Jieyu Zhang

Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding CVPR 2026 SAGE: Training Smart Any-Horizon Agents for Long Video Reasoning with Reinforcement Learning CVPR 2026 Synthetic Object Compositions for Scalable and Accurate Learning in Detection, Segmentation, and Grounding CVPR 2026 Towards Acyclic Preference Evaluation of Language Models via Multiple Evaluators AAAI 2026 TrajTok: Learning Trajectory Tokens Enhances Video Understanding CVPR 2026 Explaining Length Bias in LLM-Based Preference Evaluations EMNLP 2025 LATTE: Learning to Think with Vision Specialists EMNLP 2025 One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory ICCV 2025 Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems ICML 2025 Biomedical Visual Instruction Tuning with Clinician Preference Alignment NeurIPS 2024 DataComp-LM: In search of the next generation of training sets for language models NeurIPS 2024 EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records EMNLP 2024 Iterated Learning Improves Compositionality in Large Vision-Language Models CVPR 2024 m&m’s: A Benchmark to Evaluate Tool-Use for multi-step multi-modal Tasks ECCV 2024 Offline Training of Language Model Agents with Functions as Learnable Weights ICML 2024 SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ICML 2024 Task Me Anything NeurIPS 2024 Characterizing the Impacts of Semi-supervised Learning for Weak Supervision NeurIPS 2023 Cold-Start Data Selection for Better Few-shot Language Model Fine-tuning: A Prompt-based Uncertainty Propagation Approach ACL 2023 DataComp: In search of the next generation of multimodal datasets NeurIPS 2023 Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning CVPR 2023 Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias NeurIPS 2023 Learning Hyper Label Model for Programmatic Weak Supervision ICLR 2023 Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision AISTATS 2023 On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training NeurIPS 2023 Subclass-balancing Contrastive Learning for Long-tailed Recognition ICCV 2023 SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality NeurIPS 2023 Uncovering Neural Scaling Laws in Molecular Representation Learning NeurIPS 2023 When to Learn What: Model-Adaptive Data Augmentation Curriculum ICCV 2023 AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models NAACL 2022 Adaptive Ranking-based Sample Selection for Weakly Supervised Class-imbalanced Text Classification EMNLP 2022 Creating Training Sets via Weak Indirect Supervision ICLR 2022 Understanding Programmatic Weak Supervision via Source-aware Influence Function NeurIPS 2022 Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD NeurIPS 2021 TAXOGAN: Hierarchical Network Representation Learning via Taxonomy Guided Generative Adversarial Networks (Extended Abstract) IJCAI 2021 Taxonomy Completion via Triplet Matching Network AAAI 2021