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arXiv:2603.09998v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) have exceptional performance in machine translation, only a limited systematic assessment of translation quality has …
arXiv:2603.09978v1 Announce Type: cross Abstract: Large language models have recently surpassed specialized systems on code generation, yet their effectiveness on other code-analysis tasks remains less …
arXiv:2603.09986v1 Announce Type: cross Abstract: Hallucinations, the tendency for large language models to provide responses with factually incorrect and unsupported claims, is a serious problem …
arXiv:2603.09995v1 Announce Type: cross Abstract: Behavioral interview evaluation using large language models presents unique challenges that require structured assessment, realistic interviewer behavior simulation, and pedagogical …
arXiv:2603.09983v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable scalable performance but face severe memory constraints on edge devices. Existing offloading strategies struggle with I/O …
arXiv:2603.09994v1 Announce Type: cross Abstract: Compositionality is considered central to language abilities. As performant language systems, how do large language models (LLMs) do on compositional …
arXiv:2603.10588v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has achieved remarkable success in logical reasoning tasks, yet whether large language model (LLM) …
arXiv:2603.10564v1 Announce Type: new Abstract: The integration of Generative AI models into AI-native network systems offers a transformative path toward achieving autonomous and adaptive control. …
arXiv:2603.10677v1 Announce Type: new Abstract: Clinical diagnosis is a complex cognitive process, grounded in dynamic cue acquisition and continuous expertise accumulation. Yet most current artificial …
arXiv:2603.09982v1 Announce Type: cross Abstract: Encoder-only transformer models remain widely used for discriminative NLP tasks, yet recent architectural advances have largely focused on English. In …
arXiv:2603.10661v1 Announce Type: new Abstract: We propose FAME (Formal Abstract Minimal Explanations), a new class of abductive explanations grounded in abstract interpretation. FAME is the …
arXiv:2603.10018v1 Announce Type: cross Abstract: As large language models (LLMs) become pervasive as assistants and thought partners, it is important to characterize their persuasive influence …