4 citations · 10 across the 10 of their papers we have counts for
10 papers
Scaling World Model for Hierarchical Manipulation Policies
Qian Long, Yueze Wang, Jiaxi Song +13
Vision-Language-Action (VLA) models are promising for generalist robot manipulation but remain brittle in out-of-distribution (OOD) settings, especially with limited real-robot dat…
Knowledge Reasoning Language Model: Unifying Knowledge and Language for Inductive Knowledge Graph Reasoning
Xingrui Zhuo, Jiapu Wang, Gongqing Wu +4
Inductive Knowledge Graph Reasoning (KGR) aims to discover facts in open-domain KGs containing unknown entities and relations, which poses a challenge for KGR models in comprehendi…
Towards provable probabilistic safety for scalable embodied AI systems
Linxuan He, Lingxiang Fan, Qing-Shan Jia +13
Embodied AI systems, comprising AI models and physical plants, are increasingly prevalent across various applications. Due to the rarity of system failures, ensuring their safety i…
Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks
Jiazhao Zhang, Kunyu Wang, Shaoan Wang +6
A practical navigation agent must be capable of handling a wide range of interaction demands, such as following instructions, searching objects, answering questions, tracking peopl…
Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection
Enshen Zhou, Qi Su, Cheng Chi +5
Automatic detection and prevention of open-set failures are crucial in closed-loop robotic systems. Recent studies often struggle to simultaneously identify unexpected failures rea…
Emu3: Next-Token Prediction is All You Need
Xinlong Wang, Xiaosong Zhang, Zhengxiong Luo +22
While next-token prediction is considered a promising path towards artificial general intelligence, it has struggled to excel in multimodal tasks, which are still dominated by diff…
52B to 1T: Lessons Learned via Tele-FLM Series
Xiang Li, Yiqun Yao, Xin Jiang +17
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, the academic…
Tele-FLM Technical Report
Xiang Li, Yiqun Yao, Xin Jiang +17
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable p…
Not All Layers of LLMs Are Necessary During Inference
Siqi Fan, Xin Jiang, Xiang Li +6
Due to the large number of parameters, the inference phase of Large Language Models (LLMs) is resource-intensive. However, not all requests posed to LLMs are equally difficult to h…
Improving Vision-and-Language Reasoning via Spatial Relations Modeling
Cheng Yang, Rui Xu, Ye Guo +5
Visual commonsense reasoning (VCR) is a challenging multi-modal task, which requires high-level cognition and commonsense reasoning ability about the real world. In recent years, l…