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Large Language Models as Falsifiers for Cyber-Physical Systems
Falsification searches for counterexamples to formal specifications in cyber-physical systems (CPS). With specifications
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243 篇MoWAM: Explicit Future Motion Prediction for Efficient World Action Models
World Action Models (WAMs) improve robot policy learning by incorporating future dynamics, yet explicitly generating fut
Semantic SLAM in Precision Agriculture using Bayesian Inference
This paper presents a real-time semantic world modeling framework specialized for precision agriculture using autonomous
CoRef-GS: Cooperative Referring Gaussian Splatting for Multi-Agent Scene Understanding
Referring scene understanding for embodied robots requires grounding object- and relation-centric language queries from
Language-model groups overstate consensus when replaying human deliberation on a reasoning task
Full-consensus rates are often treated as indicators of collective cognition, yet depend on how participation and final
Parallelism, critical windows, and separations among diffusion language models
A popular selling point of diffusion large language models (dLLMs) is their capacity for parallelism: the ability to gen
RoboFind: Multi-Agent Personalized Object Search for People Who Are Blind or Have Low Vision
Blind and low-vision users often need to locate a specific personal object rather than an arbitrary instance of the same
九识建成首个L4万卡集群，无人驾驶进入多模态大模型新范式
一家做无人车的公司，为什么需要一万多张GPU？ 9月10日，九识CEO孔旗在广州宣布战略升级为“城市级物理AI”。一周后的9月17日，CTO庄立首次披露支撑这次升级的底层能力：九识已建成业内首个L4级万卡集群，算力集群总规模近1.5万卡。九
KoNeoBench: A Curated Evaluation Dataset for LLM Understanding of Korean Neologisms
Large language models (LLMs) are typically evaluated on static benchmarks, even though natural language constantly evolv
DualSQL: Text-to-SQL with Multi-Agent Reinforcement Learning
State-of-the-art Text-to-SQL systems are typically multi-agent pipelines centered around two fundamental tasks: schema l