语言大模型 / LLM

Interpretable Mnemonic Generation for Kanji Learning via Expectation-Maximization

Jaewook Lee, Alexander Scarlatos, Andrew Lan

机构 * University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校） 纠错

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

Comments The Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)

Multi-Ontology Integration with Dual-Axis Propagation for Medical Concept Representation

Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Dongjie Wang, Zijun Yao

机构 * University of Kansas（堪萨斯大学） 纠错

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

Comments This work has been accepted as a full research paper at CIKM 2025

THEME: Enhancing Thematic Investing with Semantic Stock Representations and Temporal Dynamics

Hoyoung Lee, Wonbin Ahn, Suhwan Park, Jaehoon Lee, Minjae Kim, Sungdong Yoo, Taeyoon Lim, Woohyung Lim, Yongjae Lee

机构 * Ulsan National Institute of Science and Technology（乌山国立科学技术研究所） ； LG AI Research（LG人工智能研究） 纠错

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

Comments Accepted at ACM International Conference on Information and Knowledge Management (CIKM)

Addressing accuracy and hallucination of LLMs in Alzheimer's disease research through knowledge graphs

Tingxuan Xu, Jiarui Feng, Justin Melendez, Kaleigh Roberts, Donghong Cai, Mingfang Zhu, Donald Elbert, Yixin Chen, Randall J. Bateman

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

Manifold Trajectories in Next-Token Prediction: From Replicator Dynamics to Softmax Equilibrium

Christopher R. Lee-Jenkins

机构 * Centralia College（中央学院） 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、cs.LG

CoRI: Communication of Robot Intent for Physical Human-Robot Interaction

Junxiang Wang, Emek Barış Küçüktabak, Rana Soltani Zarrin, Zackory Erickson

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

Comments To be published in Proceedings of the 9th Conference on Robot Learning (CoRL). 34 pages, 10 figures