Tongliang Liu

Venues

Frequent coauthors

Papers

1. GUIC: Certified Graph Unlearning with Individual Fairness Guarantees
   AAAI 2026 ·

   Zichong Wang

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2. La La LiDAR: Large-Scale Layout Generation from LiDAR Data
   AAAI 2026 ·

   Youquan Liu

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3. MedDCR: Learning to Design Agentic Workflows for Medical Coding
   ACL 2026 ·

   Jiyang Zheng

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4. Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer
   AAAI 2026 ·

   Jiaheng Wei

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5. Select Before Use: On the Importance of Reference Model Selection in Preference Alignment
   ACL 2026 ·

   Muyang Li

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6. A Lens into Interpretable Transformer Mistakes via Semantic Dependency
   ICML 2025 ·

   Ruo-Jing Dong

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7. A Robust Method to Discover Causal or Anticausal Relation
   ICLR 2025 ·

   Yu Yao

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8. A Sample Efficient Conditional Independence Test in the Presence of Discretization
   ICML 2025 ·

   Boyang Sun

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9. AgentAuditor: Human-level Safety and Security Evaluation for LLM Agents
   NeurIPS 2025 ·

   Hanjun Luo

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10. Aligning What Matters: Masked Latent Adaptation for Text-to-Audio-Video Generation
    NeurIPS 2025 ·

    Jiyang Zheng

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11. Can Dependencies Induced by LLM-Agent Workflows Be Trusted?
    NeurIPS 2025 ·

    Yu Yao

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12. Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models
    ICLR 2025 ·

    Jiyang Zheng

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13. Cognitive Mirrors: Exploring the Diverse Functional Roles of Attention Heads in LLM Reasoning
    NeurIPS 2025 ·

    Xueqi Ma

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14. DEEM: Diffusion models serve as the eyes of large language models for image perception
    ICLR 2025 ·

    Run Luo

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15. Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations
    ICLR 2025 ·

    Xiu-Chuan Li

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16. Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
    NeurIPS 2025 ·

    Suqin Yuan

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17. Epistemic Uncertainty for Generated Image Detection
    NeurIPS 2025 ·

    Jun Nie

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18. Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
    ICML 2025 ·

    Puning Yang

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19. Flow: Modularized Agentic Workflow Automation
    ICLR 2025 ·

    Boye Niu

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20. From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium
    ICML 2025 ·

    Xie Yi

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21. Generative Model Inversion Through the Lens of the Manifold Hypothesis
    NeurIPS 2025 ·

    Xiong Peng

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22. Instance-dependent Early Stopping
    ICLR 2025 ·

    Suqin Yuan

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23. Jailbreaking the Non-Transferable Barrier via Test-Time Data Disguising
    CVPR 2025 ·

    Yongli Xiang

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24. LaVin-DiT: Large Vision Diffusion Transformer
    CVPR 2025 ·

    Zhaoqing Wang

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25. Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning
    IJCAI 2025 ·

    Zhiqiang Kou

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26. Learning Graph Invariance by Harnessing Spuriosity
    ICLR 2025 ·

    Tianjun Yao

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27. MFT-VITON: High-Fidelity Virtual Try-On with Minimal Input via a Mask-Free Transformer-Diffusion Model
    ICCV 2025 ·

    Zhenchen Wan

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28. MLLM-For3D: Adapting Multimodal Large Language Model for 3D Reasoning Segmentation
    NeurIPS 2025 ·

    Jiaxin Huang

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29. Noisy Test-Time Adaptation in Vision-Language Models
    ICLR 2025 ·

    Chentao Cao

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30. OpenInsGaussian: Open-Vocabulary Instance Gaussian Segmentation with Context-Aware Cross-View Fusion
    ICCV 2025 ·

    Tianyu Huang

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31. Provable Discriminative Hyperspherical Embedding for Out-of-Distribution Detection
    AAAI 2025 ·

    Zhipeng Zou

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32. Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
    NeurIPS 2025 ·

    Tianjun Yao

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33. RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Rank Correlation between Labels
    NeurIPS 2025 ·

    Zhiqiang Kou

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34. Ranked from Within: Ranking Large Multimodal Models Without Labels
    ICML 2025 ·

    Weijie Tu

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35. Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates
    ICLR 2025 ·

    Xiu-Chuan Li

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36. Revealing Multimodal Causality with Large Language Models
    NeurIPS 2025 ·

    Jin Li

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37. Surprise3D: A Dataset for Spatial Understanding and Reasoning in Complex 3D Scenes
    NeurIPS 2025 ·

    Jiaxin Huang

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38. Surrogate Prompt Learning: Towards Efficient and Diverse Prompt Learning for Vision-Language Models
    ICML 2025 ·

