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20242026
most citedLISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model

4 citations · 5 across the 19 of their papers we have counts for

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10 papers · 1 filter

cs.RO2026

CarryOn: A Dual-Loop Harness for Personalized and Reliable Robot Assistance

Zixuan Wang, Yuqi Liu, Yuxin Chen +7

While generalist vision-language-action (VLA) models have enabled diverse open-world manipulation, real-world robotic assistance requires two critical capabilities they currently l…

cs.RO2026

Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models

Senqiao Yang, Chengyao Wang, Yuxin Chen +13

Scaling robot data is crucial for building generalist Vision-Language-Action (VLA) models, yet robot trajectories are harder to scale than web-scale image-text data because embodie…

cs.RO2026

XPolicyLab: A Unified Standard and Open Ecosystem for Robot Policy Evaluation and Deployment

XPolicyLab Community, Tianxing Chen, Yue Chen +67

Robot policy evaluation and deployment remain fragmented by model-specific software dependencies, data representations, and runtime interfaces, so that connecting N policies to M e…

cs.CV2026

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model

Senqiao Yang, Kaichen Zhang, Zhaoyang Jia +20

Standard vision-language models (VLMs) suffer from Moravec's paradox: they excel at complex offline visual reasoning but struggle with simple streaming perception tasks and process…

cs.CV2026

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing

Xinjie Zhang, Peng Zhang, Shicheng Zheng +21

Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to…

cs.CV2026

Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention

Wenhu Zhang, Yiming Wu, Huanyu Wang +6

Diffusion Language Models (DLMs) enable globally coherent, bidirectional, and controllable text generation, offering advantages over traditional autoregressive LLMs, while scaling…

cs.RO2026

StarVLA-: Reducing Complexity in Vision-Language-Action Systems

Jinhui Ye, Ning Gao, Senqiao Yang +7

Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landscape remains highly fragmented…

cs.AI2026

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47

As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…

cs.CV2026

Consistency Beyond Contrast: Enhancing Open-Vocabulary Object Detection Robustness via Contextual Consistency Learning

Bozhao Li, Shaocong Wu, Tong Shao +4

Recent advances in open-vocabulary object detection focus primarily on two aspects: scaling up datasets and leveraging contrastive learning to align language and vision modalities.…

cs.CV2026

Multimodal Dataset Distillation via Phased Teacher Models

Shengbin Guo, Hang Zhao, Senqiao Yang +5

Multimodal dataset distillation aims to construct compact synthetic datasets that enable efficient compression and knowledge transfer from large-scale image-text data. However, exi…