Quality follows upgrading
Academic
arXiv:2604.06515v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) allows scaling of language and vision models efficiently by activating only a small subset of experts per …
arXiv:2604.06684v1 Announce Type: new Abstract: Clinical Reasoning on Electronic Health Records (EHRs) is a fundamental yet challenging task in modern healthcare. While in-context learning (ICL) …
arXiv:2604.06192v1 Announce Type: new Abstract: Recent work uses entropy-based signals at multiple representation levels to study reasoning in large language models, but the field remains …
arXiv:2604.06393v1 Announce Type: new Abstract: Hallucination in large language models (LLMs) continues to be a significant issue, particularly in tasks like question answering, where models …
arXiv:2604.06424v1 Announce Type: new Abstract: This paper presents a transformer-based approach to solving the SympTEMIST named entity recognition (NER) and entity linking (EL) tasks. For …
arXiv:2604.06732v1 Announce Type: new Abstract: Recent developments in hardware, such as photonic integrated circuits and optical devices, are driving demand for research on constructing machine …
arXiv:2604.06631v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training while preserving data privacy, but its practical deployment is hampered by system and …
arXiv:2604.06484v1 Announce Type: new Abstract: Cultural values are expressed not only through language but also through visual scenes and everyday social practices. Yet existing evaluations …
arXiv:2604.06473v1 Announce Type: new Abstract: Multivariate forecasting with Transformers faces a core scalability challenge: modeling cross-channel dependencies via attention compounds attention's quadratic sequence complexity with …
arXiv:2604.06227v1 Announce Type: new Abstract: Accurate short-term forecasting of agricultural commodity prices is critical for food security planning and smallholder income stabilisation in developing economies, …
arXiv:2604.06333v1 Announce Type: new Abstract: Drifting models generate high-quality samples in a single forward pass by transporting generated samples toward the data distribution using a …
arXiv:2604.06552v1 Announce Type: new Abstract: Misinformation is on the rise, and the strong writing capabilities of LLMs lower the barrier for malicious actors to produce …