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20222026
most citedA Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language

42 citations · 51 across the 19 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation

Dazhao Du, Shiyan Du, Jian Liu +8

Understanding camera motion is fundamental to video perception, with applications in spatial intelligence and controllable video generation. Multimodal large language models (MLLMs…

cs.AI2026

WorldCycle: Self-Verifiable Reinforcement Learning for Long-Horizon Video World Models

Bohai Gu, Yueyang Yuan, Taiyi Wu +9

Interactive video world models are essential for long-horizon planning and exploration, yet they suffer from compounding errors. Post-training methods such as reinforcement learnin…

cs.CV2026

Train the Agent, Not the Expert: Learning to Harness Heterogeneous Experts for Multi-Turn Visual Reasoning

Yaowu Fan, Tao Han, Dazhao Du +2

Recent progress in computer vision has produced a wide range of powerful specialized models for detection, segmentation, counting, and other visual tasks. However, these models are…

cs.CV2026

WorldCraft: From Camera Navigation to Object Manipulation in Interactive Video World Models

Bohai Gu, Taiyi Wu, Yueyang Yuan +9

Recent video world models enable interactive camera navigation but provide limited control over individual objects. We study persistent object-state control in autoregressive video…

cs.CV2026

Learning Spatiotemporal Sensitivity in Video LLMs via Counterfactual Reinforcement Learning

Dazhao Du, Jian Liu, Jialong Qin +7

Video large language models (Video LLMs) can achieve strong video-QA accuracy without reliably tracking spatiotemporal dynamics. A model may answer a motion question from static cu…

cs.CV2026

MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues

Dazhao Du, Liao Duan, Jian Liu +5

Video temporal grounding (VTG), which localizes the start and end times of a queried event in an untrimmed video, is a key test of whether multimodal large language models (MLLMs)…

cs.GR2026

From Visual Synthesis to Interactive Worlds: Toward Production-Ready 3D Asset Generation

Jiafeng Wu, Zhuofan Lou, Jian Liu +3

Three-dimensional content generation has progressed from producing isolated, visually plausible shapes to constructing structured assets that can be deployed in real-time interacti…

cs.RO2026

3D Generation for Embodied AI and Robotic Simulation: A Survey

Tianwei Ye, Yifan Mao, Minwen Liao +6

Embodied AI and robotic systems increasingly depend on scalable, diverse, and physically grounded 3D content for simulation-based training and real-world deployment. While 3D gener…

cs.AI2026

GUI Agents with Reinforcement Learning: Toward Digital Inhabitants

Junan Hu, Jian Liu, Jingxiang Lai +6

Graphical User Interface (GUI) agents have emerged as a promising paradigm for intelligent systems that perceive and interact with graphical interfaces visually. Yet supervised fin…

cs.HC2026

GrandGuard: Taxonomy, Benchmark, and Safeguards for Elderly-Chatbot Interaction Safety

Changxuan Fan, Xi Yang, Yueyuan Zheng +9

As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities from social isolation, limited…

cs.CV2026

Place-it-R1: Unlocking Environment-aware Reasoning Potential of MLLM for Video Object Insertion

Bohai Gu, Taiyi Wu, Dazhao Du +5

Video object insertion is fundamental to video editing, yet existing diffusion methods often produce visually plausible but physically inconsistent results. We present Place-it-R1,…

cs.CV2026

Mesh-Pro: Asynchronous Advantage-guided Ranking Preference Optimization for Artist-style Quadrilateral Mesh Generation

Zhen Zhou, Jian Liu, Biwen Lei +10

Reinforcement learning (RL) has demonstrated remarkable success in text and image generation, yet its potential in 3D generation remains largely unexplored. Existing attempts typic…