For An Exciting Tomorrow
arXiv:2510.17884v1 Announce Type: cross Abstract: The remarkable capabilities of Large Language Models (LLMs) in natural language understanding and generation have…
arXiv:2510.18406v1 Announce Type: cross Abstract: Weakly supervised learning often operates with coarse aggregate signals rather than instance labels. We study…
arXiv:2510.16042v1 Announce Type: cross Abstract: This paper investigates the concept of Labour as an expression of `timenergy’ – a fusion…
arXiv:2508.12081v2 Announce Type: replace-cross Abstract: This paper introduces VimoRAG, a novel video-based retrieval-augmented motion generation framework for motion large language…
arXiv:2510.04774v2 Announce Type: replace-cross Abstract: Our recently introduced self-organizing nervous system (SoNS) provides robot swarms with 1) ease of behavior…
arXiv:2510.17157v1 Announce Type: cross Abstract: Generating editable, parametric CAD models from a single image holds great potential to lower the…
arXiv:2510.17022v1 Announce Type: cross Abstract: We explore if RL can be useful for symbolic mathematics. Previous work showed contrastive learning…
arXiv:2510.15557v1 Announce Type: cross Abstract: This paper presents ClapperText, a benchmark dataset for handwritten and printed text recognition in visually…
arXiv:2510.15015v1 Announce Type: cross Abstract: Text-to-Image (T2I) models have advanced rapidly, yet they remain vulnerable to semantic leakage, the unintended…
arXiv:2504.19136v3 Announce Type: replace-cross Abstract: The fusion of Synthetic Aperture Radar (SAR) and RGB imagery for land cover classification remains…