- Self-Correcting VLA: Online Action Refinement via Sparse World Imagination
Chenyv Liu, Wentao Tan, Lei Zhu, Fengling Li, Jingjing Li · Feb 25, 2026 · Citations: 0
Simulation Env Long Horizon
Reinforcement learning enhances physical grounding through exploration yet typically relies on external reward signals that remain isolated from the agent's internal states.
- LiLo-VLA: Compositional Long-Horizon Manipulation via Linked Object-Centric Policies
Yue Yang, Shuo Cheng, Yu Fang, Homanga Bharadhwaj, Mingyu Ding · Feb 25, 2026 · Citations: 0
Simulation Env Long Horizon
We introduce a 21-task simulation benchmark consisting of two challenging suites: LIBERO-Long++ and Ultra-Long.
- A Very Big Video Reasoning Suite
Maijunxian Wang, Ruisi Wang, Juyi Lin, Ran Ji, Thaddäus Wiedemer · Feb 23, 2026 · Citations: 0
Simulation Env
We further present VBVR-Bench, a verifiable evaluation framework that moves beyond model-based judging by incorporating rule-based, human-aligned scorers, enabling reproducible and interpretable diagnosis of video reasoning capabilities.
- MALLVI: A Multi-Agent Framework for Integrated Generalized Robotics Manipulation
Iman Ahmadi, Mehrshad Taji, Arad Mahdinezhad Kashani, AmirHossein Jadidi, Saina Kashani · Feb 18, 2026 · Citations: 0
Simulation Env Multi Agent
MALLVI presents a Multi Agent Large Language and Vision framework that enables closed-loop feedback driven robotic manipulation.
- UI-Venus-1.5 Technical Report
Venus Team, Changlong Gao, Zhangxuan Gu, Yulin Liu, Xinyu Qiu · Feb 9, 2026 · Citations: 0
Simulation Env Long Horizon
GUI agents have emerged as a powerful paradigm for automating interactions in digital environments, yet achieving both broad generality and consistently strong task performance remains challenging.
- Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz · Jan 14, 2026 · Citations: 0
Pairwise Preference Simulation Env Long Horizon
Fast-ThinkAct learns to reason efficiently with latent CoTs by distilling from a teacher, driven by a preference-guided objective to align manipulation trajectories that transfers both linguistic and visual planning capabilities for embodie
- Aerial Vision-Language Navigation with a Unified Framework for Spatial, Temporal and Embodied Reasoning
Huilin Xu, Zhuoyang Liu, Yixiang Luomei, Feng Xu · Dec 9, 2025 · Citations: 0
Simulation Env Long Horizon
Extensive experiments on the AerialVLN and OpenFly benchmark validate the effectiveness of our method.
- BEAT: Visual Backdoor Attacks on VLM-based Embodied Agents via Contrastive Trigger Learning
Qiusi Zhan, Hyeonjeong Ha, Rui Yang, Sirui Xu, Hanyang Chen · Oct 31, 2025 · Citations: 0
Pairwise Preference Automatic MetricsSimulation Env Long Horizon
Recent advances in Vision-Language Models (VLMs) have propelled embodied agents by enabling direct perception, reasoning, and planning task-oriented actions from visual inputs.
- World Simulation with Video Foundation Models for Physical AI
NVIDIA, :, Arslan Ali, Junjie Bai, Maciej Bala · Oct 28, 2025 · Citations: 0
Simulation Env Long Horizon
These capabilities enable more reliable synthetic data generation, policy evaluation, and closed-loop simulation for robotics and autonomous systems.
- HoloLLM: Multisensory Foundation Model for Language-Grounded Human Sensing and Reasoning
Chuhao Zhou, Jianfei Yang · May 23, 2025 · Citations: 0
Automatic MetricsSimulation Env
Embodied agents operating in smart homes must understand human behavior through diverse sensory inputs and communicate via natural language.
- RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics
Chan Hee Song, Valts Blukis, Jonathan Tremblay, Stephen Tyree, Yu Su · Nov 25, 2024 · Citations: 0
Simulation Env
Spatial understanding is a crucial capability that enables robots to perceive their surroundings, reason about their environment, and interact with it meaningfully.
- Just KIDDIN: Knowledge Infusion and Distillation for Detection of INdecent Memes
Rahul Garg, Trilok Padhi, Hemang Jain, Ugur Kursuncu, Ponnurangam Kumaraguru · Nov 19, 2024 · Citations: 0
Automatic MetricsSimulation Env
Experimental results from our study on two hate speech benchmark datasets demonstrate superior performance over the state-of-the-art baselines across AU-ROC, F1, and Recall with improvements of 1.1%, 7%, and 35%, respectively.
