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AI 大模型

语言大模型 / LLM

大语言模型、预训练、指令微调、后训练和语言模型应用。

2025-09-04 至 2025-09-04 共收录 7 信号源:cs.CL, cs.AI, cs.LG

1. 知识编辑与模型理解 7 篇

2501.09997 2025-09-04 cs.CL cs.AI 90%

Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models

Qiang Liu, Xinlong Chen, Yue Ding, Bowen Song, Weiqiang Wang, Shu Wu, Liang Wang

机构 * New Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences (CASIA)(模式识别新实验室、多模态人工智能系统国家重点实验室、自动化研究所、中国科学院)

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

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2509.02805 2025-09-04 cs.LG 79%

Challenges in Understanding Modality Conflict in Vision-Language Models

Trang Nguyen, Jackson Michaels, Madalina Fiterau, David Jensen

机构 * Manning College of Information \& Computer Sciences, University of Massachusetts Amherst, Amherst, U.S.

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

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2509.03518 2025-09-04 cs.LG 78%

Can LLMs Lie? Investigation beyond Hallucination

Haoran Huan, Mihir Prabhudesai, Mengning Wu, Shantanu Jaiswal, Deepak Pathak

机构 * Carnegie Mellon University(卡内基梅隆大学)

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

Comments Website at https://llm-liar.github.io/

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2509.02170 2025-09-04 cs.CL cs.AI 73%

Avoidance Decoding for Diverse Multi-Branch Story Generation

Kyeongman Park, Nakyeong Yang, Kyomin Jung

机构 * Seoul National University(首尔国立大学)

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

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2509.02879 2025-09-04 econ.TH 67%

Artificial or Human Intelligence?

Eric Gao

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

Comments 20 pages

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2409.06509 2025-09-04 cs.CV cs.AI cs.LG 62%

Aligning Machine and Human Visual Representations across Abstraction Levels

Lukas Muttenthaler, Klaus Greff, Frieda Born, Bernhard Spitzer, Simon Kornblith, Michael C. Mozer, Klaus-Robert Müller, Thomas Unterthiner, Andrew K. Lampinen

机构 * Google DeepMind Machine Learning Group(谷歌DeepMind机器学习组) Technische Universität Berlin(技术大学柏林) BIFOLD Berlin Institute for the Foundations of Learning and Data(柏林学习与数据基础研究所) Max Planck Institute for Human Cognitive and Brain Sciences(人类认知与脑科学Max Planck研究所) Max Planck Institute for Human Development(人类发展Max Planck研究所) TUD Dresden University of Technology(德累斯顿技术大学) Anthropic Department of Artificial Intelligence, Korea University(人工智能系,韩国大学) Max Planck Institute for Informatics(信息Max Planck研究所)

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

Comments 91 pages

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2508.20757 2025-09-04 cs.CL 57%

GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation

Yuanhao Ding, Esteban Garces Arias, Meimingwei Li, Julian Rodemann, Matthias Aßenmacher, Danlu Chen, Gaojuan Fan, Christian Heumann, Chongsheng Zhang

机构 * Henan University(河南大学) Department of Statistics, LMU Munich(慕尼黑大学统计系) Munich Center for Machine Learning (MCML)(慕尼黑机器学习中心) CISPA Helmholtz Center for Information Security, Saarbrücken(萨尔布吕肯亥姆霍尔兹信息安全中心) University of California, San Diego(加州大学圣地亚哥分校)

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

Comments Accepted at Findings of the Association for Computational Linguistics: EMNLP 2025

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