语言大模型 / LLM

LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers

Taewook Nam, Juyong Lee, Jesse Zhang, Sung Ju Hwang, Joseph J. Lim, Karl Pertsch

专题命中 其他LLM ：foundation model(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI、cs.LG

Comments 2nd Workshop on Agent Learning in Open-Endedness (ALOE) at NeurIPS 2023

FoMo Rewards: Can we cast foundation models as reward functions?

Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan, Taco Cohen

专题命中 其他LLM ：foundation model(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI、cs.LG

Comments Accepted to NeurIPS FMDM workshop

Zero-shot audio captioning with audio-language model guidance and audio context keywords

Leonard Salewski, Stefan Fauth, A. Sophia Koepke, Zeynep Akata

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI

Comments NeurIPS 2023 - Machine Learning for Audio Workshop (Oral)

Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model

Minh-Hao Van, Xintao Wu

专题命中 其他LLM ：language model(title,abstract)；large language model(abstract)；prompting(abstract)；分类 cs.CL、cs.AI

Red Teaming Language Model Detectors with Language Models

Zhouxing Shi, Yihan Wang, Fan Yin, Xiangning Chen, Kai-Wei Chang, Cho-Jui Hsieh

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.LG

Comments Preprint. Accepted by TACL

Rationale-Enhanced Language Models are Better Continual Relation Learners

Weimin Xiong, Yifan Song, Peiyi Wang, Sujian Li

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI

Comments Accepted at EMNLP 2023

Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?

Adaku Uchendu, Jooyoung Lee, Hua Shen, Thai Le, Ting-Hao 'Kenneth' Huang, Dongwon Lee

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI

Comments Accepted at The 11th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2023)

SPELL: Semantic Prompt Evolution based on a LLM

Yujian Betterest Li, Kai Wu

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI

An Appraisal-Based Chain-Of-Emotion Architecture for Affective Language Model Game Agents

Maximilian Croissant, Madeleine Frister, Guy Schofield, Cade McCall

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI

Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding

Zheng Chen, Ziyan Jiang, Fan Yang, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, Aram Galstyan

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI、cs.LG

Protect Your Prompts: Protocols for IP Protection in LLM Applications

M. A. van Wyk, M. Bekker, X. L. Richards, K. J. Nixon

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI

Comments 5 pages, 2 figures

Deliberate then Generate: Enhanced Prompting Framework for Text Generation

Bei Li, Rui Wang, Junliang Guo, Kaitao Song, Xu Tan, Hany Hassan, Arul Menezes, Tong Xiao, Jiang Bian, JingBo Zhu

专题命中 其他LLM ：prompting(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI

Evaluating statistical language models as pragmatic reasoners

Benjamin Lipkin, Lionel Wong, Gabriel Grand, Joshua B Tenenbaum

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI

Comments 8 pages, 4 figures, to appear in the Proceedings of the Annual Meeting of the Cognitive Science Society 2023

Generating Executable Action Plans with Environmentally-Aware Language Models

Maitrey Gramopadhye, Daniel Szafir

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract)；large language model(abstract)；分类 cs.CL、cs.AI

Will It Blend? Mixing Training Paradigms & Prompting for Argument Quality Prediction

Michiel van der Meer, Myrthe Reuver, Urja Khurana, Lea Krause, Selene Báez Santamaría

专题命中 其他LLM ：prompting(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.CL、cs.AI

Comments Accepted at the 9th Workshop on Argument Mining (2022)

Sycophancy Claims about Language Models: The Missing Human-in-the-Loop

语言模型中的趋炎附势主张：缺失的人工智能循环

Jan Batzner, Volker Stocker, Stefan Schmid, Gjergji Kasneci

机构 * Weizenbaum Institute（韦岑鲍姆研究所） ； Technical University Berlin（柏林技术大学） ； Technical University Munich（慕尼黑技术大学） 纠错

