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arXiv:2602.13215v1 Announce Type: new Abstract: Transformers allocate uniform computation to every position, regardless of difficulty. State Space Models (SSMs) offer efficient alternatives but struggle with …
arXiv:2602.13217v1 Announce Type: new Abstract: The main issue with most evaluation schemes today is their "static" nature: the same problems are reused repeatedly, allowing for …
arXiv:2602.13218v1 Announce Type: new Abstract: Scaling verifiable training signals remains a key bottleneck for Reinforcement Learning from Verifiable Rewards (RLVR). Logical reasoning is a natural …
arXiv:2602.13224v1 Announce Type: new Abstract: The term "hallucination" in large language models conflates distinct phenomena with different geometric signatures in embedding space. We propose a …
arXiv:2602.13226v1 Announce Type: new Abstract: Detecting text generated by large language models (LLMs) is crucial but challenging. Existing detectors depend on impractical assumptions, such as …
arXiv:2602.13230v1 Announce Type: new Abstract: Despite recent advances in artificial intelligence, many systems exhibit stagnation in long-horizon adaptability despite continued performance optimization. This work argues …
arXiv:2602.13232v1 Announce Type: new Abstract: We present PlotChain, a deterministic, generator-based benchmark for evaluating multimodal large language models (MLLMs) on engineering plot reading-recovering quantitative values …
arXiv:2602.13234v1 Announce Type: new Abstract: LLM-based role-playing has rapidly improved in fidelity, yet stronger adherence to persona constraints commonly increases vulnerability to jailbreak attacks, especially …
arXiv:2602.13235v1 Announce Type: new Abstract: Visual Retrieval-Augmented Generation (VRAG) enhances Vision-Language Models (VLMs) by incorporating external visual documents to address a given query. Existing VRAG …
arXiv:2602.13237v1 Announce Type: new Abstract: Automated reasoning is critical in domains such as law and governance, where verifying claims against facts in documents requires both …
arXiv:2602.13240v1 Announce Type: new Abstract: Code Large Language Models are frequently trained on massive datasets containing restrictively licensed source code. This creates urgent data governance …
arXiv:2602.13248v1 Announce Type: new Abstract: Natural language explanations play a critical role in establishing trust and acceptance of automated vehicles (AVs), yet existing approaches lack …