语言大模型 / LLM

DP-GPT4MTS: Dual-Prompt Large Language Model for Textual-Numerical Time Series Forecasting

Chanjuan Liu, Shengzhi Wang, Enqiang Zhu

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

Meta-rater: A Multi-dimensional Data Selection Method for Pre-training Language Models

Xinlin Zhuang, Jiahui Peng, Ren Ma, Yinfan Wang, Tianyi Bai, Xingjian Wei, Jiantao Qiu, Chi Zhang, Ying Qian, Conghui He

机构 * Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； School of Computer Science and Technology, East China Normal University（东华大学计算机科学与技术学院） 纠错

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

Comments ACL 2025 Best Theme Paper Award

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation

Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu

机构 * Computer Science and Engineering（计算机科学与工程） ； Michigan State University（密歇根州立大学） ； Meta 纠错

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

Comments Accepted by KDD 2025 Research Track

Privileged Contrastive Pretraining for Multimodal Affect Modelling

Kosmas Pinitas, Konstantinos Makantasis, Georgios N. Yannakakis

机构 * Institute of Digital Games University of Malta（数字游戏研究所马耳他大学） ； Department of Artificial Intelligence University of Malta（人工智能系马耳他大学） 纠错

专题命中 预训练与数据 ：pretraining(title,abstract)；分类 cs.LG

Why are LLMs' abilities emergent?

Vladimír Havlík

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

Comments 20 pages

How Deep Is Representational Bias in LLMs? The Cases of Caste and Religion

Agrima Seth, Monojit Choudhary, Sunayana Sitaram, Kentaro Toyama, Aditya Vashistha, Kalika Bali

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

Comments Accepted to AIES 2025

T3Time: Tri-Modal Time Series Forecasting via Adaptive Multi-Head Alignment and Residual Fusion

Abdul Monaf Chowdhury, Rabeya Akter, Safaeid Hossain Arib

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

LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points

Xuemiao Zhang, Can Ren, Chengying Tu, Rongxiang Weng, Hongfei Yan, Jingang Wang, Xunliang Cai

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

Understanding In-Context Learning of Linear Models in Transformers Through an Adversarial Lens

Usman Anwar, Johannes Von Oswald, Louis Kirsch, David Krueger, Spencer Frei

机构 * University of Cambridge（剑桥大学） ； Google, Paradigms of Intelligence Team（谷歌，Paradigms of Intelligence团队） ； Google DeepMind（谷歌DeepMind） ； Mila & Université de Montréal（Mila与蒙特利尔大学） ； UC Davis（加州大学戴维斯分校） 纠错

专题命中 预训练与数据 ：pretraining(abstract)；分类 cs.LG

Comments Transactions on Machine Learning Research (TMLR) 2025, with Featured Certification

What Holds Back Open-Vocabulary Segmentation?

Josip Šarić, Ivan Martinović, Matej Kristan, Siniša Šegvić

机构 * Faculty of Computer and Information Science（计算机与信息科学学院） ； Faculty of Electrical Engineering and Computing（电子工程与计算学院） 纠错

专题命中 预训练与数据 ：pretraining(abstract)；foundation model(comments)

Comments Accepted for publication at ICCV 25 Workshop: What is Next in Multimodal Foundation Models?

DP-DocLDM: Differentially Private Document Image Generation using Latent Diffusion Models

Saifullah Saifullah, Stefan Agne, Andreas Dengel, Sheraz Ahmed

专题命中 预训练与数据 ：pretraining(abstract)

Comments Accepted in ICDAR 2025