    Liangchen Liu

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39. Toward Robust Non-Transferable Learning: A Survey and Benchmark
    IJCAI 2025 ·

    Ziming Hong

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40. Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
    ICLR 2025 ·

    Qizhou Wang

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41. Towards Out-of-Modal Generalization without Instance-level Modal Correspondence
    ICLR 2025 ·

    Zhuo Huang

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42. Understanding and Enhancing the Transferability of Jailbreaking Attacks
    ICLR 2025 ·

    Runqi Lin

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43. When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
    ICML 2025 ·

    Ziming Hong

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44. Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions
    ICLR 2024 ·

    Xiu-Chuan Li

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45. Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization
    NeurIPS 2024 ·

    Hongling Zheng

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46. Discovery of the Hidden World with Large Language Models
    NeurIPS 2024 ·

    Chenxi Liu

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47. E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning
    AAAI 2024 ·

    Qiang Qu

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48. ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance
    CIKM 2024 ·

    Ling-Hao Chen

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49. Early Stopping Against Label Noise Without Validation Data
    ICLR 2024 ·

    Suqin Yuan

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50. Enhanced Motion-Text Alignment for Image-to-Video Transfer Learning
    CVPR 2024 ·

    Wei Zhang

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51. Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation
    ICLR 2024 ·

    Jiyang Zheng

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52. Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting
    ICLR 2024 ·

    Rong Dai

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53. Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
    ICML 2024 ·

    Chentao Cao

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54. Exploring Channel-Aware Typical Features for Out-of-Distribution Detection
    AAAI 2024 ·

    Rundong He

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55. FedImpro: Measuring and Improving Client Update in Federated Learning
    ICLR 2024 ·

    Zhenheng Tang

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56. Federated Causal Discovery from Heterogeneous Data
    ICLR 2024 ·

    Loka Li

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57. Few-Shot Adversarial Prompt Learning on Vision-Language Models
    NeurIPS 2024 ·

    Yiwei Zhou

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58. IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models
    ICLR 2024 ·

    Shaokun Zhang

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59. Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
    ICML 2024 ·

    Jiacheng Zhang

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60. Improving Non-Transferable Representation Learning by Harnessing Content and Style
    ICLR 2024 ·

    Ziming Hong

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61. In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment
    NeurIPS 2024 ·

    Dongting Hu

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62. Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
    ICML 2024 ·

    Runqi Lin

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63. Learning the Latent Causal Structure for Modeling Label Noise
    NeurIPS 2024 ·

    Yexiong Lin

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64. MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
    ICML 2024 ·

    Hongduan Tian

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65. Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning
    ICML 2024 ·

    Zhuo Huang

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66. Mind the Gap Between Prototypes and Images in Cross-domain Finetuning
    NeurIPS 2024 ·

    Hongduan Tian

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67. Mitigating Label Noise on Graphs via Topological Sample Selection
    ICML 2024 ·

    Yuhao Wu

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68. Negative Label Guided OOD Detection with Pretrained Vision-Language Models
    ICLR 2024 ·

    Xue Jiang

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69. Neural Auto-designer for Enhanced Quantum Kernels
    ICLR 2024 ·

    Cong Lei

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70. NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation
    ICLR 2024 ·

    Pengfei Zheng

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71. NoiseGPT: Label Noise Detection and Rectification through Probability Curvature
    NeurIPS 2024 ·

    Haoyu Wang

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72. On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
    ICLR 2024 ·

    Runqi Lin

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73. One-Shot Learning as Instruction Data Prospector for Large Language Models
    ACL 2024 ·

    Yunshui Li

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74. Optimal Kernel Choice for Score Function-based Causal Discovery
    ICML 2024 ·

    Wenjie Wang

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75. Out-of-Distribution Detection with Negative Prompts
    ICLR 2024 ·

    Jun Nie

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76. Pseudo-Private Data Guided Model Inversion Attacks
    NeurIPS 2024 ·

    Xiong Peng

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77. Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
    ICML 2024 ·

    Xiaobo Xia

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78. Robust Training of Federated Models with Extremely Label Deficiency
    ICLR 2024 ·

    Yonggang Zhang

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79. Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
    ICML 2024 ·

    Yusong Hu

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80. Towards Realistic Model Selection for Semi-supervised Learning
    ICML 2024 ·

    Muyang Li

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81. Training A Secure Model Against Data-Free Model Extraction
    ECCV 2024 ·

    Zhenyi Wang

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82. Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning
    ICML 2024 ·

    Yuhao Wu

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83. Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
    NeurIPS 2024 ·

    Haoang Chi

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84. What If the Input is Expanded in OOD Detection?
    NeurIPS 2024 ·

    Boxuan Zhang

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85. Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning
    CVPR 2024 ·

    Ziming Hong

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