Bo Han

DiCaP: Distribution-Calibrated Pseudo-labeling for Semi-Supervised Multi-Label Learning AAAI 2026 Transferability of Adversarial Attacks in Video-based MLLMs: A Cross-modal Image-to-Video Approach AAAI 2026 Select Before Use: On the Importance of Reference Model Selection in Preference Alignment ACL 2026 From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? ICML 2025 From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium ICML 2025 Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning ICML 2025 Adaptive Localization of Knowledge Negation for Continual LLM Unlearning ICML 2025 COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation ICML 2025 GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs ICML 2025 When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need ICML 2025 A Lens into Interpretable Transformer Mistakes via Semantic Dependency ICML 2025 Learning without Isolation: Pathway Protection for Continual Learning ICML 2025 Instance-dependent Early Stopping ICLR 2025 Understanding and Enhancing the Transferability of Jailbreaking Attacks ICLR 2025 Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond ICLR 2025 Towards Effective Evaluations and Comparisons for LLM Unlearning Methods ICLR 2025 Towards Out-of-Modal Generalization without Instance-level Modal Correspondence ICLR 2025 Fast and Accurate Blind Flexible Docking ICLR 2025 Noisy Test-Time Adaptation in Vision-Language Models ICLR 2025 A Robust Method to Discover Causal or Anticausal Relation ICLR 2025 Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection ICLR 2025 Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation ICLR 2025 Golden Noise for Diffusion Models: A Learning Framework ICCV 2025 Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning EMNLP 2025 Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models COLING 2025 Provable Discriminative Hyperspherical Embedding for Out-of-Distribution Detection AAAI 2025 Eliciting Causal Abilities in Large Language Models for Reasoning Tasks AAAI 2025 One-shot Federated Learning Methods: A Practical Guide IJCAI 2025 Towards Regularized Mixture of Predictions for Class-Imbalanced Semi-Supervised Facial Expression Recognition IJCAI 2025 Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning CVPR 2024 Few-Shot Adversarial Prompt Learning on Vision-Language Models NIPS 2024 Mind the Gap Between Prototypes and Images in Cross-domain Finetuning NIPS 2024 What If the Input is Expanded in OOD Detection? NIPS 2024 FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion NIPS 2024 Pseudo-Private Data Guided Model Inversion Attacks NIPS 2024 Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection NIPS 2024 Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation NIPS 2024 Unveiling Causal Reasoning in Large Language Models: Reality or Mirage? NIPS 2024 Discovery of the Hidden World with Large Language Models NIPS 2024 A Sober Look at the Robustness of CLIPs to Spurious Features NIPS 2024 Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? NIPS 2024 AMD: Autoregressive Motion Diffusion AAAI 2024 Federated Learning with Extremely Noisy Clients via Negative Distillation AAAI 2024 Enhancing Evolving Domain Generalization through Dynamic Latent Representations AAAI 2024 Enhancing Neural Subset Selection: Integrating Background Information into Set Representations ICLR 2024 Negative Label Guided OOD Detection with Pretrained Vision-Language Models ICLR 2024 Robust Training of Federated Models with Extremely Label Deficiency ICLR 2024 FedImpro: Measuring and Improving Client Update in Federated Learning ICLR 2024 Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel ICLR 2024 NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation ICLR 2024 Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs ICLR 2024 On the Over-Memorization During Natural, Robust and Catastrophic Overfitting ICLR 2024 Out-of-Distribution Detection with Negative Prompts ICLR 2024 Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting ICLR 2024 Accurate Forgetting for Heterogeneous Federated Continual Learning ICLR 2024 Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy ICLR 2024 Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation ICLR 2024 Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection ICML 2024 How Interpretable Are Interpretable Graph Neural Networks? ICML 2024 Towards Realistic Model Selection for Semi-supervised Learning ICML 2024 Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency ICML 2024 MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence ICML 2024 Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning ICML 2024 Mitigating Label Noise on Graphs via Topological Sample Selection ICML 2024 Balancing Similarity and Complementarity for Federated Learning ICML 2024 MCM: Multi-condition Motion Synthesis Framework IJCAI 2024 ParsNets: A Parsimonious Composition of Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning IJCAI 2024 Trustworthy Machine Learning under Imperfect Data IJCAI 2024 On the Learnability of Out-of-distribution Detection JMLR 2024 Habitus: Boosting Mobile Immersive Content Delivery through Full-body Pose Tracking and Multipath Networking NSDI 2024 Combating Representation Learning Disparity with Geometric Harmonization NIPS 2023 FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning NIPS 2023 InstanT: Semi-supervised Learning with Instance-dependent Thresholds NIPS 2023 Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis ICCV 2023 Label-Noise Learning with Intrinsically Long-Tailed Data ICCV 2023 Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples ICCV 2023 Holistic Label Correction for Noisy Multi-Label Classification ICCV 2023 Combating Bilateral Edge Noise for Robust Link Prediction NIPS 2023 Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization ICLR 2023 Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning ICLR 2023 A Universal Unbiased Method for Classification from Aggregate Observations ICML 2023 Detecting Out-of-distribution Data through In-distribution Class Prior ICML 2023 Learning to Augment Distributions for Out-of-distribution Detection NIPS 2023 Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources NIPS 2023 Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NIPS 2023 Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping NIPS 2023 Understanding and Improving Feature Learning for Out-of-Distribution Generalization NIPS 2023 Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation