arXiv:2609.09425v2 Announce Type: replace-cross Abstract: Educational data filters have become a practical way to improve language-model pre-training, but most filters…
arXiv:2609.11390v1 Announce Type: cross Abstract: State-of-the-art retrieval-augmented generation (RAG) methods exploit document structures to acquire sufficient evidence, but often incur…
arXiv:2609.11391v1 Announce Type: cross Abstract: Environmental controversies in global supply chains pose significant risks for global buyers. This study examines…
arXiv:2609.10372v2 Announce Type: replace-cross Abstract: We present the PACE, a framework for retrieval-augmented dialogue serving that formalizes Perceived Time-to-First-Response (PTFR)…
arXiv:2609.10584v1 Announce Type: new Abstract: Bounded-suboptimal search seeks a solution within a factor $w$ of optimal while reducing search effort.…
arXiv:2609.08038v2 Announce Type: replace-cross Abstract: Smart healthcare monitoring systems require precise action recognition to ensure well-being and timely intervention in…
arXiv:2609.10016v1 Announce Type: cross Abstract: We introduce MetroLLM-Bench, a 955-case benchmark for testing language models as the policy layer of…
arXiv:2609.10018v1 Announce Type: cross Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time.…
arXiv:2609.08977v2 Announce Type: replace-cross Abstract: In this work, we present Gander, an end-to-end model that unifies omni perception, realtime interaction,…
arXiv:2609.09203v1 Announce Type: new Abstract: Existing benchmarks for autonomous AI scientists evaluate only final outputs—generated code, hypotheses, or papers—yet discard…
