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Large Language Models (LLMs) are transforming healthcare through the development of LLM-based agents that can understand, reason about, and assist with medical tasks. This survey provides a comprehensive review of LLM-based agents in…

计算与语言 · 计算机科学 2025-05-27 Wenxuan Wang , Zizhan Ma , Zheng Wang , Chenghan Wu , Jiaming Ji , Wenting Chen , Xiang Li , Yixuan Yuan

Role-playing games (RPG) are games in which players interact with one another to create narratives. The role of players in the RPG is largely based on the interaction between players and their characters. This emerging form of shared…

计算与语言 · 计算机科学 2025-03-27 Alessandro Maisto

As large language models (LLMs) continue to make significant strides, their better integration into agent-based simulations offers a transformational potential for understanding complex social systems. However, such integration is not…

物理与社会 · 物理学 2024-05-14 Onder Gurcan

Optimizing numerical systems and mechanism design is crucial for enhancing player experience in Massively Multiplayer Online (MMO) games. Traditional optimization approaches rely on large-scale online experiments or parameter tuning over…

人工智能 · 计算机科学 2025-12-03 Ran Zhang , Kun Ouyang , Tiancheng Ma , Yida Yang , Dong Fang

Mental health challenges are rising globally, while traditional support services face limited availability and high costs. Large language models offer potential for conversational support, but often lack personalization, empathy, and…

人机交互 · 计算机科学 2026-04-24 Truong Le Minh Toan , Dieu Bang Mach , Tan Duy Le , Nguyen Tan Viet Tuyen

We evaluate the ability of the current generation of large language models (LLMs) to help a decision-making agent facing an exploration-exploitation tradeoff. While previous work has largely study the ability of LLMs to solve combined…

机器学习 · 计算机科学 2026-02-18 Keegan Harris , Aleksandrs Slivkins

Recent studies show that LLMs possess different skills and specialize in different tasks. In fact, we observe that their varied performance occur in several levels of granularity. For example, in the code optimization task, code LLMs excel…

人工智能 · 计算机科学 2025-10-24 Yuanzhe Liu , Ryan Deng , Tim Kaler , Xuhao Chen , Charles E. Leiserson , Yao Ma , Jie Chen

Language model (LM)-based agents have demonstrated promising capabilities in automating complex tasks from natural language instructions, yet they continue to struggle with long-horizon planning and reasoning. To address this, we propose an…

人工智能 · 计算机科学 2026-05-05 Wenyi Wu , Sibo Zhu , Kun Zhou , Biwei Huang

Large language models (LLMs) are effective at answering questions that are clearly asked. However, when faced with ambiguous queries they can act unpredictably and produce incorrect outputs. This underscores the need for the development of…

计算与语言 · 计算机科学 2024-02-22 Yizhe Zhang , Jiarui Lu , Navdeep Jaitly

Large Language Models (LLMs) can be deployed in situations where they process positive/negative interactions with other agents. We study how this is done under the sociological framework of social balance, which explains the emergence of…

计算与语言 · 计算机科学 2026-01-07 Pedro Cisneros-Velarde

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are artificial entities that sense their environment,…

Large Language Models (LLMs) are becoming ubiquitous to create intelligent virtual assistants that assist users in interacting with a system, as exemplified in marketing. Although LLMs have been discussed in Modeling & Simulation (M&S), the…

人机交互 · 计算机科学 2024-09-25 Philippe J. Giabbanelli , Jose J. Padilla , Ameeta Agrawal

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…

人工智能 · 计算机科学 2024-04-23 Zeyu Zhang , Xiaohe Bo , Chen Ma , Rui Li , Xu Chen , Quanyu Dai , Jieming Zhu , Zhenhua Dong , Ji-Rong Wen

Large language models (LLMs) are increasingly used to provide instructions to many agents who interact with one another. Such shared reliance couples agents who appear to act independently: they may in fact be guided by a common model. This…

计算机科学与博弈论 · 计算机科学 2026-05-08 Jonathan Shaki , Eden Hartman , Sarit Kraus , Yonatan Aumann

Language is a ubiquitous tool that is foundational to reasoning and collaboration, ranging from everyday interactions to sophisticated problem-solving tasks. The establishment of a common language can serve as a powerful asset in ensuring…

人工智能 · 计算机科学 2025-08-12 Dom Huh , Prasant Mohapatra

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

Traditionally, offline datasets have been used to evaluate task-oriented dialogue (TOD) models. These datasets lack context awareness, making them suboptimal benchmarks for conversational systems. In contrast, user-agents, which are…

计算与语言 · 计算机科学 2024-11-18 Taaha Kazi , Ruiliang Lyu , Sizhe Zhou , Dilek Hakkani-Tur , Gokhan Tur

Large language models (LLMs) are increasingly used to model human social behavior, with recent research exploring their ability to simulate social dynamics. Here, we test whether LLMs mirror human behavior in social dilemmas, where…

社会与信息网络 · 计算机科学 2024-11-18 Jin Han , Balaraju Battu , Ivan Romić , Talal Rahwan , Petter Holme

Large language models (LLMs) have brought autonomous agents closer to artificial general intelligence (AGI) due to their promising generalization and emergent capabilities. There is, however, a lack of studies on how LLM-based agents…

人工智能 · 计算机科学 2024-08-13 Yanan Chen , Ali Pesaranghader , Tanmana Sadhu , Dong Hoon Yi

As AI usage becomes more prevalent in social contexts, understanding agent-user interaction is critical to designing systems that improve both individual and group outcomes. We present an online behavioral experiment (N = 243) in which…

计算机科学与博弈论 · 计算机科学 2026-02-16 Kehang Zhu , Nithum Thain , Vivian Tsai , James Wexler , Crystal Qian