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Large language models (LLMs) have demonstrated significant progress in various natural language generation and understanding tasks. However, their linguistic generalization capabilities remain questionable, raising doubts about whether…

Recent development of large-scale pre-trained language models (PLM) have significantly improved the capability of models in various NLP tasks, in terms of performance after task-specific fine-tuning and zero-shot / few-shot learning.…

Computation and Language · Computer Science 2022-04-21 Chenguang Zhu , Michael Zeng

Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them…

What makes large language models (LLMs) impressive is also what makes them hard to evaluate: their diversity of uses. To evaluate these models, we must understand the purposes they will be used for. We consider a setting where these…

Computation and Language · Computer Science 2024-06-04 Keyon Vafa , Ashesh Rambachan , Sendhil Mullainathan

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs,…

Computation and Language · Computer Science 2023-10-10 Thilo Hagendorff , Sarah Fabi

Large language models (LLMs) have demonstrated impressive capabilities in general scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses, human-level intelligence. Among their numerous skills, the…

Computation and Language · Computer Science 2023-11-30 Zhiwei He , Tian Liang , Wenxiang Jiao , Zhuosheng Zhang , Yujiu Yang , Rui Wang , Zhaopeng Tu , Shuming Shi , Xing Wang

Evaluating reasoning ability in Large Language Models (LLMs) is important for advancing artificial intelligence, as it transcends mere linguistic task performance. It involves understanding whether these models truly understand information,…

Artificial Intelligence · Computer Science 2025-10-29 Benjamin Grando Moreira

This study investigates the efficacy of large language models (LLMs) as tools for grading master-level student essays. Utilizing a sample of 60 essays in political science, the study compares the accuracy of grades suggested by the GPT-4…

General Economics · Economics 2024-06-25 Magnus Lundgren

Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI)…

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

Machine Learning · Computer Science 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

Large Language Models (LLMs) like GPT-3 and GPT-4 have emerged as groundbreaking innovations with capabilities that extend far beyond traditional AI applications. These sophisticated models, trained on massive datasets, can generate…

Software Engineering · Computer Science 2025-05-21 Md Asraful Haque

Large Language Models (LLMs) are able to provide assistance on a wide range of information-seeking tasks. However, model outputs may be misleading, whether unintentionally or in cases of intentional deception. We investigate the ability of…

Computation and Language · Computer Science 2024-07-17 Betty Li Hou , Kejian Shi , Jason Phang , James Aung , Steven Adler , Rosie Campbell

How should we compare the capabilities of language models (LMs) and humans? I draw inspiration from comparative psychology to highlight some challenges. In particular, I consider a case study: processing of recursively nested grammatical…

Computation and Language · Computer Science 2023-02-17 Andrew Kyle Lampinen

Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models…

Artificial Intelligence · Computer Science 2024-05-24 Guilherme F. C. F. Almeida , José Luiz Nunes , Neele Engelmann , Alex Wiegmann , Marcelo de Araújo

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

Language models (LMs) are statistical models trained to assign probability to human-generated text. As such, it is reasonable to question whether they approximate linguistic variability exhibited by humans well. This form of statistical…

Computation and Language · Computer Science 2024-03-19 Evgenia Ilia , Wilker Aziz

Systematic reviews are vital for guiding practice, research, and policy, yet they are often slow and labour-intensive. Large language models (LLMs) could offer a way to speed up and automate systematic reviews, but their performance in such…

Computation and Language · Computer Science 2024-04-11 Qusai Khraisha , Sophie Put , Johanna Kappenberg , Azza Warraitch , Kristin Hadfield

In our opinion the exuberance surrounding the relative success of data-driven large language models (LLMs) is slightly misguided and for several reasons (i) LLMs cannot be relied upon for factual information since for LLMs all ingested text…

Computation and Language · Computer Science 2023-09-15 Walid S. Saba

Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored. However, little work has been done on investigating the pedagogical ability of…

Computation and Language · Computer Science 2023-10-23 An-Zi Yen , Wei-Ling Hsu

Large language models (LLMs) have emerged as powerful tools for many AI problems and exhibit remarkable in-context learning (ICL) capabilities. Compositional ability, solving unseen complex tasks that combine two or more simple tasks, is an…

Computation and Language · Computer Science 2024-08-13 Zhuoyan Xu , Zhenmei Shi , Yingyu Liang