Xiaobo Xia

Orcid: 0000-0003-3615-0919

According to our database¹, Xiaobo Xia authored at least 95 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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Links

On csauthors.net:

Bibliography

2026

QuantClaw: Precision Where It Matters for OpenClaw.

[BibT_eX]

[DOI]

CoRR, April, 2026

Omnimodal Dataset Distillation via High-order Proxy Alignment.

[BibT_eX]

[DOI]

CoRR, April, 2026

Walk the Talk: Bridging the Reasoning-Action Gap for Thinking with Images via Multimodal Agentic Policy Optimization.

[BibT_eX]

[DOI]

CoRR, April, 2026

BATQuant: Outlier-resilient MXFP4 Quantization via Learnable Block-wise Optimization.

[BibT_eX]

[DOI]

CoRR, March, 2026

FreeAct: Freeing Activations for LLM Quantization.

[BibT_eX]

[DOI]

CoRR, March, 2026

AUHead: Realistic Emotional Talking Head Generation via Action Units Control.

[BibT_eX]

[DOI]

CoRR, February, 2026

SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models.

[BibT_eX]

[DOI]

CoRR, February, 2026

Do All Individual Layers Help? An Empirical Study of Task-Interfering Layers in Vision-Language Models.

[BibT_eX]

[DOI]

CoRR, February, 2026

APEX: A Decoupled Memory-based Explorer for Asynchronous Aerial Object Goal Navigation.

[BibT_eX]

[DOI]

CoRR, February, 2026

Inject Once Survive Later: Backdooring Vision-Language-Action Models to Persist Through Downstream Fine-tuning.

[BibT_eX]

[DOI]

CoRR, February, 2026

Lingua-SafetyBench: A Benchmark for Safety Evaluation of Multilingual Vision-Language Models.

[BibT_eX]

[DOI]

CoRR, January, 2026

Positive-Unlabeled Reinforcement Learning Distillation for On-Premise Small Models.

[BibT_eX]

[DOI]

CoRR, January, 2026

Generalizable Multimodal Large Language Model Editing via Invariant Trajectory Learning.

[BibT_eX]

[DOI]

CoRR, January, 2026

What Makes Low-Bit Quantization-Aware Training Work for Reasoning LLMs? A Systematic Study.

[BibT_eX]

[DOI]

CoRR, January, 2026

Logic Unseen: Revealing the Logical Blindspots of Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Potent but Stealthy: Rethink Profile Pollution Against Sequential Recommendation via Bi-Level Constrained Reinforcement Paradigm.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Taming Camera-Controlled Video Generation with Verifiable Geometry Reward.

[BibT_eX]

[DOI]

CoRR, December, 2025

ITS3D: Inference-Time Scaling for Text-Guided 3D Diffusion Models.

[BibT_eX]

[DOI]

CoRR, November, 2025

AnchorFlow: Training-Free 3D Editing via Latent Anchor-Aligned Flows.

[BibT_eX]

[DOI]

CoRR, November, 2025

Calibrated Multimodal Representation Learning with Missing Modalities.

[BibT_eX]

[DOI]

CoRR, November, 2025

Potent but Stealthy: Rethink Profile Pollution against Sequential Recommendation via Bi-level Constrained Reinforcement Paradigm.

[BibT_eX]

[DOI]

CoRR, November, 2025

UtilGen: Utility-Centric Generative Data Augmentation with Dual-Level Task Adaptation.

[BibT_eX]

[DOI]

CoRR, October, 2025

OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models.

[BibT_eX]

[DOI]

CoRR, October, 2025

NExT-OMNI: Towards Any-to-Any Omnimodal Foundation Models with Discrete Flow Matching.

[BibT_eX]

[DOI]

CoRR, October, 2025

Principled Multimodal Representation Learning.

[BibT_eX]

[DOI]

CoRR, July, 2025

LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment.

[BibT_eX]

[DOI]

CoRR, June, 2025

Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Score.

[BibT_eX]

[DOI]

CoRR, May, 2025

L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models.

[BibT_eX]

[DOI]

CoRR, May, 2025

VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning.

[BibT_eX]

[DOI]

CoRR, April, 2025

GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents.

[BibT_eX]

[DOI]

CoRR, April, 2025

Continual Multimodal Contrastive Learning.

[BibT_eX]

[DOI]

CoRR, March, 2025

Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction.

