arXiv:2512.21107v1 Announce Type: new Abstract: Safety for Large Language Models (LLMs) has been an ongoing research focus since their emergence...

arXiv:2512.20929v1 Announce Type: cross Abstract: Human language processing relies on the brain’s capacity for predictive inference. We present a machine...

arXiv:2512.20634v1 Announce Type: cross Abstract: Catastrophic forgetting remains a fundamental challenge in continual learning for large language models. Recent work...

arXiv:2512.20848v1 Announce Type: new Abstract: We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano...

arXiv:2509.16189v3 Announce Type: replace-cross Abstract: When do machine learning systems fail to generalize, and what mechanisms could improve their generalization?...

arXiv:2512.20352v1 Announce Type: new Abstract: Qualitative research faces a critical reliability challenge: traditional inter-rater agreement methods require multiple human coders,...

arXiv:2512.15649v2 Announce Type: replace-cross Abstract: The computational and memory overheads associated with expanding the context window of LLMs severely limit...

arXiv:2512.19399v1 Announce Type: cross Abstract: Interpretability methods for large language models (LLMs) typically derive directions from textual supervision, which can...

arXiv:2512.19908v1 Announce Type: new Abstract: The rise of AI has fueled growing concerns about “hype” in machine learning papers, yet...