ICML 2023 Moderately Distributional Exploration for Domain Generalization ICML 2023 Combating Exacerbated Heterogeneity for Robust Models in Federated Learning ICLR 2023 Out-of-distribution Detection with Implicit Outlier Transformation ICLR 2023 Harnessing Out-Of-Distribution Examples via Augmenting Content and Style ICLR 2023 A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond ICLR 2023 Federated Learning with Bilateral Curation for Partially Class-Disjoint Data NIPS 2023 Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization CVPR 2023 Hard Sample Matters a Lot in Zero-Shot Quantization CVPR 2023 SODA: Robust Training of Test-Time Data Adaptors NIPS 2023 Adjustment and Alignment for Unbiased Open Set Domain Adaptation CVPR 2023 FedFed: Feature Distillation against Data Heterogeneity in Federated Learning NIPS 2023 NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension AAAI 2023 Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability ICML 2023 Exploring Model Dynamics for Accumulative Poisoning Discovery ICML 2023 On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation ICML 2023 Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score ICML 2023 Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023 Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation NIPS 2023 Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization NIPS 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels ICLR 2022 Adversarial Robustness Through the Lens of Causality ICLR 2022 Understanding and Improving Graph Injection Attack by Promoting Unnoticeability ICLR 2022 Reliable Adversarial Distillation with Unreliable Teachers ICLR 2022 Exploiting Class Activation Value for Partial-Label Learning ICLR 2022 Rethinking Class-Prior Estimation for Positive-Unlabeled Learning ICLR 2022 Meta Discovery: Learning to Discover Novel Classes given Very Limited Data ICLR 2022 Exact Shape Correspondence via 2D graph convolution NIPS 2022 Watermarking for Out-of-distribution Detection NIPS 2022 Counterfactual Fairness with Partially Known Causal Graph NIPS 2022 Robust Weight Perturbation for Adversarial Training IJCAI 2022 Is Out-of-Distribution Detection Learnable? NIPS 2022 Synergy-of-Experts: Collaborate to Improve Adversarial Robustness NIPS 2022 Pluralistic Image Completion with Gaussian Mixture Models NIPS 2022 Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks NIPS 2022 Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NIPS 2022 RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning NIPS 2022 Towards Lightweight Black-Box Attack Against Deep Neural Networks NIPS 2022 Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack ICML 2022 Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning ICML 2022 Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network ICML 2022 Understanding Robust Overfitting of Adversarial Training and Beyond ICML 2022 Improving Adversarial Robustness via Mutual Information Estimation ICML 2022 Modeling Adversarial Noise for Adversarial Training ICML 2022 Contrastive Learning with Boosted Memorization ICML 2022 YuZu: Neural-Enhanced Volumetric Video Streaming NSDI 2022 Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization JMLR 2022 Learning from Noisy Pairwise Similarity and Unlabeled Data JMLR 2022 Fair Classification with Instance-dependent Label Noise CLEAR 2022 Instance-Dependent Label-Noise Learning With Manifold-Regularized Transition Matrix Estimation CVPR 2022 EAGAN: Efficient Two-Stage Evolutionary Architecture Search for GANs ECCV 2022 Confidence Scores Make Instance-dependent Label-noise Learning Possible ICML 2021 Instance-dependent Label-noise Learning under a Structural Causal Model NIPS 2021 TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation NIPS 2021 Probabilistic Margins for Instance Reweighting in Adversarial Training NIPS 2021 Geometry-aware Instance-reweighted Adversarial Training ICLR 2021 Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model AAAI 2021 Learning with Group Noise AAAI 2021 Understanding and Improving Early Stopping for Learning with Noisy Labels NIPS 2021 Robust early-learning: Hindering the memorization of noisy labels ICLR 2021 Universal Semi-Supervised Learning NIPS 2021 Pointwise Binary Classification with Pairwise Confidence Comparisons ICML 2021 Maximum Mean Discrepancy Test is Aware of Adversarial Attacks ICML 2021 Provably End-to-end Label-noise Learning without Anchor Points ICML 2021 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels ICML 2021 Towards Defending against Adversarial Examples via Attack-Invariant Features ICML 2021 Learning Diverse-Structured Networks for Adversarial Robustness ICML 2021 Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning NIPS 2020 Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling AAAI 2020 Part-dependent Label Noise: Towards Instance-dependent Label Noise NIPS 2020 Attacks Which Do Not Kill Training Make Adversarial Learning Stronger ICML 2020 Searching to Exploit Memorization Effect in Learning with Noisy Labels ICML 2020 Variational Imitation Learning with Diverse-quality Demonstrations ICML 2020 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust ICML 2020 Learning with Multiple Complementary Labels ICML 2020 A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery IJCAI 2020 Provably Consistent Partial-Label Learning NIPS 2020 Towards Robust ResNet: A Small Step but a Giant Leap IJCAI 2019 How does Disagreement Help Generalization against Label Corruption? ICML 2019 Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations ICML 2019 Are Anchor Points Really Indispensable in Label-Noise Learning? NIPS 2019 Co-teaching: Robust training of deep neural networks with extremely noisy labels NIPS 2018 Masking: A New Perspective of Noisy Supervision NIPS 2018 A Stacking-based Approach to Twitter User Geolocation Prediction ACL 2013 A Support Platform for Event Detection using Social Intelligence EACL 2012 Geolocation Prediction in Social Media Data by Finding Location Indicative Words COLING 2012 Automatically Constructing a Normalisation Dictionary for Microblogs EMNLP 2012 Automatically Constructing a Normalisation Dictionary for Microblogs CONLL 2012 Lexical Normalisation of Short Text Messages: Makn Sens a #twitter ACL 2011 SRL-Based Verb Selection for ESL EMNLP 2010 Semantic Role Labeling for News Tweets COLING 2010 Collective Semantic Role Labeling on Open News Corpus by Leveraging Redundancy COLING 2010