[BibT_eX]

[DOI]

CoRR, March, 2025

A three-tier AI solution for equitable glaucoma diagnosis across China's hierarchical healthcare system.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2025

Towards Modality Generalization: A Benchmark and Prospective Analysis.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Multimedia, 2025

DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

DEEM: Diffusion models serve as the eyes of large language models for image perception.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Where, What, Why: Towards Explainable Driver Attention Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

LaVin-DiT: Large Vision Diffusion Transformer.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Transferring Annotator- and Instance-Dependent Transition Matrix for Learning From Crowds.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., November, 2024

Tackling Noisy Labels With Network Parameter Additive Decomposition.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., September, 2024

Regularly Truncated M-Estimators for Learning With Noisy Labels.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

Conditional Consistency Regularization for Semi-Supervised Multi-Label Image Classification.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2024

Towards Modality Generalization: A Benchmark and Prospective Analysis.

[BibT_eX]

[DOI]

CoRR, 2024

MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct.

[BibT_eX]

[DOI]

CoRR, 2024

Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection.

[BibT_eX]

[DOI]

CoRR, 2024

Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception.

[BibT_eX]

[DOI]

CoRR, 2024

Mitigating Label Noise on Graph via Topological Sample Selection.

[BibT_eX]

[DOI]

CoRR, 2024

Open-Vocabulary Segmentation with Unpaired Mask-Text Supervision.

[BibT_eX]

[DOI]

CoRR, 2024

Few-Shot Adversarial Prompt Learning on Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mitigating Label Noise on Graphs via Topological Sample Selection.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Realistic Model Selection for Semi-supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

One-Shot Learning as Instruction Data Prospector for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Dynamics-aware loss for learning with label noise.

[BibT_eX]

[DOI]

Pattern Recognit., December, 2023

Extended $T$T: Learning With Mixed Closed-Set and Open-Set Noisy Labels.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

One Shot Learning as Instruction Data Prospector for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Coreset Selection with Prioritized Multiple Objectives.

[BibT_eX]

[DOI]

CoRR, 2023

VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence.

[BibT_eX]

[DOI]

CoRR, 2023

Multi-Label Noise Transition Matrix Estimation with Label Correlations: Theory and Algorithm.

[BibT_eX]

[DOI]

CoRR, 2023

Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision.

[BibT_eX]

[DOI]

CoRR, 2023

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Harnessing Out-Of-Distribution Examples via Augmenting Content and Style.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Holistic Label Correction for Noisy Multi-Label Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

HumanMAC: Masked Motion Completion for Human Motion Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

A machine learning approach for predicting human shortest path task performance.

[BibT_eX]

[DOI]

Vis. Informatics, 2022

LR-SVM+: Learning Using Privileged Information with Noisy Labels.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2022

Pluralistic Image Completion with Probabilistic Mixture-of-Experts.

[BibT_eX]

[DOI]

CoRR, 2022

Pluralistic Image Completion with Gaussian Mixture Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data.

[BibT_eX]

[DOI]

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Objects in Semantic Topology.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Sample Selection with Uncertainty of Losses for Learning with Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Selective-Supervised Contrastive Learning with Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Learning lightweight super-resolution networks with weight pruning.

[BibT_eX]

[DOI]

Neural Networks, 2021

Kernel Mean Estimation by Marginalized Corrupted Distributions.

[BibT_eX]

[DOI]

CoRR, 2021

Instance Correction for Learning with Open-set Noisy Labels.

[BibT_eX]

[DOI]

CoRR, 2021

BloodCaps: A capsule network based model for the multiclassification of human peripheral blood cells.

[BibT_eX]

[DOI]

Comput. Methods Programs Biomed., 2021

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Robust early-learning: Hindering the memorization of noisy labels.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels.

[BibT_eX]

[DOI]

CoRR, 2020

Parts-dependent Label Noise: Towards Instance-dependent Label Noise.

[BibT_eX]

[DOI]

CoRR, 2020

Class2Simi: A New Perspective on Learning with Label Noise.

[BibT_eX]

[DOI]

CoRR, 2020

Multi-Class Classification from Noisy-Similarity-Labeled Data.

[BibT_eX]

[DOI]

CoRR, 2020

Part-dependent Label Noise: Towards Instance-dependent Label Noise.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Are Anchor Points Really Indispensable in Label-Noise Learning?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Xiaobo Xia

Timeline

Legend:

Links

On csauthors.net:

Bibliography

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