语言大模型 / LLM

On the generalization of language models from in-context learning and finetuning: a controlled study

Andrew K. Lampinen, Arslan Chaudhry, Stephanie C. Y. Chan, Cody Wild, Diane Wan, Alex Ku, Jörg Bornschein, Razvan Pascanu, Murray Shanahan, James L. McClelland

机构 * Google DeepMind（谷歌DeepMind） ； Google DeepMind & Stanford University（谷歌DeepMind与斯坦福大学） 纠错

专题命中 预训练与数据 ：language model(title,abstract)；large language model(abstract)；pretraining(abstract)；分类 cs.CL、cs.AI、cs.LG

Comments FoRLM workshop, NeurIPS 2025

Do Syntactic Categories Help in Developmentally Motivated Curriculum Learning for Language Models?

Arzu Burcu Güven, Anna Rogers, Rob van der Goot

机构 * IT University of Copenhagen（哥本哈根IT大学） 纠错

专题命中 预训练与数据 ：language model(title)；分类 cs.CL

Journal ref Proceedings of the First BabyLM Workshop 2025

Private-RAG: Answering Multiple Queries with LLMs while Keeping Your Data Private

Ruihan Wu, Erchi Wang, Zhiyuan Zhang, Yu-Xiang Wang

机构 * Computer Science and Engineering University of California, San Diego（计算机科学与工程大学加州大学圣地亚哥分校） ； Halıcıoğlu Data Science Institute University of California, San Diego（Halıcıoğlu数据科学研究所加州大学圣地亚哥分校） ； Department of Computer Science University of California, Los Angeles（计算机科学系加州大学洛杉矶分校） 纠错

专题命中 预训练与数据 ：large language model(abstract)；language model(abstract)；分类 cs.AI、cs.LG

It Takes Two: A Dual Stage Approach for Terminology-Aware Translation

Akshat Singh Jaswal

机构 * PES University（PES大学） 纠错

专题命中 预训练与数据 ：LLM(abstract)；分类 cs.CL、cs.AI

Comments Accepted to WMT 2025. Code availavle at https://github.com/akshat-sj/duterm

Journal ref In Proceedings of the Tenth Conference on Machine Translation, pages 1344-1350, Suzhou, China. Association for Computational Linguistics (2025)

Laytrol: Preserving Pretrained Knowledge in Layout Control for Multimodal Diffusion Transformers

Sida Huang, Siqi Huang, Ping Luo, Hongyuan Zhang

专题命中 预训练与数据 ：pretraining(abstract)

Comments Accepted by AAAI 2026

Quantum-centric machine learning for molecular dynamics

Yanxian Tao, Lingyun Wan, Xiongzhi Zeng, Yingdi Jin, Jie Liu, Zhenyu Li, Jinlong Yang

专题命中 预训练与数据 ：pretraining(abstract)

Heuristic Time Complexity of NISQ Shortest-Vector-Problem Solvers

Miloš Prokop, Petros Wallden

专题命中 预训练与数据 ：pretraining(abstract)

Comments 33pages, 5figures

Journal ref IEEE Transactions on Quantum Engineering, vol. 6, pp. 1-19 (2025)