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This paper presents a systematic defense of large language model (LLM) hallucinations or 'confabulations' as a potential resource instead of a categorically negative pitfall. The standard view is that confabulations are inherently…

计算与语言 · 计算机科学 2024-06-27 Peiqi Sui , Eamon Duede , Sophie Wu , Richard Jean So

The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper…

计算与语言 · 计算机科学 2024-08-26 Desta Haileselassie Hagos , Rick Battle , Danda B. Rawat

Large Language Models (LLMs) are being integrated into professional domains, yet their limitations in such high-stakes fields as law remain poorly understood. In response, this paper introduces examples of critical challenges to the…

人工智能 · 计算机科学 2026-01-27 Eljas Linna , Tuula Linna

Recent advancements in large language models (LLMs) have sparked optimism about their potential to accelerate scientific discovery, with a growing number of works proposing research agents that autonomously generate and validate new ideas.…

计算与语言 · 计算机科学 2024-09-09 Chenglei Si , Diyi Yang , Tatsunori Hashimoto

Large language models (LLMs) have significant potential for generating educational questions and problems, enabling educators to create large-scale learning materials. However, LLMs are fundamentally limited by the ``Artificial Hivemind''…

人工智能 · 计算机科学 2025-12-30 Manh Hung Nguyen , Adish Singla

AI large language models have (co-)produced amazing written works from newspaper articles to novels and poetry. These works meet the standards of the standard definition of creativity: being original and useful, and sometimes even the…

人工智能 · 计算机科学 2022-06-22 Claire Stevenson , Iris Smal , Matthijs Baas , Raoul Grasman , Han van der Maas

Given the remarkable performance of Large Language Models (LLMs), an important question arises: Can LLMs conduct human-like scientific research and discover new knowledge, and act as an AI scientist? Scientific discovery is an iterative…

机器学习 · 计算机科学 2025-02-24 Tingting Chen , Srinivas Anumasa , Beibei Lin , Vedant Shah , Anirudh Goyal , Dianbo Liu

With recent Nobel Prizes recognising AI contributions to science, Large Language Models (LLMs) are transforming scientific research by enhancing productivity and reshaping the scientific method. LLMs are now involved in experimental design,…

Large Language Models (LLMs) are demonstrating rapid improvements on complex reasoning benchmarks, particularly when allowed to utilize intermediate reasoning steps before converging on a final solution. However, current literature often…

计算与语言 · 计算机科学 2026-01-01 Ákos Prucs , Márton Csutora , Mátyás Antal , Márk Marosi

Story-writing is a fundamental aspect of human imagination, relying heavily on creativity to produce narratives that are novel, effective, and surprising. While large language models (LLMs) have demonstrated the ability to generate…

计算与语言 · 计算机科学 2025-05-13 Mete Ismayilzada , Claire Stevenson , Lonneke van der Plas

Large language models (LLMs) are increasingly used in verbal creative tasks. However, previous assessments of the creative capabilities of LLMs remain weakly grounded in human creativity theory and are thus hard to interpret. The widely…

计算与语言 · 计算机科学 2026-01-29 Kumiko Nakajima , Jan Zuiderveld , Sandro Pezzelle

We introduce the Concept Bottleneck Large Language Model (CB-LLM), a pioneering approach to creating inherently interpretable Large Language Models (LLMs). Unlike traditional black-box LLMs that rely on post-hoc interpretation methods with…

计算与语言 · 计算机科学 2024-07-08 Chung-En Sun , Tuomas Oikarinen , Tsui-Wei Weng

As generative AI becomes increasingly embedded in everyday workflows, it is important to evaluate its performance in ways that reflect real-world usage rather than abstract notions of intelligence. Unlike many existing benchmarks that…

人工智能 · 计算机科学 2025-05-14 Justin K Miller , Wenjia Tang

This paper investigates the potential of AI models, particularly large language models (LLMs), to support knowledge exploration and augment human creativity during ideation. We present "Latent Lab" an interactive tool for discovering…

人工智能 · 计算机科学 2023-11-23 Kevin Dunnell , Trudy Painter , Andrew Stoddard , Andy Lippman

Large language models (LLMs) bring unprecedented flexibility in defining and executing complex, creative natural language generation (NLG) tasks. Yet, this flexibility brings new challenges, as it introduces new degrees of freedom in…

计算与语言 · 计算机科学 2024-07-08 Furkan Şahinuç , Ilia Kuznetsov , Yufang Hou , Iryna Gurevych

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

The evaluation of LLMs' creativity represents a crucial research domain, though challenges such as data contamination and costly human assessments often impede progress. Drawing inspiration from human creativity assessment, we propose PACE,…

计算与语言 · 计算机科学 2025-10-15 Ziliang Qiu , Renfen Hu

Large language models (LLMs) are advanced artificial intelligence (AI) systems that can perform a variety of tasks commonly found in human intelligence tests, such as defining words, performing calculations, and engaging in verbal…

计算与语言 · 计算机科学 2024-09-12 David Ilić , Gilles E. Gignac

This paper explores the enhancement of creativity in Large Language Models (LLMs) like vGPT-4 through associative thinking, a cognitive process where creative ideas emerge from linking seemingly unrelated concepts. Associative thinking…

计算与语言 · 计算机科学 2024-05-14 Pronita Mehrotra , Aishni Parab , Sumit Gulwani

The rapid advancement of generative models has empowered modern AI systems to comprehend and produce highly sophisticated content, even achieving human-level performance in specific domains. However, these models are fundamentally…