Quality follows upgrading
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전체 전문분석자료
arXiv:2602.12402v1 Announce Type: cross Abstract: Analog and mixed-signal (AMS) integrated circuits (ICs) lie at the core of modern computing and communications systems. However, despite the …
arXiv:2602.12413v1 Announce Type: cross Abstract: If LLM training data is polluted with benchmark test data, then benchmark performance gives biased estimates of out-of-distribution (OOD) generalization. …
arXiv:2602.12422v1 Announce Type: cross Abstract: Cache replacement remains a challenging problem in CPU microarchitecture, often addressed using hand-crafted heuristics, limiting cache performance. Cache data analysis …
arXiv:2602.12424v1 Announce Type: cross Abstract: Benchmarks establish a standardized evaluation framework to systematically assess the performance of large language models (LLMs), facilitating objective comparisons and …
arXiv:2602.12430v2 Announce Type: cross Abstract: The transition from monolithic language models to modular, skill-equipped agents marks a defining shift in how large language models (LLMs) …
arXiv:2602.12444v1 Announce Type: cross Abstract: Reinforcement learning (RL) is a powerful framework for optimal decision-making and control but often lacks provable guarantees for safety-critical applications. …
arXiv:2602.12463v1 Announce Type: cross Abstract: We argue that it is neither necessary nor sufficient for a mathematical proof to have epistemic value that it be …
arXiv:2602.12470v1 Announce Type: cross Abstract: RNA design, the task of finding a sequence that folds into a target secondary structure, has broad biological and biomedical …
arXiv:2602.12302v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) combine the natural language understanding and generation capabilities of LLMs with perception skills in modalities …
arXiv:2602.12414v1 Announce Type: new Abstract: Since FineWeb-Edu, data curation for LLM pretraining has predominantly relied on single scalar quality scores produced by small classifiers. A …
arXiv:2602.12445v1 Announce Type: new Abstract: Language models (LMs) are known to be prone to response biases, which present as option preference biases in fixed-response questions. …
arXiv:2602.12575v1 Announce Type: new Abstract: Psychological scale refinement traditionally relies on response-based methods such as factor analysis, item response theory, and network psychometrics to optimize …