Quality follows upgrading
Tag: cs.AI
arXiv:2604.06603v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong knowledge reserves and task-solving capabilities, but still face the challenge of severe hallucination, …
arXiv:2604.06491v1 Announce Type: new Abstract: We introduce Discrete flow Matching policy Optimization (DoMinO), a unified framework for Reinforcement Learning (RL) fine-tuning Discrete Flow Matching (DFM) …
arXiv:2604.06483v1 Announce Type: new Abstract: Large language models that require multiple GPU cards to host are usually the most capable models. It is necessary to …
arXiv:2604.06391v1 Announce Type: new Abstract: Graphs are a central representation in biomedical research, capturing molecular interaction networks, gene regulatory circuits, cell--cell communication maps, and knowledge …
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:2604.06377v1 Announce Type: new Abstract: We investigate whether post-trained capabilities can be transferred across models without retraining, with a focus on transfer across different model …
arXiv:2604.06260v1 Announce Type: new Abstract: Test-time scaling investigates whether a fixed diffusion language model (DLM) can generate better outputs when given more inference compute, without …
arXiv:2604.06448v1 Announce Type: new Abstract: Prime Video regularly conducts load tests to simulate the viewer traffic spikes seen during live events such as Thursday Night …
arXiv:2604.06613v1 Announce Type: new Abstract: Modern reasoning models continue generating long after the answer is already determined. Across five model configurations, two families, and three …
arXiv:2604.06346v1 Announce Type: new Abstract: Large language models have shown strong potential for Arabic medical text generation; however, traditional fine-tuning objectives treat all medical cases …
arXiv:2604.06204v1 Announce Type: new Abstract: Personalization is essential for Large Language Model (LLM)-based agents to adapt to users' preferences and improve response quality and task …
arXiv:2604.06201v1 Announce Type: new Abstract: While most reading comprehension benchmarks for LLMs focus on factual information that can be answered by localizing specific textual evidence, …