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The rapid advancement of Large Language Models (LLMs) has revolutionized various sectors by automating routine tasks, marking a step toward the realization of Artificial General Intelligence (AGI). However, they still struggle to…

机器学习 · 计算机科学 2024-02-21 Zihao Tang , Zheqi Lv , Shengyu Zhang , Fei Wu , Kun Kuang

We introduce AgreeMate, a framework for training Large Language Models (LLMs) to perform strategic price negotiations through natural language. We apply recent advances to a negotiation setting where two agents (i.e. buyer or seller) use…

计算与语言 · 计算机科学 2024-12-30 Ainesh Chatterjee , Samuel Miller , Nithin Parepally

In the same way that generative models today conduct most of their training in a self-supervised fashion, how can agentic models conduct their training in a self-supervised fashion, interactively exploring, learning, and preparing to…

机器学习 · 计算机科学 2025-10-21 Kathryn Wantlin , Chongyi Zheng , Benjamin Eysenbach

AI and generative AI tools, including chatbots like ChatGPT that rely on large language models (LLMs), have burst onto the scene this year, creating incredible opportunities to increase work productivity and improve our lives. Statisticians…

计算与语言 · 计算机科学 2024-03-27 Mark Glickman , Yi Zhang

AI2T is an interactively teachable AI for authoring intelligent tutoring systems (ITSs). Authors tutor AI2T by providing a few step-by-step solutions and then grading AI2T's own problem-solving attempts. From just 20-30 minutes of…

人机交互 · 计算机科学 2024-11-28 Daniel Weitekamp , Erik Harpstead , Kenneth Koedinger

Large Action Models (LAMs) for AI Agents offer incredible potential but face challenges due to the need for high-quality training data, especially for multi-steps tasks that involve planning, executing tool calls, and responding to…

Artificial General Intelligence falls short when communicating role specific nuances to other systems. This is more pronounced when building autonomous LLM agents capable and designed to communicate with each other for real world problem…

机器学习 · 计算机科学 2024-03-19 Rabimba Karanjai , Weidong Shi

Augmenting large language models (LLMs) with external tools has emerged as a promising approach to solving complex problems. However, traditional methods, which finetune LLMs with tool demonstration data, can be both costly and restricted…

计算与语言 · 计算机科学 2024-01-17 Shibo Hao , Tianyang Liu , Zhen Wang , Zhiting Hu

Prompt-based learning has been demonstrated as a compelling paradigm contributing to large language models' tremendous success (LLMs). Inspired by their success in language tasks, existing research has leveraged LLMs in embodied instruction…

Large Language Models (LLMs) have become increasingly integral to enhancing developer productivity, particularly in code generation, comprehension, and repair tasks. However, fine-tuning these models with high-quality, real-world data is…

软件工程 · 计算机科学 2024-12-12 Xiaoyun Liang , Jingyi Ren , Jiayi Qi , Chao Peng , Bo Jiang

While Large Language Models (LLMs) are being quickly adapted to many domains, including healthcare, their strengths and pitfalls remain under-explored. In our study, we examine the effects of prompt engineering to guide Large Language…

计算与语言 · 计算机科学 2024-09-04 Daniil Filienko , Yinzhou Wang , Caroline El Jazmi , Serena Xie , Trevor Cohen , Martine De Cock , Weichao Yuwen

In virtual reality (VR) educational scenarios, Pedagogical agents (PAs) enhance immersive learning through realistic appearances and interactive behaviors. However, most existing PAs rely on static speech and simple gestures. This…

人机交互 · 计算机科学 2026-03-11 Ninghao Wan , Jiarun Song , Fuzheng Yang

Large Language Models (LLMs) now excel at generative skills and can create content at impeccable speeds. However, they are imperfect and still make various mistakes. In a Computer Science education context, as these models are widely…

人机交互 · 计算机科学 2024-10-11 Qianou Ma , Hua Shen , Kenneth Koedinger , Tongshuang Wu

The recent advancements introduced by Large Language Models (LLMs) have transformed how Artificial Intelligence (AI) can support complex, real world tasks, pushing research outside the text boundaries towards multi modal contexts and…

计算机视觉与模式识别 · 计算机科学 2026-03-25 Federico Toschi , Nicolò Brunello , Andrea Sassella , Vincenzo Scotti , Mark James Carman

Large language models (LLMs) have been used to generate formal proofs of mathematical theorems in proofs assistants such as Lean. However, we often want to optimize a formal proof with respect to various criteria, depending on its…

人工智能 · 计算机科学 2026-05-22 Riyaz Ahuja , Jeremy Avigad , Prasad Tetali , Sean Welleck

Prompt optimization aims to find the best prompt to a large language model (LLM) for a given task. LLMs have been successfully used to help find and improve prompt candidates for single-step tasks. However, realistic tasks for agents are…

计算与语言 · 计算机科学 2024-10-04 Yongchao Chen , Jacob Arkin , Yilun Hao , Yang Zhang , Nicholas Roy , Chuchu Fan

As AI systems increasingly become embedded in interactive and im-mersive artistic environments, artists and technologists are discovering new opportunities to engage with their interpretive and autonomous capacities as creative…

人机交互 · 计算机科学 2026-02-09 Pavlos Panagiotidis , Jocelyn Spence , Nils Jaeger , Paul Tennent

This paper assesses the potential for large language models (LLMs) to serve as assistive tools in the creative writing process, by means of a single, in-depth case study. In the course of the study, we develop interactive and multi-voice…

计算与语言 · 计算机科学 2023-12-08 Murray Shanahan , Catherine Clarke

Psychological consultation is essential for improving mental health and well-being, yet challenges such as the shortage of qualified professionals and scalability issues limit its accessibility. To address these challenges, we explore the…

计算与语言 · 计算机科学 2024-08-30 Rafael Souza , Jia-Hao Lim , Alexander Davis

With recent advancements in natural language processing, Large Language Models (LLMs) have emerged as powerful tools for various real-world applications. Despite their prowess, the intrinsic generative abilities of LLMs may prove…

人工智能 · 计算机科学 2025-12-30 Jingqing Ruan , Yihong Chen , Bin Zhang , Zhiwei Xu , Tianpeng Bao , Guoqing Du , Shiwei Shi , Hangyu Mao , Ziyue Li , Xingyu Zeng , Rui Zhao