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相关论文: Ask an Expert: Leveraging Language Models to Impro…

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The answering quality of an aligned large language model (LLM) can be drastically improved if treated with proper crafting of prompts. In this paper, we propose ExpertPrompting to elicit the potential of LLMs to answer as distinguished…

计算与语言 · 计算机科学 2025-03-06 Benfeng Xu , An Yang , Junyang Lin , Quan Wang , Chang Zhou , Yongdong Zhang , Zhendong Mao

Common methods for aligning large language models (LLMs) with desired behaviour heavily rely on human-labelled data. However, as models grow increasingly sophisticated, they will surpass human expertise, and the role of human evaluation…

Large Language Models (LLMs) have shown remarkable performance in various natural language processing tasks but face challenges in mathematical reasoning, where complex problem-solving requires both linguistic understanding and mathematical…

计算与语言 · 计算机科学 2025-03-20 Shuguang Chen , Guang Lin

Understanding the dynamics of counseling conversations is an important task, yet it is a challenging NLP problem regardless of the recent advance of Transformer-based pre-trained language models. This paper proposes a systematic approach to…

计算与语言 · 计算机科学 2024-02-23 Younghun Lee , Dan Goldwasser , Laura Schwab Reese

We present Multi-expert Prompting, a novel enhancement of ExpertPrompting (Xu et al., 2023), designed to improve the large language model (LLM) generation. Specifically, it guides an LLM to fulfill an input instruction by simulating…

计算与语言 · 计算机科学 2024-11-04 Do Xuan Long , Duong Ngoc Yen , Anh Tuan Luu , Kenji Kawaguchi , Min-Yen Kan , Nancy F. Chen

Medical dialogue systems have attracted significant attention for their potential to act as medical assistants. Enabling these medical systems to emulate clinicians' diagnostic reasoning process has been the long-standing research focus.…

计算与语言 · 计算机科学 2024-06-21 Kaishuai Xu , Yi Cheng , Wenjun Hou , Qiaoyu Tan , Wenjie Li

Large language models (LLMs) have demonstrated remarkable performance by following natural language instructions without fine-tuning them on domain-specific tasks and data. However, leveraging LLMs for domain-specific question answering…

Prior research demonstrates that performance of language models on reasoning tasks can be influenced by suggestions, hints and endorsements. However, the influence of endorsement source credibility remains underexplored. We investigate…

计算与语言 · 计算机科学 2026-05-28 Priyanka Mary Mammen , Emil Joswin , Shankar Venkitachalam

Each day, individuals set behavioral goals such as eating healthier, exercising regularly, or increasing productivity. While psychological frameworks (i.e., goal setting and implementation intentions) can be helpful, they often need…

Large language models (LLMs) have emerged as powerful tools in natural language processing (NLP), showing a promising future of artificial generated intelligence (AGI). Despite their notable performance in the general domain, LLMs have…

计算与语言 · 计算机科学 2025-01-23 Jingyuan Chen , Tao Wu , Wei Ji , Fei Wu

This study investigates the design, development, and evaluation of a Large Language Model (LLM)-based chatbot for teaching English conversations in an English as a Foreign Language (EFL) context. Employing the Design and Development…

Large language models (LLMs) have demonstrated remarkable capabilities in language generation, understanding, and few-shot learning in recent years. An extensive body of work has explored how their performance may be further improved…

计算与语言 · 计算机科学 2023-05-24 Yilun Du , Shuang Li , Antonio Torralba , Joshua B. Tenenbaum , Igor Mordatch

Large Language Models (LLMs), such as ChatGPT, have recently been applied to various NLP tasks due to its open-domain generation capabilities. However, there are two issues with applying LLMs to dialogue tasks. 1. During the dialogue…

计算与语言 · 计算机科学 2023-10-06 Siwei Wu , Xiangqing Shen , Rui Xia

Large Language Models (LLMs) are transforming scholarly tasks like search and summarization, but their reliability remains uncertain. Current evaluation metrics for testing LLM reliability are primarily automated approaches that prioritize…

人机交互 · 计算机科学 2026-02-25 Anna Martin-Boyle , William Humphreys , Martha Brown , Cara Leckey , Harmanpreet Kaur

How do we communicate with others to achieve our goals? We use our prior experience or advice from others, or construct a candidate utterance by predicting how it will be received. However, our experiences are limited and biased, and…

人工智能 · 计算机科学 2023-11-06 Ryan Liu , Howard Yen , Raja Marjieh , Thomas L. Griffiths , Ranjay Krishna

The advent of large language models (LLMs) has significantly advanced various fields, including natural language processing and automated dialogue systems. This paper explores the application of LLMs in psychological counseling, addressing…

计算与语言 · 计算机科学 2024-06-21 Wenjie Li , Tianyu Sun , Kun Qian , Wenhong Wang

Large Language Models (LLMs) and chatbots show significant promise in streamlining the legal intake process. This advancement can greatly reduce the workload and costs for legal aid organizations, improving availability while making legal…

计算机与社会 · 计算机科学 2023-11-23 Nick Goodson , Rongfei Lu

We investigate how to teach large language models (LLMs) to perform scientific reasoning by leveraging expert discussions as a learning signal. Focusing on the genomics domain, we develop an automated pipeline to extract trainable data and…

人工智能 · 计算机科学 2025-06-04 Ming Yin , Yuanhao Qu , Ling Yang , Le Cong , Mengdi Wang

With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities…

计算机与社会 · 计算机科学 2024-01-02 Kevin Wang , Jason Ramos , Ramon Lawrence

Large language models (LLMs) are transforming the ways the general public accesses and consumes information. Their influence is particularly pronounced in pivotal sectors like healthcare, where lay individuals are increasingly appropriating…

计算与语言 · 计算机科学 2023-10-24 Yiqiao Jin , Mohit Chandra , Gaurav Verma , Yibo Hu , Munmun De Choudhury , Srijan Kumar
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