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Large Language Models (LLMs) have exhibited impressive generation capabilities, but they suffer from hallucinations when solely relying on their internal knowledge, especially when answering questions that require less commonly known…

计算与语言 · 计算机科学 2023-11-01 Wenting Zhao , Ye Liu , Tong Niu , Yao Wan , Philip S. Yu , Shafiq Joty , Yingbo Zhou , Semih Yavuz

Large language models (LLMs) are powerful dialogue agents, but specializing them towards fulfilling a specific function can be challenging. Instructing tuning, i.e. tuning models on instruction and sample responses generated by humans…

计算与语言 · 计算机科学 2024-01-11 Dennis Ulmer , Elman Mansimov , Kaixiang Lin , Justin Sun , Xibin Gao , Yi Zhang

The advent of Large Language Models (LLMs) has revolutionized language understanding and human-like text generation, drawing interest from many other fields with this question in mind: What else are the LLMs capable of? Despite their…

人工智能 · 计算机科学 2024-10-24 Nurullah Sevim , Mostafa Ibrahim , Sabit Ekin

Current Large Language Models (LLMs) face inherent limitations due to their pre-defined context lengths, which impede their capacity for multi-hop reasoning within extensive textual contexts. While existing techniques like…

计算与语言 · 计算机科学 2024-06-19 Weizhi Fei , Xueyan Niu , Guoqing Xie , Yanhua Zhang , Bo Bai , Lei Deng , Wei Han

The advent of Large Language Models (LLMs) has revolutionized various domains of artificial intelligence, including the realm of software engineering. In this research, we evaluate the efficacy of pre-trained LLMs in replicating the tasks…

软件工程 · 计算机科学 2024-06-10 Tajmilur Rahman , Rahul Singh , Mir Yousuf Sultan

In modern dialogue systems, the use of Large Language Models (LLMs) has grown exponentially due to their capacity to generate diverse, relevant, and creative responses. Despite their strengths, striking a balance between the LLMs'…

计算与语言 · 计算机科学 2023-08-01 Chen Zhang

To enhance the quality of generated stories, recent story generation models have been investigating the utilization of higher-level attributes like plots or commonsense knowledge. The application of prompt-based learning with large language…

计算与语言 · 计算机科学 2023-07-25 Zhuohan Xie , Trevor Cohn , Jey Han Lau

In this paper, we explore the potential of Large Language Models (LLMs) with assertions to mitigate imbalances in educational datasets. Traditional models often fall short in such contexts, particularly due to the complexity and nuanced…

计算机与社会 · 计算机科学 2024-07-03 Jeanne McClure , Machi Shimmei , Noboru Matsuda , Shiyan Jiang

Large Language Models (LLMs) can generate content that is as persuasive as human-written text and appear capable of selectively producing deceptive outputs. These capabilities raise concerns about potential misuse and unintended…

计算与语言 · 计算机科学 2024-12-24 Cameron R. Jones , Benjamin K. Bergen

Large language models (LLMs) have emerged as versatile tools in various daily applications. However, they are fraught with issues that undermine their utility and trustworthiness. These include the incorporation of erroneous references…

计算与语言 · 计算机科学 2023-09-13 Dongyub Lee , Taesun Whang , Chanhee Lee , Heuiseok Lim

As large language models (LLMs) increasingly permeate daily lives, there is a growing demand for real-time interactions that mirror human conversations. Traditional turn-based chat systems driven by LLMs prevent users from verbally…

计算与语言 · 计算机科学 2026-01-14 Xinrong Zhang , Yingfa Chen , Shengding Hu , Xu Han , Zihang Xu , Yuanwei Xu , Weilin Zhao , Maosong Sun , Zhiyuan Liu

Educational interventions are effective tools for enhancing student learning. While Large Language Models (LLMs) allow for generating adaptive feedback at scale, current studies lack clear methodologies for providing Just-in-Time (JiT)…

计算与语言 · 计算机科学 2026-05-27 Younghun Lee , Amir Bralin , Nobel Sanjay Rebello , Dan Goldwasser

Large language models (LLMs) are proficient at generating fluent text with minimal task-specific supervision. Yet, their ability to provide well-grounded rationalizations for knowledge-intensive tasks remains under-explored. Such tasks,…

计算与语言 · 计算机科学 2024-02-02 Aditi Mishra , Sajjadur Rahman , Hannah Kim , Kushan Mitra , Estevam Hruschka

The capabilities of large language models (LLMs) have raised concerns about their potential to create and propagate convincing narratives. Here, we study their performance in detecting convincing arguments to gain insights into LLMs'…

计算与语言 · 计算机科学 2024-10-07 Paula Rescala , Manoel Horta Ribeiro , Tiancheng Hu , Robert West

Large Language Models (LLMs) have demonstrated amazing capabilities in language generation, text comprehension, and knowledge reasoning. While a single powerful model can already handle multiple tasks, relying on a single perspective can…

计算与语言 · 计算机科学 2024-06-12 Zining Qin , Chenhao Wang , Huiling Qin , Weijia Jia

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

人机交互 · 计算机科学 2024-04-10 M. Namvarpour , A. Razi

Large language models (LLMs) exhibit remarkable performance across various NLP tasks. However, they often generate incorrect or hallucinated information, which hinders their practical applicability in real-world scenarios. Human feedback…

计算与语言 · 计算机科学 2023-05-24 Wenhao Yu , Zhihan Zhang , Zhenwen Liang , Meng Jiang , Ashish Sabharwal

The task of cultivating healthy communication in online communities becomes increasingly urgent, as gaming and social media experiences become progressively more immersive and life-like. We approach the challenge of moderating online…

计算机与社会 · 计算机科学 2023-06-09 Henrik Axelsen , Johannes Rude Jensen , Sebastian Axelsen , Valdemar Licht , Omri Ross

Large language models (LLMs) are increasingly seen as assistants, copilots, and consultants, capable of supporting a wide range of tasks through natural conversation. However, most systems remain constrained by a linear request-response…

计算与语言 · 计算机科学 2026-05-05 Jiaqi Chen , Yanzhe Zhang , Yutong Zhang , Yijia Shao , Diyi Yang

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the…

计算与语言 · 计算机科学 2024-04-12 Linyi Yang , Shuibai Zhang , Zhuohao Yu , Guangsheng Bao , Yidong Wang , Jindong Wang , Ruochen Xu , Wei Ye , Xing Xie , Weizhu Chen , Yue Zhang