English
Related papers

Related papers: Epistemic Alignment: A Mediating Framework for Use…

200 papers

Large language models are increasingly relied upon as sources of information, but their propensity for generating false or misleading statements with high confidence poses risks for users and society. In this paper, we confront the critical…

As Large Language Models (LLMs) rise in popularity, it is necessary to assess their capability in critically relevant domains. We present a comprehensive evaluation framework, grounded in science communication research, to assess LLM…

Large Language Models (LLMs) have demonstrated unprecedented language understanding and reasoning capabilities to capture diverse user preferences and advance personalized recommendations. Despite the growing interest in LLM-based…

Information Retrieval · Computer Science 2025-04-30 Zihuai Zhao , Wenqi Fan , Yao Wu , Qing Li

We examine epistemological threats posed by human and LLM interaction. We develop collective epistemology as a theory of epistemic warrant distributed across human collectives, using bounded rationality and dual process theory as…

Human-Computer Interaction · Computer Science 2026-03-05 Angjelin Hila

The rapid integration of large language models (LLMs) into everyday workflows has transformed how individuals perform cognitive tasks such as writing, programming, analysis, and multilingual communication. While prior research has focused…

Artificial Intelligence · Computer Science 2026-04-29 Hyunwoo Kim , Harin Yu , Hanau Yi

The increasing use of LLMs as substitutes for humans in ``aligning'' LLMs has raised questions about their ability to replicate human judgments and preferences, especially in ambivalent scenarios where humans disagree. This study examines…

Computation and Language · Computer Science 2025-06-02 Bhaktipriya Radharapu , Manon Revel , Megan Ung , Sebastian Ruder , Adina Williams

Large language models (LLMs) are rapidly transforming knowledge work by improving the quality and efficiency of tasks such as writing, coding, and data analysis. However, their growing use in education has exposed a learning-performance…

Large language models (LLMs) are prone to hallucination stemming from misaligned self-awareness, particularly when processing queries exceeding their knowledge boundaries. While existing mitigation strategies employ uncertainty estimation…

Computation and Language · Computer Science 2025-10-10 Hang Zheng , Hongshen Xu , Yuncong Liu , Lu Chen , Pascale Fung , Kai Yu

In the age of artificial intelligence, the role of large language models (LLMs) is becoming increasingly central. Despite their growing prevalence, their capacity to consolidate knowledge from different training documents - a crucial…

Computation and Language · Computer Science 2024-02-26 Gabriele Prato , Jerry Huang , Prasannna Parthasarathi , Shagun Sodhani , Sarath Chandar

Large Language Models (LLMs) have developed rapidly and are widely applied to both general-purpose and professional tasks to assist human users. However, they still struggle to comprehend and respond to the true user needs when intentions…

Computation and Language · Computer Science 2026-02-17 Minyuan Ruan , Ziyue Wang , Kaiming Liu , Yunghwei Lai , Peng Li , Yang Liu

Effective feedback is essential for fostering students' success in scientific inquiry. With advancements in artificial intelligence, large language models (LLMs) offer new possibilities for delivering instant and adaptive feedback. However,…

Artificial Intelligence · Computer Science 2025-02-19 Kathrin Seßler , Arne Bewersdorff , Claudia Nerdel , Enkelejda Kasneci

Large Language Models (LLMs) acquire extensive knowledge and remarkable abilities from extensive text corpora, making them powerful tools for various applications. To make LLMs more usable, aligning them with human preferences is essential.…

Computation and Language · Computer Science 2024-10-21 Mozhi Zhang , Pengyu Wang , Chenkun Tan , Mianqiu Huang , Dong Zhang , Yaqian Zhou , Xipeng Qiu

Large language models (LLMs) have shown remarkable capabilities in dialogue generation and reasoning, yet their effectiveness in eliciting user-known but concealed information in open-ended conversations remains limited. In many interactive…

Machine Learning · Computer Science 2026-04-16 Tao Wang , Jingyao Lu , Xibo Wang , Haonan Huang , Su Yao , Zhiqiang Hu , Xingyan Chen , Enmao Diao

In recent years, large language models (LLMs), such as GPTs, have attained great impact worldwide. However, how to adapt these LLMs to better suit the vertical domain-specific tasks by utilizing external knowledge remains not completely…

Computation and Language · Computer Science 2023-11-03 Peng Fu , Yiming Zhang , Haobo Wang , Weikang Qiu , Junbo Zhao

Understanding human attitudes, preferences, and behaviors through social surveys is essential for academic research and policymaking. Yet traditional surveys face persistent challenges, including fixed-question formats, high costs, limited…

Computation and Language · Computer Science 2025-11-14 Chenxi Lin , Weikang Yuan , Zhuoren Jiang , Biao Huang , Ruitao Zhang , Jianan Ge , Yueqian Xu , Jianxing Yu

Large Language Models (LLMs) are transforming writing, reading, teaching, and knowledge retrieval in many academic fields. However, concerns regarding their misuse and erroneous outputs have led to varying degrees of trust in LLMs within…

Computers and Society · Computer Science 2025-02-10 Minseok Jung , Aurora Zhang , May Fung , Junho Lee , Paul Pu Liang

Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue. To enable these tutoring systems to provide personalized support, it is essential to…

Computation and Language · Computer Science 2026-05-05 Shuyan Huang , Alexander Scarlatos , Jaewook Lee , Andrew Lan

E-learning environments are increasingly harnessing large language models (LLMs) like GPT-3.5 and GPT-4 for tailored educational support. This study introduces an approach that integrates dynamic knowledge graphs with LLMs to offer nuanced…

Artificial Intelligence · Computer Science 2024-12-06 Patrick Ocheja , Brendan Flanagan , Yiling Dai , Hiroaki Ogata

To assist users in complex tasks, LLMs generate plans: step-by-step instructions towards a goal. While alignment methods aim to ensure LLM plans are helpful, they train (RLHF) or evaluate (ChatbotArena) on what users prefer, assuming this…

To improve the performance of large language models (LLMs), researchers have explored providing LLMs with textual task-solving experience via prompts. However, they rely on manual efforts to acquire and apply such experience for each task,…

Computation and Language · Computer Science 2024-07-15 Jinglong Gao , Xiao Ding , Yiming Cui , Jianbai Zhao , Hepeng Wang , Ting Liu , Bing Qin
‹ Prev 1 3 4 5 6 7 10 Next ›