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The humanlike responses of large language models (LLMs) have prompted social scientists to investigate whether LLMs can be used to simulate human participants in experiments, opinion polls and surveys. Of central interest in this line of…

计算与语言 · 计算机科学 2024-05-14 Nikolay B Petrov , Gregory Serapio-García , Jason Rentfrow

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have demonstrated significant capabilities across numerous applications. However, the performance of these models in languages with fewer resources, such…

计算与语言 · 计算机科学 2024-05-24 Birger Moell

The integration of emotional support into various conversational scenarios presents profound societal benefits, such as social interactions, mental health counseling, and customer service. However, there are unsolved challenges that hinder…

计算与语言 · 计算机科学 2023-08-23 Zhonghua Zheng , Lizi Liao , Yang Deng , Liqiang Nie

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…

计算与语言 · 计算机科学 2024-04-11 Qusai Khraisha , Sophie Put , Johanna Kappenberg , Azza Warraitch , Kristin Hadfield

Language models have steadily increased in size over the past few years. They achieve a high level of performance on various natural language processing (NLP) tasks such as question answering and summarization. Large language models (LLMs)…

计算与语言 · 计算机科学 2023-01-31 Jessica Huynh , Cathy Jiao , Prakhar Gupta , Shikib Mehri , Payal Bajaj , Vishrav Chaudhary , Maxine Eskenazi

Large vision-language models (LVLMs) have recently witnessed rapid advancements, exhibiting a remarkable capacity for perceiving, understanding, and processing visual information by connecting visual receptor with large language models…

计算机视觉与模式识别 · 计算机科学 2023-09-06 Shuai Bai , Shusheng Yang , Jinze Bai , Peng Wang , Xingxuan Zhang , Junyang Lin , Xinggang Wang , Chang Zhou , Jingren Zhou

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. Recent research has…

计算与语言 · 计算机科学 2024-12-05 Sergio E. Zanotto , Segun Aroyehun

This survey provides a comprehensive review of research on multi-turn dialogue systems, with a particular focus on multi-turn dialogue systems based on large language models (LLMs). This paper aims to (a) give a summary of existing LLMs and…

计算与语言 · 计算机科学 2025-08-18 Zihao Yi , Jiarui Ouyang , Zhe Xu , Yuwen Liu , Tianhao Liao , Haohao Luo , Ying Shen

As Large Language Models (LLMs) are increasingly deployed in customer-facing applications, a critical yet underexplored question is how users communicate differently with LLM chatbots compared to human agent. In this study, we present…

计算与语言 · 计算机科学 2025-10-06 Fulei Zhang , Zhou Yu

We study the limitations of Large Language Models (LLMs) for the task of response generation in human-machine dialogue. Several techniques have been proposed in the literature for different dialogue types (e.g., Open-Domain). However, the…

计算与语言 · 计算机科学 2024-08-06 Simone Alghisi , Massimo Rizzoli , Gabriel Roccabruna , Seyed Mahed Mousavi , Giuseppe Riccardi

To what extent can language alone give rise to complex concepts, or is embodied experience essential? Recent advancements in large language models (LLMs) offer fresh perspectives on this question. Although LLMs are trained on restricted…

计算与语言 · 计算机科学 2023-12-04 Qihui Xu , Yingying Peng , Samuel A. Nastase , Martin Chodorow , Minghua Wu , Ping Li

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,…

计算与语言 · 计算机科学 2023-10-10 Thilo Hagendorff , Sarah Fabi

The emergence of Large Language Models (LLMs) has great potential to reshape the landscape of many social media platforms. While this can bring promising opportunities, it also raises many threats, such as biases and privacy concerns, and…

人机交互 · 计算机科学 2024-02-14 Kristina Radivojevic , Nicholas Clark , Paul Brenner

Deploying Large Language Models (LLMs) for question answering (QA) over lengthy contexts is a significant challenge. In industrial settings, this process is often hindered by high computational costs and latency, especially when multiple…

计算与语言 · 计算机科学 2025-09-29 Xiliang Zhu , Shi Zong , David Rossouw

Numerous methods have been proposed to detect, estimate, and analyze properties of people in images, including 3D pose, shape, contact, human-object interaction, and emotion. While widely applicable in vision and other areas, such methods…

计算机视觉与模式识别 · 计算机科学 2025-05-30 Jing Lin , Yao Feng , Weiyang Liu , Michael J. Black

People increasingly hold sustained, open-ended conversations with large language models (LLMs). Public reports and early studies suggest that, in such settings, models can reinforce delusional or conspiratorial ideation or even amplify…

人机交互 · 计算机科学 2026-04-09 Peter Kirgis , Ben Hawriluk , Sherrie Feng , Aslan Bilimer , Sam Paech , Zeynep Tufekci

In this technical report, we present TeleChat, a collection of large language models (LLMs) with parameters of 3 billion, 7 billion and 12 billion. It includes pretrained language models as well as fine-tuned chat models that is aligned…

This paper studies recent developments in large language models' (LLM) abilities to pass assessments in introductory and intermediate Python programming courses at the postsecondary level. The emergence of ChatGPT resulted in heated debates…

计算机与社会 · 计算机科学 2023-10-05 Jaromir Savelka , Arav Agarwal , Marshall An , Chris Bogart , Majd Sakr

The introduction of ChatGPT has garnered widespread attention in both academic and industrial communities. ChatGPT is able to respond effectively to a wide range of human questions, providing fluent and comprehensive answers that…

计算与语言 · 计算机科学 2023-01-19 Biyang Guo , Xin Zhang , Ziyuan Wang , Minqi Jiang , Jinran Nie , Yuxuan Ding , Jianwei Yue , Yupeng Wu

There is much excitement about the opportunity to harness the power of large language models (LLMs) when building problem-solving assistants. However, the standard methodology of evaluating LLMs relies on static pairs of inputs and outputs,…