arXiv:2607. 20265v1 Announce Type: cross Abstract: Large-scale pretrained language models such as T5 and BERT have demonstrated strong capabilities for generating structured knowledge.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2606. 24841v1 Announce Type: new Abstract: Prompt-based learning has emerged as a dominant paradigm in natural language processing.
arXiv:2602. 12996v2 Announce Type: replace-cross Abstract: Knowledge augmentation has significantly enhanced the performance of Large Language Models (LLMs) in knowledge-intensive tasks.
arXiv:2602. 15829v2 Announce Type: replace Abstract: The superficial alignment hypothesis (SAH) posits that large language models learn most of their knowledge during pre-training, and that post-training merely surfaces this knowledge.
arXiv:2606. 12117v1 Announce Type: cross Abstract: Benchmark scores often misrepresent a large language model's (LLM's) knowledge, because they rely, e.
arXiv:2509. 26169v2 Announce Type: replace Abstract: Alignment of large language models remains a central challenge in natural language processing.
arXiv:2607. 08399v1 Announce Type: cross Abstract: Large language models process prompts by propagating activations through dozens of layers before generating a response.