arXiv:2512.16762v3 Announce Type: replace
Abstract: Generative Pre-trained Transformer (GPT) architectures are the most popular design for language modeling. Energy-based modeling is a different paradigm that views inference as a dynamical process ope…
arXiv:2605.00058v1 Announce Type: cross
Abstract: The primary goal of Design Verification (DV) is to ensure that a proposed chip design implementation (either in code, or physical form) exactly matches its specification and is free of functional error…
arXiv:2604.26181v2 Announce Type: replace
Abstract: Multimodal deep neural networks deployed in realistic environments must contend with runtime variations: changes in modality quality, overall input complexity, and available platform resources. Curre…
arXiv:2605.00169v1 Announce Type: cross
Abstract: Network digital twins (NDTs) are transforming network management by offering precise virtual replicas of physical network systems. However, their reliance on diverse and sensitive data introduces signi…
arXiv:2507.09001v3 Announce Type: replace-cross
Abstract: Machine learning (ML) models for electronic structure typically rely on large datasets generated by computationally expensive Kohn-Sham density functional theory calculations, as it is not know…
arXiv:2512.04341v3 Announce Type: replace
Abstract: Popular offline reinforcement learning (RL) methods rely on explicit conservatism, penalizing out-of-dataset actions or restricting rollout horizons. We question the universality of this principle an…
arXiv:2605.00324v1 Announce Type: cross
Abstract: Large-scale ranking systems depend on thousands of features derived from user behavior across multiple time horizons. Typically requires model retraining — resulting in long iteration cycles (3–6 mon…
arXiv:2512.19927v2 Announce Type: replace
Abstract: Seismology faces fundamental challenges in state forecasting and reconstruction (e.g., earthquake early warning and ground motion prediction) and managing the parametric variability of source locatio…
arXiv:2604.27977v2 Announce Type: replace
Abstract: Despite recent progress in language models and agents for scientific data-driven discovery, further advancing their capabilities is held back by the absence of verifiable environments representing re…
arXiv:2512.13746v5 Announce Type: replace-cross
Abstract: Fiber reinforcement and polymer matrix respond differently to manufacturing conditions due to mismatch in coefficient of thermal expansion and matrix shrinkage during curing of thermosets. Thes…