2 citations · 3 across the 9 of their papers we have counts for
10 papers
RoMeRL: Balancing Feedback Coverage and the Memory-Reward Trap in Self-Evolving Agent Memory via Reduced-Order Utility States
Yi Yang, Zhennan Chen, Yihong Zhuang +5
Learning-based memory systems for self-evolving LLM agents face two tightly coupled challenges. First, trajectory-indexed utilities grow with the interaction history, thereby dispe…
Kimi K3: Open Frontier Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +398
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…
ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
Wenli Xiao, Jia Xie, Tonghe Zhang +14
Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bottleneck in the pursuit of gener…
TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation
Huaihang Zheng, Yi Yang, Kai Ma +8
Vision-Language-Action (VLA) models have become a powerful framework for robotic manipulation, and recent studies have introduced tactile or force feedback into VLAs to address con…
Partially Observable Adversarial Patch Attacks on Vision-Language-Action Models in Robotics
Xiaofei Wang, Mingliang Han, Tianyu Hao +3
Vision-language-action (VLA) models are gaining attention in robotics, yet their robustness to adversarial attacks remains largely unexplored. Existing work shows that adversarial…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +333
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations
Tingyu Yuan, Biaoliang Guan, Wen Ye +8
In embodied intelligence, the embodiment gap between robotic and human hands brings significant challenges for learning from human demonstrations. Although some studies have attemp…
Mantis: A Versatile Vision-Language-Action Model with Disentangled Visual Foresight
Yi Yang, Xueqi Li, Yiyang Chen +7
Recent advances in Vision-Language-Action (VLA) models demonstrate that visual signals can effectively complement sparse action supervisions. However, letting VLA directly predict…
LoHoVLA: A Unified Vision-Language-Action Model for Long-Horizon Embodied Tasks
Yi Yang, Jiaxuan Sun, Siqi Kou +2
Real-world embodied agents face long-horizon tasks, characterized by high-level goals demanding multi-step solutions beyond single actions. Successfully navigating these requires b…
TacticAI: an AI assistant for football tactics
Zhe Wang, Petar Veličković, Daniel Hennes +20
Identifying key patterns of tactics implemented by rival teams, and developing effective responses, lies at the heart of modern football. However, doing so algorithmically remains…