activity
20232026
most citedAttribute-driven Disentangled Representation Learning for Multimodal Recommendation

17 citations · 36 across the 39 of their papers we have counts for

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13 papers · 1 filter

cs.RO2026

World-Calibrated Proposal-to-Action Flow for Vision-Language-Action Models

Jie He, Wei Li, Junwen Tong +3

Flow-based Vision-Language-Action (VLA) policies generate action chunks by transporting samples from a task-agnostic isotropic Gaussian source. As this source is conditioned on nei…

cs.CV2026

NavHarness: Adaptive Goals for Agentic Vision-Language Navigation

Haoxiang Shi, Zaijing Li, Muhe Ding +3

Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents offer a promising basis for…

cs.CV2026

Inline Memory Meets Reusable Skills: Memory-centric Framework for Vision-Language-Action Model

Zaijing Li, Rui Shao, Bing Hu +3

Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, yet adapting them to new tasks and domains remains inefficient: existing met…

cs.RO2026

UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling

Wei Li, Rui Shao, Jie He +3

Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a fundamental transition realizabil…

cs.CV2026

Learning to Use Imagination: Progress-Conditioned Future Utilization for World Action Models

Yijie Zhu, Zitong Yu, Wei Li +4

World Action Models (WAMs) extend Vision-Language-Action (VLA) models by incorporating future visual dynamics into action generation. However, existing WAMs often utilize imagined…

cs.CV2026

LookAgain: Closed-Loop GUI Grounding with Visually Grounded Reflection

Renshan Zhang, Haoyang Meng, Yixiao He +3

Recent graphical user interface (GUI) grounders have significantly advanced single-shot accuracy on standard benchmarks, yet their performance degrades sharply on small targets, de…

cs.CV2026

ViMax: Agentic Video Generation

Lingxuan Huang, Sizhe He, Hengji Zhou +3

Long-form video generation requires systematic narrative planning and visual consistency that current short-clip methods cannot provide. Existing methods generate isolated sequence…

cs.CV2026

Technical Report of RoboSpatial Challenge at CVPR 2026: Selective Reasoning Activation and Reference-Frame Disambiguation for Embodied Spatial Reasoning

Yuxiang Xie, Qi Lv, Jianming Xing +4

Vision-language models achieve strong general perception but often struggle with the spatial reasoning required for embodied tasks. We present RoboSpatialBrain, our submission to t…

cs.CV2026

Efficient Visual Pointing for Embodied AI:Agent-Driven Data Synthesis, Cross-Block Attention, and Iterative Correction

Zijian Hong, Qi Lv, Yuxiang Xie +4

Visual pointing maps a language instruction to pixel co ordinates, a core skill for embodied AI. We describe our PointArena 2026 solution, which achieves 77.2% overall accuracy and…

cs.RO2026

Learning New Tasks via Reusable Skills: Skill-Compositional Experts for Embodied Continual Learning

Shuaike Zhang, Shaokun Wang, Haoyu Tang +2

Embodied Continual Learning (ECL) aims to enable robots to continually acquire new manipulation tasks while retaining previously learned behaviors under closed-loop control. In ECL…

cs.AI2026

Towards Next-Generation Healthcare: A Survey of Medical Embodied AI for Perception, Decision-Making, and Action

Cheng Zhang, Qing Cai, Xingzheng Wu +6

Foundation models have demonstrated impressive performance in enhancing healthcare efficiency across a wide range of medical applications. Nevertheless, their limited ability to pe…

cs.RO2026

ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation

Wei Li, Jizhihui Liu, Li Yixing +3

Current Vision-Language-Action (VLA) models primarily focus on mapping 2D observations to actions, but exhibit notable limitations in spatiotemporal perception and reasoning: 1) sp…

cs.RO2026

Global Prior Meets Local Consistency: Dual-Memory Augmented Vision-Language-Action Model for Efficient Robotic Manipulation

Zaijing Li, Bing Hu, Rui Shao +5

Hierarchical Vision-Language-Action (VLA) models have rapidly become a dominant paradigm for robotic manipulation. It typically comprising a Vision-Language backbone for perception…