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AI systems are gaining widespread adoption across various sectors and domains. Creating high-quality AI system requirements is crucial for aligning the AI system with business goals and consumer values and for social responsibility.…

软件工程 · 计算机科学 2025-07-17 Asma Yamani , Malak Baslyman , Moataz Ahmed

Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only if they faithfully reflect real human behaviors. Current evaluations of simulation fidelity are…

计算与语言 · 计算机科学 2026-04-14 Tiancheng Hu , Joachim Baumann , Lorenzo Lupo , Nigel Collier , Dirk Hovy , Paul Röttger

Large Language Models (LLMs) are increasingly deployed across diverse real-world applications and user communities. As such, it is crucial that these models remain both morally grounded and knowledge-aware. In this work, we uncover a…

计算与语言 · 计算机科学 2026-03-11 Saugata Purkayastha , Pranav Kushare , Pragya Paramita Pal , Sukannya Purkayastha

Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their potential is role-playing, where LLMs simulate diverse roles…

计算机与社会 · 计算机科学 2026-04-23 Xinyue Li , Zhenpeng Chen , Jie M. Zhang , Ying Xiao , Tianlin Li , Weisong Sun , Yang Liu , Yiling Lou , Xuanzhe Liu

Large Language Models (LLMs) have shown impressive capabilities in various applications, but they still face various inconsistency issues. Existing works primarily focus on the inconsistency issues within a single LLM, while we…

计算与语言 · 计算机科学 2024-11-15 Kai Xiong , Xiao Ding , Yixin Cao , Ting Liu , Bing Qin

Large Language Models have become popular for their remarkable capabilities in human-oriented tasks and traditional natural language processing tasks. Its efficient functioning is attributed to the attention mechanism in the Transformer…

计算与语言 · 计算机科学 2023-06-06 Ritwik Sinha , Zhao Song , Tianyi Zhou

Advances in the general capabilities of large language models (LLMs) have led to their use for information retrieval, and as components in automated decision systems. A faithful representation of probabilistic reasoning in these models may…

人工智能 · 计算机科学 2025-04-21 Gabriel Freedman , Francesca Toni

The need for interpretability in deep learning has driven interest in counterfactual explanations, which identify minimal changes to an instance that change a model's prediction. Current counterfactual (CF) generation methods require…

计算与语言 · 计算机科学 2025-12-11 Van Bach Nguyen , Christin Seifert , Jörg Schlötterer

Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code…

材料科学 · 物理学 2024-10-22 Ge Lei , Ronan Docherty , Samuel J. Cooper

Language models (LMs) are used for a diverse range of tasks, from question answering to writing fantastical stories. In order to reliably accomplish these tasks, LMs must be able to discern the modal category of a sentence (i.e., whether it…

计算与语言 · 计算机科学 2026-04-29 Michael A. Lepori , Jennifer Hu , Ishita Dasgupta , Roma Patel , Thomas Serre , Ellie Pavlick

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in…

计算与语言 · 计算机科学 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

Recent advancements in Large Language Models (LLMs) have brought them closer to matching human cognition across a variety of tasks. How well do these models align with human performance in detecting and mapping analogies? Prior research has…

计算与语言 · 计算机科学 2025-07-16 Kalit Inani , Keshav Kabra , Vijay Marupudi , Sashank Varma

Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as superior in handling various natural language processing tasks…

计算与语言 · 计算机科学 2023-11-30 Han Cao , Lingwei Wei , Mengyang Chen , Wei Zhou , Songlin Hu

Narrative understanding involves capturing the author's cognitive processes, providing insights into their knowledge, intentions, beliefs, and desires. Although large language models (LLMs) excel in generating grammatically coherent text,…

计算与语言 · 计算机科学 2026-01-19 Lixing Zhu , Runcong Zhao , Lin Gui , Yulan He

Recent advances in large language models (LLM) have enabled richer social simulations, allowing for the study of various social phenomena. However, most recent work has used a more omniscient perspective on these simulations (e.g., single…

计算与语言 · 计算机科学 2024-10-07 Xuhui Zhou , Zhe Su , Tiwalayo Eisape , Hyunwoo Kim , Maarten Sap

Significant scientific discoveries have driven the progress of human civilisation. The explosion of scientific literature and data has created information barriers across disciplines that have slowed the pace of scientific discovery. Large…

计算与语言 · 计算机科学 2023-11-13 Biqing Qi , Kaiyan Zhang , Haoxiang Li , Kai Tian , Sihang Zeng , Zhang-Ren Chen , Bowen Zhou

A Large Language Model (LLM) represents a cutting-edge artificial intelligence model that generates coherent content, including grammatically precise sentences, human-like paragraphs, and syntactically accurate code snippets. LLMs can play…

软件工程 · 计算机科学 2023-12-11 Robson Santos , Italo Santos , Cleyton Magalhaes , Ronnie de Souza Santos

Large Language Models (LLMs) are trained on vast and diverse internet corpora that often include inaccurate or misleading content. Consequently, LLMs can generate misinformation, making robust fact-checking essential. This review…

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase…

人机交互 · 计算机科学 2025-03-24 Michelle Brachman , Amina El-Ashry , Casey Dugan , Werner Geyer

Large Language Models (LLMs), when used for conditional text generation, often produce hallucinations, i.e., information that is unfaithful or not grounded in the input context. This issue arises in typical conditional text generation…