normalization Methods in Deep Learning AAAI 2020 Meta-Learning PAC-Bayes Priors in Model Averaging AAAI 2020 Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks AAAI 2019 Few-Shot Learning With Global Class Representations ICCV 2019 Community Exploration: From Offline Optimization to Online Learning NIPS 2018 Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications IJCAI 2018