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Large Language Models (LLMs) have emerged as a powerful tool in advancing the Text-to-SQL task, significantly outperforming traditional methods.Nevertheless, as a nascent research field, there is still no consensus on the optimal prompt…

Computation and Language · Computer Science 2026-03-20 Bin Zhang , Yuxiao Ye , Guoqing Du , Xiaoru Hu , Zhishuai Li , Chi Harold Liu , Zhiwei Xu , Guoliang Fan , Rui Zhao , Ziyue Li , Hangyu Mao

While significant progress has been made in automating various aspects of software development through coding agents, there is still significant room for improvement in their bug fixing capabilities. Debugging and investigation of runtime…

Software Engineering · Computer Science 2026-04-22 Spandan Garg , Yufan Huang

The rise of Large Language Models (LLMs) has affected various disciplines that got beyond mere text generation. Going beyond their textual nature, this project proposal aims to investigate the interaction between LLMs and non-verbal…

Computation and Language · Computer Science 2024-02-01 Philipp Wicke

This paper introduces a novel approach to creating adaptive language agents by integrating active inference with large language models (LLMs). While LLMs demonstrate remarkable capabilities, their reliance on static prompts limits…

Computation and Language · Computer Science 2025-01-13 Rithvik Prakki

Large language models (LLMs) have been increasingly applied to tasks in language understanding and interactive decision-making, with their impressive performance largely attributed to the extensive domain knowledge embedded within them.…

Artificial Intelligence · Computer Science 2024-10-16 Zhiyuan Sun , Haochen Shi , Marc-Alexandre Côté , Glen Berseth , Xingdi Yuan , Bang Liu

Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are featured in their self-evolving capability, which is the basis for…

Artificial Intelligence · Computer Science 2024-04-23 Zeyu Zhang , Xiaohe Bo , Chen Ma , Rui Li , Xu Chen , Quanyu Dai , Jieming Zhu , Zhenhua Dong , Ji-Rong Wen

Medical Decision-Making (MDM) is a multi-faceted process that requires clinicians to assess complex multi-modal patient data patient, often collaboratively. Large Language Models (LLMs) promise to streamline this process by synthesizing…

GUIs have long been central to human-computer interaction, providing an intuitive and visually-driven way to access and interact with digital systems. The advent of LLMs, particularly multimodal models, has ushered in a new era of GUI…

Artificial Intelligence · Computer Science 2025-05-07 Chaoyun Zhang , Shilin He , Jiaxu Qian , Bowen Li , Liqun Li , Si Qin , Yu Kang , Minghua Ma , Guyue Liu , Qingwei Lin , Saravan Rajmohan , Dongmei Zhang , Qi Zhang

Large Language Models (LLMs) are nowadays expected to generate content aligned with human preferences. Current work focuses on alignment at model training time, through techniques such as Reinforcement Learning with Human Feedback (RLHF).…

Artificial Intelligence · Computer Science 2026-01-21 James Y. Huang , Sailik Sengupta , Daniele Bonadiman , Yi-An Lai , Arshit Gupta , Nikolaos Pappas , Saab Mansour , Katrin Kirchhoff , Dan Roth

Simulating learner actions helps stress-test open-ended interactive learning environments and prototype new adaptations before deployment. While recent studies show the promise of using large language models (LLMs) for simulating human…

Artificial Intelligence · Computer Science 2024-10-15 Amogh Mannekote , Adam Davies , Jina Kang , Kristy Elizabeth Boyer

Large Language Models (LLMs) are transforming artificial intelligence, enabling autonomous agents to perform diverse tasks across various domains. These agents, proficient in human-like text comprehension and generation, have the potential…

Artificial Intelligence · Computer Science 2024-04-10 Saikat Barua

Large Language Model (LLM) agents, capable of performing a broad range of actions, such as invoking tools and controlling robots, show great potential in tackling real-world challenges. LLM agents are typically prompted to produce actions…

Computation and Language · Computer Science 2024-06-10 Xingyao Wang , Yangyi Chen , Lifan Yuan , Yizhe Zhang , Yunzhu Li , Hao Peng , Heng Ji

Software code generation using Large Language Models (LLMs) is one of the most successful applications of modern artificial intelligence. Foundational models are very effective for popular frameworks that benefit from documentation,…

Software Engineering · Computer Science 2025-10-01 Dmitriy Kostunin , Vladimir Sotnikov , Sergo Golovachev , Abhay Mehta , Tim Lukas Holch , Elisa Jones

Large Language Models(LLMs) have dramatically revolutionized the field of Natural Language Processing(NLP), offering remarkable capabilities that have garnered widespread usage. However, existing interaction paradigms between LLMs and users…

Computation and Language · Computer Science 2024-03-11 Juhao Liang , Ziwei Wang , Zhuoheng Ma , Jianquan Li , Zhiyi Zhang , Xiangbo Wu , Benyou Wang

As Large Language Models (LLMs) become increasingly integrated into our daily lives, the potential harms from deceptive behavior underlie the need for faithfully interpreting their decision-making. While traditional probing methods have…

Machine Learning · Computer Science 2024-11-08 Anthony Costarelli , Mat Allen , Severin Field

Recent advancements in large language models (LLMs) have brought significant changes to various domains, especially through LLM-driven autonomous agents. A representative scenario is in software development, where LLM agents demonstrate…

Computation and Language · Computer Science 2024-06-06 Chen Qian , Yufan Dang , Jiahao Li , Wei Liu , Zihao Xie , Yifei Wang , Weize Chen , Cheng Yang , Xin Cong , Xiaoyin Che , Zhiyuan Liu , Maosong Sun

Large Language Models (LLMs) and Reinforcement Learning (RL) are two powerful approaches for building autonomous agents. However, due to limited understanding of the game environment, agents often resort to inefficient exploration and…

Machine Learning · Computer Science 2024-11-26 Ziyu Chen , Zhiqing Xiao , Xinbei Jiang , Junbo Zhao

Large language models (LLMs) have significantly advanced in various fields and intelligent agent applications. However, current LLMs that learn from human or external model supervision are costly and may face performance ceilings as task…

Computation and Language · Computer Science 2024-06-04 Zhengwei Tao , Ting-En Lin , Xiancai Chen , Hangyu Li , Yuchuan Wu , Yongbin Li , Zhi Jin , Fei Huang , Dacheng Tao , Jingren Zhou

Large Language Models (LLMs) have emerged as integral tools for reasoning, planning, and decision-making, drawing upon their extensive world knowledge and proficiency in language-related tasks. LLMs thus hold tremendous potential for…

Artificial Intelligence · Computer Science 2024-05-24 Xudong Guo , Kaixuan Huang , Jiale Liu , Wenhui Fan , Natalia Vélez , Qingyun Wu , Huazheng Wang , Thomas L. Griffiths , Mengdi Wang

Providing students with flexible and timely academic support is a challenge at most colleges and universities, leaving many students without help outside scheduled hours. Large language models (LLMs) are promising for bridging this gap, but…

Computers and Society · Computer Science 2025-09-12 Chang Liu , Loc Hoang , Andrew Stolman , Rene F. Kizilcec , Bo Wu
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