专题命中 其他LLM ：language model(title,abstract)；LLM(abstract,comments)；large language model(abstract)；分类 cs.CL

AI总结 本文探讨了大型语言模型中趋炎附势现象的测量挑战，提出五个核心操作化定义，并指出当前研究缺乏对人类感知的评估，为未来研究提供建议。

Comments NeurIPS 2025 Workshop on LLM Evaluation and ICLR 2025 Workshop on Bi-Directional Human-AI Alignment

LLM Company Policies and Policy Implications in Software Organizations

Ranim Khojah, Mazen Mohamad, Linda Erlenhov, Francisco Gomes de Oliveira Neto, Philipp Leitner

机构 * Chalmers University of Technology and University of Gothenburg（楚尔姆斯理工大学和哥德堡大学） 纠错

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI

Comments Accepted at IEEE Software Special Issue on AIware in the Foundation Models Era

LLM assisted web application functional requirements generation: A case study of four popular LLMs over a Mess Management System

Rashmi Gupta, Aditya K Gupta, Aarav Jain, Avinash C Pandey, Atul Gupta

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI

Comments 11 pages, 12 figures, Accepted in EASE 2025 https://conf.researchr.org/details/ease-2025/ease-2025-ai-models---data/11/LLM-assisted-web-application-functional-requirements-generation-A-case-study-of-fou

PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generation

Ye Liu, Yue Xue, Daoyuan Wu, Yuqiang Sun, Yi Li, Miaolei Shi, Yang Liu

专题命中 其他LLM ：LLM(title,abstract)；large language model(abstract)；language model(abstract)；分类 cs.AI

Comments Accepted by NDSS Symposium 2025. Please cite the conference version of this paper, e.g., "Ye Liu, Yue Xue, Daoyuan Wu, Yuqiang Sun, Yi Li, Miaolei Shi, Yang Liu. PropertyGPT: LLM-driven Formal Verification of Smart Contracts through Retrieval-Augmented Property Generation. In 32nd Annual Network and Distributed System Security Symposium (NDSS 2025)."

SteP: Stacked LLM Policies for Web Actions

Paloma Sodhi, S. R. K. Branavan, Yoav Artzi, Ryan McDonald

专题命中 其他LLM ：LLM(title,abstract)；language model(abstract,comments)；large language model(abstract)；分类 cs.LG

Comments Accepted at Conference on Language Modeling (COLM) 2024. 30 pages, 15 figures

Generative AI-Enabled Mission-Aware Radio Orchestration for RIS-Assisted LEO Satellite ISAC Systems

面向RIS辅助低轨卫星一体化感知通信（ISAC）系统的生成式AI赋能任务感知无线电编排

Fitsum Debebe Tilahun, Chung G. Kang

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 针对RIS辅助LEO ISAC系统，本文提出生成式AI赋能的无线电编排框架，利用LLM将任务映射为结构化策略，对比LLM-ZS与LLM-ICL在组合任务上的性能，验证生成式AI可增强无线电编排且不替代关键物理层优化。

GuideFetch: A Task Coordination Framework for Concurrent Navigation and Object Retrieval in Assistive Robot Dogs

GuideFetch：用于辅助机器狗并发导航与物体检索的任务协调框架

Qian Yin, Ruiping Liu, Kunyu Peng, Jianxiang Man, Isik Baran Sandan, Junwei Zheng, Yufan Chen, Di Wen, Kailun Yang, Rainer Stiefelhagen

机构 * Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院） ； Hunan University（湖南大学） 纠错

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 针对异构辅助机器狗的导航与物体检索并发任务，提出GuideFetch协调框架，通过LLM规划与状态验证提升执行效率，并行执行可缩短41.3%平均总完成时间。

Comments Accepted to the 1st Workshop on Multimodal Digital Agents (MDA) at ECCV 2026

Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes

探索在特定软件工程目的中采用LLMs的个体因素

Stefano Lambiase, Gemma Catolino, Fabio Palomba, Filomena Ferrucci, Daniel Russo

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 本文研究个体因素如何影响软件工程师在特定软件工程任务中采用LLMs，通过结构方程模型分析五个关键目的中的相关属性，揭示不同因素对LLM采用的影响。

From Search Agents to Dissemination Interfaces: Understanding Human Trust in Health Information from Conversational Search

从搜索智能体到传播界面：理解人们对对话式搜索中健康信息的信任

Xin Sun, Rongjun Ma, Xiaochang Zhao, Janne Lindqvist, Jan de Wit, Zhuying Li, Abdallah El Ali, Jos A. Bosch

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 本研究通过两项混合方法研究，发现人们对ChatGPT提供的健康信息信任显著高于谷歌，且传播界面类型会显著影响这种信任，为开发可信的LLM驱动健康工具提供了关键见解。

An Extensive Empirical Study on Code Translation Technique

代码翻译技术的大规模实证研究

Ruihang Fan, Jiajun Jiang, Xinpeng Wang, Jiateng Fu, Fengjie Li, Jiasi Shen

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 本研究通过大规模实证对比，发现LLM及基于LLM的代码翻译方法在方法级正确性上优于学习类方法，类级翻译更难，静态与逻辑错误是主要挑战，为代码翻译技术开发提供指导。

MAG-Bot: A Multi-Agent Auditing Framework for Social Bot Detection

MAG-Bot：一种用于社交机器人检测的多智能体审计框架

Sichen Zhao, Yalun Qi

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 本研究提出基于LangGraph的多智能体框架MAG-Bot，用于社交机器人检测，通过角色约束的证据分解修正单LLM审计的盲点，在TwiBot-22测试集上显著提升了检测的准确率、召回率与F1值。

Equivalence Checking of ML GPU Kernels

ML GPU 内核的等价性检查

Benjamin Driscoll, Kshitij Dubey, Anjiang Wei, Neeraj Kayal, Rahul Sharma, Alex Aiken

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 研究人员提出首个GPU内核等价性检查器Volta，可验证手工、LLM及编译器优化的ML内核正确性，适用于卷积、矩阵乘法等ML计算。

Search or Chat? Comparing How We Learn About Debated Topics

搜索还是聊天？对比我们如何了解有争议的话题

Ran Yu, Alisa Rieger, Rabia Karatoprak Ersen, Jiqun Liu

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 该研究通过194人参与的众包实验，对比传统搜索与LLM聊天界面对学习有争议话题的影响，发现工具无显著差异，用户特征对学习结果影响更大。

Explanatory Engagement Under Rare Anomalous Failure: Asymptotic Rarity in Model Behavior (or: The Asymptotic AI)

罕见异常失效下的解释性参与：模型行为中的渐近稀有性（或：渐近式AI）

Sam Mao

专题命中 其他LLM ：LLM(summary_cn,abstract)；prompting(abstract)；分类 cs.CL、cs.AI、cs.LG

AI总结 本研究探究LLM在低可控失效概率工作流中，解释性参与度随失效渐近稀有性的变化，发现触发结构是关键调节变量，不同模型的异常识别与参与表现存在差异。

Comments 11 figures. Elicitation-condition sweep across three open-weight models (qwen3:8b, llama3.1:8b, mistral:7b); pipeline scripts and experimental data available upon reasonable request

Who Is Really Playing? Strategic Interaction in AI-Guided Populations

通过AI维持群体合作：一种针对大语言模型的folk定理

Jonathan Shaki, Eden Hartman, Sarit Kraus, Yonatan Aumann

专题命中 其他LLM ：LLM(summary_cn,abstract)；large language model(abstract)；language model(abstract)

AI总结 本文研究了大语言模型如何通过指导多个群体中的代理实现合作，发现即使基础游戏激励不一致，共享LLM指导也能维持合作，证明了针对LLM的folk定理。