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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

The future of autonomous vehicles lies in the convergence of human-centric design and advanced AI capabilities. Autonomous vehicles of the future will not only transport passengers but also interact and adapt to their desires, making the…

人机交互 · 计算机科学 2023-09-20 Can Cui , Yunsheng Ma , Xu Cao , Wenqian Ye , Ziran Wang

Empathetic dialogue is an indispensable part of building harmonious social relationships and contributes to the development of a helpful AI. Previous approaches are mainly based on fine small-scale language models. With the advent of…

计算与语言 · 计算机科学 2024-07-29 Yushan Qian , Wei-Nan Zhang , Ting Liu

Large Language Models (LLMs), often show strong performance on English tasks, while exhibiting limitations on other languages. What is an LLM's multilingual capability when it is trained only on certain languages? The underlying mechanism…

计算与语言 · 计算机科学 2024-06-04 Fei Yuan , Shuai Yuan , Zhiyong Wu , Lei Li

The development of large language models (LLMs) has brought unprecedented possibilities for artificial intelligence (AI) based medical diagnosis. However, the application perspective of LLMs in real diagnostic scenarios is still unclear…

计算与语言 · 计算机科学 2024-05-21 Zhoujian Sun , Cheng Luo , Ziyi Liu , Zhengxing Huang

The potential of large language models (LLMs) as decision support tools is increasingly being explored in fields such as business, engineering, and medicine, which often face challenging tasks of decision-making under uncertainty. In this…

人工智能 · 计算机科学 2024-10-14 Ollie Liu , Deqing Fu , Dani Yogatama , Willie Neiswanger

Large language models (LLMs) have shown impressive capabilities across a wide range of language tasks. However, their reasoning process is primarily guided by statistical patterns in training data, which limits their ability to handle novel…

人工智能 · 计算机科学 2025-08-21 Hong Su

Large language models (LLMs) have made significant advancements in natural language processing and are concurrently extending the language ability to other modalities, such as speech and vision. Nevertheless, most of the previous work…

计算与语言 · 计算机科学 2024-01-02 Hongkun Hao , Long Zhou , Shujie Liu , Jinyu Li , Shujie Hu , Rui Wang , Furu Wei

The era of Large Language Models (LLMs) presents a new opportunity for interpretability--agentic interpretability: a multi-turn conversation with an LLM wherein the LLM proactively assists human understanding by developing and leveraging a…

人工智能 · 计算机科学 2025-06-17 Been Kim , John Hewitt , Neel Nanda , Noah Fiedel , Oyvind Tafjord

Conversational Assistants (CA) are increasingly supporting human workers in knowledge management. Traditionally, CAs respond in specific ways to predefined user intents and conversation patterns. However, this rigidness does not handle the…

人机交互 · 计算机科学 2024-07-15 Samuel Kernan Freire , Chaofan Wang , Evangelos Niforatos

Online education platforms, leveraging the internet to distribute education resources, seek to provide convenient education but often fall short in real-time communication with students. They often struggle to address the diverse obstacles…

人工智能 · 计算机科学 2024-04-29 Qingyao Li , Lingyue Fu , Weiming Zhang , Xianyu Chen , Jingwei Yu , Wei Xia , Weinan Zhang , Ruiming Tang , Yong Yu

Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions. However, the development of LLMs has been primarily focused on high-resource languages, such as English,…

A Conversational Recommender System (CRS) offers increased transparency and control to users by enabling them to engage with the system through a real-time multi-turn dialogue. Recently, Large Language Models (LLMs) have exhibited an…

This paper explores an intriguing observation: fine-tuning a large language model (LLM) with responses generated by a LLM often yields better results than using responses generated by humans, particularly in reasoning tasks. We conduct an…

计算与语言 · 计算机科学 2025-12-09 Xuan Ren , Biao Wu , Lingqiao Liu

Digital technologies have long been explored as a complement to standard procedure in mental health research and practice, ranging from the management of electronic health records to app-based interventions. The recent emergence of large…

Large language models (LLMs) are very performant connectionist systems, but do they exhibit more compositionality? More importantly, is that part of why they perform so well? We present empirical analyses across four LLM families (12…

计算与语言 · 计算机科学 2025-05-21 Ruchira Dhar , Anders Søgaard

Recent advancements in large language models (LLMs) have spurred interest in expanding their application beyond text-based tasks. A large number of studies have explored integrating other modalities with LLMs, notably speech modality, which…

计算与语言 · 计算机科学 2025-09-10 Zhengdong Yang , Shuichiro Shimizu , Yahan Yu , Chenhui Chu

Current Large Language Models (LLMs) are predominantly designed with English as the primary language, and even the few that are multilingual tend to exhibit strong English-centric biases. Much like speakers who might produce awkward…

计算与语言 · 计算机科学 2025-07-29 Yanzhu Guo , Simone Conia , Zelin Zhou , Min Li , Saloni Potdar , Henry Xiao

Large Language Model (LLM) has gained popularity and achieved remarkable results in open-domain tasks, but its performance in real industrial domain-specific scenarios is average due to its lack of specific domain knowledge. This issue has…

计算与语言 · 计算机科学 2023-10-17 Fangkai Yang , Pu Zhao , Zezhong Wang , Lu Wang , Jue Zhang , Mohit Garg , Qingwei Lin , Saravan Rajmohan , Dongmei Zhang

The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive content generation at an unprecedented scale. In this paper, we…

计算与语言 · 计算机科学 2026-04-22 Sander Noels , Alexander Rogiers , Maarten Buyl , Tijl De Bie