20 citations · 39 across the 46 of their papers we have counts for
16 papers · 1 filter
AVC-Reward: Event-Centric Audio-Video Consistency Evaluation
Yuruo Wu, Kaihang Pan, Kai Shen +6
As joint audio-video generation models become more capable, they can generate audio-visual scenes exhibiting three forms of complexity: multi-event composition, multi-layer audio m…
Beyond the Remembered World: Predictive 4D Belief for Persistent Navigation in Evolving Worlds
Mingjian Gao, Zhaocheng Li, Haoyang Huang +7
Persistent spatial memory enables embodied agents to navigate familiar environments across repeated visits. However, targets may move while unobserved, including during navigation,…
RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?
Zhenxuan Fan, Bo Zhang, Yutong Lin +9
Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task compl…
Iron: Intent-Aligned and Retrospective Dual Learning Framework for Enhancing Generalist Virtual Agents
Jiahe Ying, Wendong Bu, Kaihang Pan +6
Achieving virtual agents capable of automating tasks across diverse digital environments remains a pivotal challenge in Embodied AI. While Multimodal Large Language Models (MLLMs)…
UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets
Xian Li, Rong Wei, Lujie Yang +6
Physically grounded 3D assets are increasingly important for embodied AI and robotic simulation. However, most existing 3D assets lack unified physical semantics, including articul…
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
Yundaichuan Zhan, Minghe Gao, Zhongqi Yue +7
Recent works have explored integrating Vision-Language Models (VLMs) with classical planners that rely on symbolic representations of planning problems to generate long-horizon pla…
InstructSAM: Segment Any Instance with Any Instructions
Yuqian Yuan, Wentong Li, Zhaocheng Li +6
In this paper, we introduce InstructSAM, a unified and streamlined framework designed for multi-instance segmentation under arbitrary instructions. We formulates instruction-driven…
Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration
Weile Chen, Bingchen Miao, Qifan Yu +6
Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on handcrafted execution pipelines…
VisualThink-VLA: Visual Intermediate Reasoning for Effective and Low-Latency Vision-Language-Action Policies
Mingjian Gao, Wenqiao Zhang, Yuqian Yuan +9
Recent work has begun to equip vision-language-action (VLA) policies with explicit intermediate reasoning. In embodied control, however, textual chain-of-thought is a poor fit: irr…
CrossView Suite: Harnessing Cross-view Spatial Intelligence of MLLMs with Dataset, Model and Benchmark
Wei Wang, Yuqian Yuan, Tianwei Lin +4
Spatial intelligence requires multimodal large language models (MLLMs) to move beyond single-view perception and reason consistently about objects, visibility, geometry, and intera…
BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answering
Chang Zong, Hao Ning, Siliang Tang +2
Biomedical question answering often requires decisions from retrieved literature whose relevance, quality, and support for candidate answers are uneven. Most retrieval-augmented la…
SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness
Haiyi Qiu, Kaihang Pan, Jiacheng Li +3
Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image generation. However, these m…
OmniWeaving: Towards Unified Video Generation with Free-form Composition and Reasoning
Kaihang Pan, Qi Tian, Jianwei Zhang +12
While proprietary systems such as Seedance-2.0 have achieved remarkable success in omni-capable video generation, the academic research community lags far behind: most of its model…
CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging
Jie Cao, Zhenxuan Fan, Zhuonan Wang +8
Large language models (LLMs) achieve remarkable performance on diverse downstream and domain-specific tasks via parameter-efficient fine-tuning (PEFT). However, existing PEFT metho…
Draft-Thinking: Learning Efficient Reasoning in Long Chain-of-Thought LLMs
Jie Cao, Tianwei Lin, Zhenxuan Fan +7
Long chain-of-thought~(CoT) reasoning improves the problem-solving capability of large reasoning models~(LRMs), but often incurs substantial inference cost and overthinking. Existi…
CORE: Code-based Inverse Self-Training Framework with Graph Expansion for Virtual Agents
Keyu Wang, Bingchen Miao, Wendong Bu +7
The development of Multimodal Virtual Agents has made significant progress through the integration of Multimodal Large Language Models. However, mainstream training paradigms face…