语言大模型 / LLM

Unlocking the Power of LLM Uncertainty for Active In-Context Example Selection

Hsiu-Yuan Huang, Zichen Wu, Yutong Yang, Junzhao Zhang, Yunfang Wu

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

Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

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

Comments To appear in NeurIPS 2024 under the modified title 'From Causal to Concept-Based Representation Learning'

Enhancing Zero-shot Chain of Thought Prompting via Uncertainty-Guided Strategy Selection

Shanu Kumar, Saish Mendke, Karody Lubna Abdul Rahman, Santosh Kurasa, Parag Agrawal, Sandipan Dandapat

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

Comments Accepted in COLING 2025

SAUP: Situation Awareness Uncertainty Propagation on LLM Agent

Qiwei Zhao, Xujiang Zhao, Yanchi Liu, Wei Cheng, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Huaxiu Yao, Haifeng Chen

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

LLM Generated Distribution-Based Prediction of US Electoral Results, Part I

Caleb Bradshaw, Caelen Miller, Sean Warnick

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

Comments 17 pages, 10 Figures, Pre-print

CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept

YuXuan Wu, Bonaventure F. P. Dossou, Dianbo Liu

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

Mechanistic Behavior Editing of Language Models

Joykirat Singh, Subhabrata Dutta, Tanmoy Chakraborty

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

HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection

Xuefeng Du, Chaowei Xiao, Yixuan Li

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

Comments NeurIPS 2024 Spotlight

ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented Framework

Zhongqi Yang, Elahe Khatibi, Nitish Nagesh, Mahyar Abbasian, Iman Azimi, Ramesh Jain, Amir M. Rahmani

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

Comments Published on Smart Health

Journal ref Smart Health 32 (2024): 100465

Confidence Estimation for LLM-Based Dialogue State Tracking

Yi-Jyun Sun, Suvodip Dey, Dilek Hakkani-Tur, Gokhan Tur

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

Comments Accepted for publication at IEEE SLT 2024

Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in?

Chengzhi Zhong, Fei Cheng, Qianying Liu, Junfeng Jiang, Zhen Wan, Chenhui Chu, Yugo Murawaki, Sadao Kurohashi

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

Comments work in progress

Effective Prompt Extraction from Language Models

Yiming Zhang, Nicholas Carlini, Daphne Ippolito

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

SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals

Ruihan Yang, Jiangjie Chen, Yikai Zhang, Siyu Yuan, Aili Chen, Kyle Richardson, Yanghua Xiao, Deqing Yang

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

Comments Preprint

Analyzing LLM Behavior in Dialogue Summarization: Unveiling Circumstantial Hallucination Trends

Sanjana Ramprasad, Elisa Ferracane, Zachary C. Lipton

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

Comments Accepted at ACL 2024

Cycles of Thought: Measuring LLM Confidence through Stable Explanations

Evan Becker, Stefano Soatto

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

GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications

Shishir G. Patil, Tianjun Zhang, Vivian Fang, Noppapon C., Roy Huang, Aaron Hao, Martin Casado, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica

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

SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection

Bradley P. Allen, Fina Polat, Paul Groth

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

Comments 6 pages, 6 figures, 4 tables, camera-ready copy, accepted to the 18th International Workshop on Semantic Evaluation (SemEval-2024), for associated code and data see https://github.com/bradleypallen/shroom

Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition

Kyle Buettner, Sina Malakouti, Xiang Lorraine Li, Adriana Kovashka

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

Comments To appear in IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024

TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

Chenxi Sun, Hongyan Li, Yaliang Li, Shenda Hong

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

Supporting Student Decisions on Learning Recommendations: An LLM-Based Chatbot with Knowledge Graph Contextualization for Conversational Explainability and Mentoring

Hasan Abu-Rasheed, Mohamad Hussam Abdulsalam, Christian Weber, Madjid Fathi

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

A Vision Check-up for Language Models

Pratyusha Sharma, Tamar Rott Shaham, Manel Baradad, Stephanie Fu, Adrian Rodriguez-Munoz, Shivam Duggal, Phillip Isola, Antonio Torralba

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

Uncertainty-aware Language Modeling for Selective Question Answering

Qi Yang, Shreya Ravikumar, Fynn Schmitt-Ulms, Satvik Lolla, Ege Demir, Iaroslav Elistratov, Alex Lavaee, Sadhana Lolla, Elaheh Ahmadi, Daniela Rus, Alexander Amini, Alejandro Perez

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

Hallucination Augmented Recitations for Language Models

Abdullatif Köksal, Renat Aksitov, Chung-Ching Chang

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

Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher

Xiang Shi, Jiawei Liu, Yinpeng Liu, Qikai Cheng, Wei Lu

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

Comments 14 pages, 4 figures, under peer review

Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Jiuhai Chen, Jonas Mueller

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

Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations

Cedric Waterschoot, Nava Tintarev, Francesco Barile

机构 * Maastricht University（马斯特里赫特大学） 纠错

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

Comments Short paper accepted at the Nineteenth ACM Conference on Recommender Systems (RecSys '25). Cedric Waterschoot, Nava Tintarev, and Francesco Barile. 2025. Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations. Proceedings of the Nineteenth ACM Conference on Recommender Systems (RecSys '25), Prague, Czech Republic. doi: 10.1145/3705328.3748015

Analysing the Residual Stream of Language Models Under Knowledge Conflicts

Yu Zhao, Xiaotang Du, Giwon Hong, Aryo Pradipta Gema, Alessio Devoto, Hongru Wang, Xuanli He, Kam-Fai Wong, Pasquale Minervini

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

Comments Foundation Model Interventions Workshop @ NeurIPS 2024

Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation

Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee

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

Comments Accepted in Socially Responsible Language Modelling Research (SoLaR) 2023 at NeurIPS 2023; the first two authors contribute equally

Execution-Anchored Hallucination Calibration Reranking for Verilog Code Generation

面向Verilog代码生成的执行锚定幻觉校准重排序

Guang Yang, Xing Hu, Xiang Chen, Terry Yue Zhuo, Xin Xia

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

AI总结 该研究针对LLM生成Verilog代码时的性能问题，提出EAHC重排序框架，通过双通道架构融合执行与推理信号，解决现有方法的域迁移差和推理幻觉问题。

Collective Hallucination in Multi-Agent LLMs:Modeling and Defense

多智能体大语言模型中的集体幻觉：建模与防御

Saeid Jamshidi

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

AI总结 提出一种系统级模型描述多智能体LLM中幻觉的传播与放大，并设计交互感知控制方法，通过置信加权聚合、自适应影响调节、外部验证和隔离不可靠智能体来抑制错误传播，在TruthfulQA和TriviaQA上使幻觉降低39%，事实准确率提升至0.87。