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Large Language Models (LLMs) have demonstrated remarkable abilities across numerous disciplines, primarily assessed through tasks in language generation, knowledge utilization, and complex reasoning. However, their alignment with human…

人工智能 · 计算机科学 2023-07-31 Xuena Wang , Xueting Li , Zi Yin , Yue Wu , Liu Jia

For Large Language Models (LLMs), a disconnect persists between benchmark performance and real-world utility. Current evaluation frameworks remain fragmented, prioritizing technical metrics while neglecting holistic assessment for…

人工智能 · 计算机科学 2025-11-19 Jun Wang , Ninglun Gu , Kailai Zhang , Zijiao Zhang , Yelun Bao , Jin Yang , Xu Yin , Liwei Liu , Yihuan Liu , Pengyong Li , Gary G. Yen , Junchi Yan

Large Language Models (LLMs) offer the potential for automatic time series analysis and reporting, which is a critical task across many domains, spanning healthcare, finance, climate, energy, and many more. In this paper, we propose a…

计算与语言 · 计算机科学 2024-10-10 Elizabeth Fons , Rachneet Kaur , Soham Palande , Zhen Zeng , Tucker Balch , Manuela Veloso , Svitlana Vyetrenko

The effective assessment of the instruction-following ability of large language models (LLMs) is of paramount importance. A model that cannot adhere to human instructions might be not able to provide reliable and helpful responses. In…

计算与语言 · 计算机科学 2023-11-17 Yimin Jing , Renren Jin , Jiahao Hu , Huishi Qiu , Xiaohua Wang , Peng Wang , Deyi Xiong

The growing interest in employing large language models (LLMs) for decision-making in social and economic contexts has raised questions about their potential to function as agents in these domains. A significant number of societal problems…

计算机科学与博弈论 · 计算机科学 2025-11-25 Hadi Hosseini , Samarth Khanna

Large Language Models (LLMs) have lately been on the spotlight of researchers, businesses, and consumers alike. While the linguistic capabilities of such models have been studied extensively, there is growing interest in investigating them…

计算与语言 · 计算机科学 2023-08-17 Sotiris Lamprinidis

Relevance judgments are crucial for evaluating information retrieval systems, but traditional human-annotated labels are time-consuming and expensive. As a result, many researchers turn to automatic alternatives to accelerate method…

信息检索 · 计算机科学 2025-07-15 Naghmeh Farzi , Laura Dietz

Predictive analysis is a cornerstone of modern decision-making, with applications in various domains. Large Language Models (LLMs) have emerged as powerful tools in enabling nuanced, knowledge-intensive conversations, thus aiding in complex…

计算与语言 · 计算机科学 2025-05-26 Qin Chen , Yuanyi Ren , Xiaojun Ma , Yuyang Shi

Large language models (LLMs) have emerged as powerful tools for simulating complex social phenomena using human-like agents with specific traits. In human societies, value similarity is important for building trust and close relationships;…

计算与语言 · 计算机科学 2025-11-26 Yuki Sakamoto , Takahisa Uchida , Hiroshi Ishiguro

Recent studies evaluate the value orientation of large language models (LLMs) using adapted social surveys, typically by prompting models with survey questions and comparing their responses to average human responses. This paper identifies…

计算与语言 · 计算机科学 2026-02-05 Jindřich Libovický

Human relevance assessment is time-consuming and cognitively intensive, limiting the scalability of Information Retrieval evaluation. This has led to growing interest in using large language models (LLMs) as proxies for human judges.…

信息检索 · 计算机科学 2026-04-28 Chuting Yu , Hang Li , Guido Zuccon , Joel Mackenzie , Teerapong Leelanupab

Using Large Language Models (LLMs) for relevance assessments offers promising opportunities to improve Information Retrieval (IR), Natural Language Processing (NLP), and related fields. Indeed, LLMs hold the promise of allowing IR…

With the recent undeniable advancement in reasoning abilities in large language models (LLMs) like ChatGPT and GPT-4, there is a growing trend for using LLMs on various tasks. One area where LLMs can be employed is as an alternative…

计算与语言 · 计算机科学 2023-10-23 Chenhui Shen , Liying Cheng , Xuan-Phi Nguyen , Yang You , Lidong Bing

The paper underscores the significance of Large Language Models (LLMs) in reshaping recommender systems, attributing their value to unique reasoning abilities absent in traditional recommenders. Unlike conventional systems lacking direct…

信息检索 · 计算机科学 2024-03-20 Arpita Vats , Vinija Jain , Rahul Raja , Aman Chadha

Large Language Models (LLMs) aim to serve as versatile assistants aligned with human values, as defined by the principles of being helpful, honest, and harmless (hhh). However, in terms of Multimodal Large Language Models (MLLMs), despite…

计算机视觉与模式识别 · 计算机科学 2024-03-27 Zhelun Shi , Zhipin Wang , Hongxing Fan , Zaibin Zhang , Lijun Li , Yongting Zhang , Zhenfei Yin , Lu Sheng , Yu Qiao , Jing Shao

LLMs (Large Language Models) are increasingly used in text processing pipelines to intelligently respond to a variety of inputs and generation tasks. This raises the possibility of replacing human roles that bottleneck existing information…

计算与语言 · 计算机科学 2025-12-18 Kester Clegg , Richard Hawkins , Ibrahim Habli , Tom Lawton

In this paper, we initiate our discussion by demonstrating how Large Language Models (LLMs), when tasked with responding to queries, display a more even probability distribution in their answers if they are more adept, as opposed to their…

计算与语言 · 计算机科学 2024-07-10 Tingyu Xia , Bowen Yu , Yuan Wu , Yi Chang , Chang Zhou

Mathematical reasoning serves as a cornerstone for assessing the fundamental cognitive capabilities of human intelligence. In recent times, there has been a notable surge in the development of Large Language Models (LLMs) geared towards the…

计算与语言 · 计算机科学 2024-09-18 Janice Ahn , Rishu Verma , Renze Lou , Di Liu , Rui Zhang , Wenpeng Yin

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

In the rapidly evolving domain of Natural Language Generation (NLG) evaluation, introducing Large Language Models (LLMs) has opened new avenues for assessing generated content quality, e.g., coherence, creativity, and context relevance.…

计算与语言 · 计算机科学 2024-06-13 Zhen Li , Xiaohan Xu , Tao Shen , Can Xu , Jia-Chen Gu , Yuxuan Lai , Chongyang Tao , Shuai Ma