← Authors

Xiaobo Xia

32 papers · 2019–2026 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (44) πŸ‘‘ Triple Crown πŸ† Keyword Champion 🀝 Dynamic Duo (25) πŸ† Grand Slam πŸ’Ž Century Club (30) ⚑ Prolific Year (6) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (108) πŸ”₯ Unstoppable (7)

Conferences

ICLR (8) NIPS (7) ICML (5) ICCV (4) AAAI (3) CVPR (3) ACL (2)

Top co-authors

Tongliang Liu (25) Bo Han (16) Mingming Gong (6) Jun Yu (6) Chen Gong (5) Min Yang (4) Gang Niu (4) Nannan Wang (4) Yunshui Li (4) Yewen Li (3)

Keywords

noisy label (4) transition matrix (3) label noise (2) instruction datum (2) foundation model (2) noisy label learning (2) out-of-distribution detection (2) multi-label classification (2) label correlation (2) anchor point (2) large language model (2) variational autoencoder (2) vision-language model (2) computer vision (1) domain adaptation (1) robust optimization (1) domain generalization (1) image generation (1) adversarial learning (1) representation learning (1)

Papers

Potent but Stealthy: Rethink Profile Pollution Against Sequential Recommendation via Bi-Level Constrained Reinforcement Paradigm AAAI 2026
Logic Unseen: Revealing the Logical Blindspots of Vision-Language Models AAAI 2026
Where, What, Why: Towards Explainable Driver Attention Prediction ICCV 2025
Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs AAAI 2025
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct ACL 2025
LaVin-DiT: Large Vision Diffusion Transformer CVPR 2025
DEEM: Diffusion models serve as the eyes of large language models for image perception ICLR 2025
DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization ICML 2025
One-Shot Learning as Instruction Data Prospector for Large Language Models ACL 2024
Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints ICML 2024
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models ICLR 2024
Towards Realistic Model Selection for Semi-supervised Learning ICML 2024
Few-Shot Adversarial Prompt Learning on Vision-Language Models NIPS 2024
Mitigating Label Noise on Graphs via Topological Sample Selection ICML 2024
Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples ICCV 2023
Holistic Label Correction for Noisy Multi-Label Classification ICCV 2023
Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning 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
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources NIPS 2023
Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization CVPR 2023
HumanMAC: Masked Motion Completion for Human Motion Prediction ICCV 2023
Selective-Supervised Contrastive Learning With Noisy Labels CVPR 2022
Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning NIPS 2022
Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE NIPS 2022
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels ICLR 2022
Objects in Semantic Topology ICLR 2022
Pluralistic Image Completion with Gaussian Mixture Models NIPS 2022
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels ICML 2021
Robust early-learning: Hindering the memorization of noisy labels ICLR 2021
Part-dependent Label Noise: Towards Instance-dependent Label Noise NIPS 2020
Are Anchor Points Really Indispensable in Label-Noise Learning? NIPS 2019