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Large language models (LLMs) are demonstrably capable of cross-lingual transfer, but can produce inconsistent output when prompted with the same queries written in different languages. To understand how language models are able to…

计算与语言 · 计算机科学 2025-09-29 Zheng Wei Lim , Alham Fikri Aji , Trevor Cohn

Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with disinformation content might have dramatic consequences for…

计算与语言 · 计算机科学 2025-06-13 Ivan Vykopal , Matúš Pikuliak , Ivan Srba , Robert Moro , Dominik Macko , Maria Bielikova

Large Language Models (LLMs) are effective at deceiving, when prompted to do so. But under what conditions do they deceive spontaneously? Models that demonstrate better performance on reasoning tasks are also better at prompted deception.…

计算与语言 · 计算机科学 2025-04-02 Samuel M. Taylor , Benjamin K. Bergen

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

Natural language processing based on large language models (LLMs) is a booming field of AI research. After neural networks have proven to outperform humans in games and practical domains based on pattern recognition, we might stand now at a…

计算机与社会 · 计算机科学 2023-03-31 Anna Strasser

Large language models (LLMs) can produce erroneous responses that sound fluent and convincing, raising the risk that users will rely on these responses as if they were correct. Mitigating such overreliance is a key challenge. Through a…

人机交互 · 计算机科学 2025-02-13 Sunnie S. Y. Kim , Jennifer Wortman Vaughan , Q. Vera Liao , Tania Lombrozo , Olga Russakovsky

Large language models (LLMs) are increasingly used in statistical research and applications. However,they are also notorious for unreliable or biased information. Here, we explore whether LLMs can be used to improve the precision of…

应用统计 · 统计学 2026-05-29 Jaylin Lowe , Adam Sales , Johann A. Gagnon-Bartsch

Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4's law evaluation raise questions concerning their performance in real-world legal…

计算与语言 · 计算机科学 2023-10-19 Ruihao Shui , Yixin Cao , Xiang Wang , Tat-Seng Chua

The development of highly fluent large language models (LLMs) has prompted increased interest in assessing their reasoning and problem-solving capabilities. We investigate whether several LLMs can solve a classic type of deductive reasoning…

计算与语言 · 计算机科学 2024-04-16 Spencer M. Seals , Valerie L. Shalin

Large language models (LLMs) enable researchers to analyze text at unprecedented scale and minimal cost. Researchers can now revisit old questions and tackle novel ones with rich data. We provide an econometric framework for realizing this…

计量经济学 · 经济学 2025-12-08 Jens Ludwig , Sendhil Mullainathan , Ashesh Rambachan

The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Nevertheless, LLMs are prone to hallucination, generating…

Large language models (LLMs) can reproduce a wide variety of rhetorical styles and generate text that expresses a broad spectrum of sentiments. This capacity, now available at low cost, makes them powerful tools for manipulation and…

社会与信息网络 · 计算机科学 2024-05-08 Yaqub Chaudhary , Jonnie Penn

Large language models (LLMs) are a promising venue for natural language understanding and generation tasks. However, current LLMs are far from reliable: they are prone to generate non-factual information and, more crucially, to contradict…

机器学习 · 计算机科学 2024-04-22 Diego Calanzone , Stefano Teso , Antonio Vergari

Making legal knowledge accessible to non-experts is crucial for enhancing general legal literacy and encouraging civic participation in democracy. However, legal documents are often challenging to understand for people without legal…

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…

计算与语言 · 计算机科学 2024-07-17 Betty Li Hou , Kejian Shi , Jason Phang , James Aung , Steven Adler , Rosie Campbell

The rapid advancement of large language models (LLMs) has inspired researchers to integrate them extensively into the academic workflow, potentially reshaping how research is practiced and reviewed. While previous studies highlight the…

计算与语言 · 计算机科学 2025-10-15 Rui Li , Jia-Chen Gu , Po-Nien Kung , Heming Xia , Junfeng liu , Xiangwen Kong , Zhifang Sui , Nanyun Peng

Recent advancements in Large Language Models (LLMs), such as ChatGPT and LLaMA, have significantly transformed Natural Language Processing (NLP) with their outstanding abilities in text generation, summarization, and classification.…

计算与语言 · 计算机科学 2024-08-12 Md Nazmus Sakib , Md Athikul Islam , Royal Pathak , Md Mashrur Arifin

The advent of Large Language Models (LLMs) has garnered significant popularity and wielded immense power across various domains within Natural Language Processing (NLP). While their capabilities are undeniably impressive, it is crucial to…

机器学习 · 计算机科学 2024-07-31 Sara Abdali , Jia He , CJ Barberan , Richard Anarfi

Large language models (LLMs) have revolutionized natural language processing, yet their propensity for hallucination, generating plausible but factually incorrect or fabricated content, remains a critical challenge. This report provides a…

计算与语言 · 计算机科学 2025-08-05 Manuel Cossio

Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine translation, and conversational systems. Despite their transformative potential, these models…

密码学与安全 · 计算机科学 2025-08-05 Kang Chen , Xiuze Zhou , Yuanguo Lin , Jinhe Su , Yuanhui Yu , Li Shen , Fan Lin