"Dear LLaVA, Please Drive": A Depth-Aware Vision-Language Agent for Closed-Loop Robotic Control
Research paper by Sebastian Berger and collaborators, published 2026 in arXiv (Cornell University). Research area: Reinforcement Learning in Robotics.
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Research paper by Sebastian Berger and collaborators, published 2026 in arXiv (Cornell University). Research area: Reinforcement Learning in Robotics.
Research paper by Jiajun Deng and collaborators. arXiv record dated 2025-04-24. Research area: Computer vision.
Research paper by Hongzhe Huang and collaborators. arXiv record dated 2024-12-16. Research area: Artificial intelligence.
Research paper by Yadong Lu and collaborators. Published 2023-09-18. Topics: LLaVA, MiniGPT-4, parameter-efficient training methods, LoRA, QLoRA.
Research paper by Liang Chen and collaborators. Published 2024-03-11. Topics: Large Vision-Language Models, LLaVA-1.5, QwenVL-Chat, Video-LLaVA, attention computation.
Research paper by David M. Chan and collaborators. Published 2024-11-07. Topics: transformer-based models, LLaVA, Chameleon, discrete tokenized representation, image patches.
Research paper by Grzegorz Statkiewicz and collaborators. arXiv record dated 2026-02-17. Research area: Language technology.
Research paper by Lyucheng Wu and collaborators. Published 2025-07-17. Topics: Multimodal Large Language Models, MLLMs, AutoSteer, Safety Awareness Score, SAS.
Research paper by Dianyi Wang and collaborators. Published 2025-06-10. Topics: autoregressive supervision, large vision-language models (LVLMs), visual modality, image captions, autoregressive image generation.
Research paper by Zhibin Lan and collaborators. arXiv record dated 2025-08-06. Research area: Computer vision.
Research paper by Nahid Alam and collaborators. Published 2025-05-13. Topics: Vision-Language Models, multilingual image-text pretraining dataset, LLaVA pretraining dataset, multilingual image-text model.
Research paper by Yi-Fan Zhang and collaborators. Published 2024-06-12. Topics: Large Multimodal Models, high resolution, resolution upscaling, global view, adapters.
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