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arXiv:2604.05655v1 Announce Type: new Abstract: This work characterizes large language models' chain-of-thought generation as a structured trajectory through representation space. We show that mathematical reasoning …
arXiv:2604.05091v1 Announce Type: new Abstract: We present MegaTrain, a memory-centric system that efficiently trains 100B+ parameter large language models at full precision on a single …
arXiv:2604.05624v1 Announce Type: new Abstract: Named Entity Recognition (NER) is a foundational NLP task, yet research in Yor\`ub\'a has been constrained by limited and domain-specific …
arXiv:2604.04939v1 Announce Type: new Abstract: The paper considers a new quantitative-qualitative proximity measure for the features of information objects, where data enters a common information …
arXiv:2604.05477v1 Announce Type: new Abstract: Autonomous GUI agents based on vision-language models (VLMs) often assume deterministic environment responses, generating actions without verifying whether previous operations …
arXiv:2604.05514v1 Announce Type: new Abstract: The paradigm of programmable diagram generation is evolving rapidly, playing a crucial role in structured visualization. However, most existing studies …
arXiv:2604.05461v1 Announce Type: new Abstract: Information cocoons on social media limit users' exposure to posts with diverse viewpoints. Modern platforms use stance detection as an …
arXiv:2604.05552v1 Announce Type: new Abstract: Large Language Models demonstrate outstanding performance in many language tasks but still face fundamental challenges in managing the non-linear flow …
arXiv:2604.05371v1 Announce Type: new Abstract: The deployment of lightweight segmentation models on drones for autonomous power line inspection presents a critical challenge: maintaining reliable performance …
arXiv:2604.05424v1 Announce Type: new Abstract: PRISM-MCTS: Learning from Reasoning Trajectories with Metacognitive Reflection Siyuan Cheng, Bozhong Tian, Yanchao Hao, Zheng Wei Published: 06 Apr 2026, …
arXiv:2604.05243v1 Announce Type: new Abstract: Background: Children do not simply learn that balls are round and blocks are square. They learn that shape is the …
arXiv:2604.05179v1 Announce Type: new Abstract: Large language models (LLMs) remain susceptible to jailbreak and direct prompt-injection attacks, yet the strongest defensive filters frequently over-refuse benign …