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Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering
Large language models (LLMs) have demonstrated strong capabilities in question answering, yet they still frequently suff
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686 篇DySCo: Dynamic Sharding for Collaborative Edge-Cloud LLM Inference with Depth-Synchronized Batching
Pervasive intelligent applications are increasingly deployed on mobile and Internet of Things (IoT) edge devices. Conseq
VisionWeave: Weaving Elastic Visual Representations as a Native Capability of MLLMs
Multimodal large language models have become the dominant paradigm for visual understanding, but incur substantial costs
EmbodiedSmith: Scaling Embodied Data through Recursive Self-Improvement Flywheel in Simulation
Scaling robotic foundation models requires diverse training data and reliable evaluation environments. Simulation offers
Persistent Memory in Multi-Agent LLM Inference: What It Costs, What It Buys, and When You Can Tell
Decomposing long-context inference across cooperating agents bounds the active KV cache per call rather than total evide
Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs
Clinical questions often depend on linking a patient's multimodal evidence to external biomedical knowledge, yet existin
Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design
Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, s
Adaptive Mean Flow for Responsive Closed-Loop Robot Control
Diffusion- and flow-based robot policies have recently become widespread in robotic Imitation Learning (IL) due to their