语言大模型 / LLM

Beyond the Black Box: Integrating Lexical and Semantic Methods in Quantitative Discourse Analysis with BERTopic

Thomas Compton

机构 * University of York（约克大学） 纠错

专题命中 知识编辑与模型理解 ：large language model(abstract)；language model(abstract)；分类 cs.CL

Comments 5 pages conference paper, 4 tables

Trustworthy Agents for Electronic Health Records through Confidence Estimation

Yongwoo Song, Minbyul Jeong, Mujeen Sung

机构 * Kyung Hee University（庆熙大学） 纠错

专题命中 知识编辑与模型理解 ：large language model(abstract)；language model(abstract)；分类 cs.AI

Novel Approaches to Artificial Intelligence Development Based on the Nearest Neighbor Method

I. I. Priezzhev, D. A. Danko, A. V. Shubin

机构 * National University of Oil and Gas «Gubkin University»（石油国家大学「古比金大学」） ； IPLab LLC（IPLab公司） 纠错

专题命中 知识编辑与模型理解 ：large language model(abstract)；language model(abstract)；分类 cs.AI

Comments 18 pages, 6 figures. Novel hierarchical neural networks based on k-nearest neighbors method for addressing hallucination effects, training complexity, and catastrophic forgetting in modern AI systems. Includes mathematical formulations using Kohonen self-organizing maps and experimental validation on MNIST handwritten digit recognition and machine translation tasks

OmniHuman-1.5: Instilling an Active Mind in Avatars via Cognitive Simulation

Jianwen Jiang, Weihong Zeng, Zerong Zheng, Jiaqi Yang, Chao Liang, Wang Liao, Han Liang, Yuan Zhang, Mingyuan Gao

机构 * Intelligent Creation Lab, ByteDance（字节跳动智能创作实验室） 纠错

专题命中 知识编辑与模型理解 ：large language model(abstract)；language model(abstract)

Comments Homepage: https://omnihuman-lab.github.io/v1_5/

Of the People, By the Algorithm: How AI Transforms Democratic Representation

Yuval Rymon

专题命中 知识编辑与模型理解 ：large language model(abstract)；language model(abstract)

Comments 13 pages

Can VLMs Recall Factual Associations From Visual References?

Dhananjay Ashok, Ashutosh Chaubey, Hirona J. Arai, Jonathan May, Jesse Thomason

机构 * University of Southern California（南加州大学） ； Information Sciences Institute, University of Southern California（信息科学研究所，南加州大学） 纠错

专题命中 知识编辑与模型理解 ：language model(abstract)；分类 cs.CL、cs.AI

Comments To appear at EMNLP 2025 (Findings)

MergeSAM: Unsupervised change detection of remote sensing images based on the Segment Anything Model

Meiqi Hu, Lingzhi Lu, Chengxi Han, Xiaoping Liu

专题命中 知识编辑与模型理解 ：foundation model(abstract)

Comments 4 pages