activity
20222026
most citedFrom Persona to Personalization: A Survey on Role-Playing Language Agents

14 citations · 56 across the 33 of their papers we have counts for

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Showing 2024Show all

15 papers · 1 filter

cs.CL2024

MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning

Nianqi Li, Zujie Liang, Siyu Yuan +3

Program-of-Thought (PoT), which aims to use programming language instead of natural language as an intermediate step in reasoning, is an important way for LLMs to solve mathematica…

cs.AI2024

Revealing the Barriers of Language Agents in Planning

Jian Xie, Kexun Zhang, Jiangjie Chen +5

Autonomous planning has been an ongoing pursuit since the inception of artificial intelligence. Based on curated problem solvers, early planning agents could deliver precise soluti…

cs.CR2024★ 1 cited

WAPITI: A Watermark for Finetuned Open-Source LLMs

Lingjie Chen, Ruizhong Qiu, Siyu Yuan +6

Watermarking of large language models (LLMs) generation embeds an imperceptible statistical pattern within texts, making it algorithmically detectable. Watermarking is a promising…

cs.CL2024

Past Meets Present: Creating Historical Analogy with Large Language Models

Nianqi Li, Siyu Yuan, Jiangjie Chen +5

Historical analogies, which compare known past events with contemporary but unfamiliar events, are important abilities that help people make decisions and understand the world. How…

cs.AI2024

MINDECHO: Role-Playing Language Agents for Key Opinion Leaders

Rui Xu, Dakuan Lu, Xiaoyu Tan +5

Large language models~(LLMs) have demonstrated impressive performance in various applications, among which role-playing language agents (RPLAs) have engaged a broad user base. Now,…

cs.CV2024

Light Up the Shadows: Enhance Long-Tailed Entity Grounding with Concept-Guided Vision-Language Models

Yikai Zhang, Qianyu He, Xintao Wang +3

Multi-Modal Knowledge Graphs (MMKGs) have proven valuable for various downstream tasks. However, scaling them up is challenging because building large-scale MMKGs often introduces…

cs.CL2024★ 2 cited

SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals

Ruihan Yang, Jiangjie Chen, Yikai Zhang +5

Language agents powered by large language models (LLMs) are increasingly valuable as decision-making tools in domains such as gaming and programming. However, these agents often fa…

cs.AI2024

EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms

Siyu Yuan, Kaitao Song, Jiangjie Chen +3

The rise of powerful large language models (LLMs) has spurred a new trend in building LLM-based autonomous agents for solving complex tasks, especially multi-agent systems. Despite…

cs.CL2024

Boosting Scientific Concepts Understanding: Can Analogy from Teacher Models Empower Student Models?

Siyu Yuan, Cheng Jiayang, Lin Qiu +1

Analogical reasoning plays a critical role in human cognition, enabling us to understand new concepts by associating them with familiar ones. Previous research in the AI community…

cs.CL2024★ 14 cited

From Persona to Personalization: A Survey on Role-Playing Language Agents

Jiangjie Chen, Xintao Wang, Rui Xu +15

Recent advancements in large language models (LLMs) have significantly boosted the rise of Role-Playing Language Agents (RPLAs), i.e., specialized AI systems designed to simulate a…

cs.CL2024

"A good pun is its own reword": Can Large Language Models Understand Puns?

Zhijun Xu, Siyu Yuan, Lingjie Chen +1

Puns play a vital role in academic research due to their distinct structure and clear definition, which aid in the comprehensive analysis of linguistic humor. However, the understa…

cs.CL2024★ 1 cited

Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works

Xinfeng Yuan, Siyu Yuan, Yuhan Cui +5

Large language models (LLMs) have demonstrated impressive performance and spurred numerous AI applications, in which role-playing agents (RPAs) are particularly popular, especially…

cs.AI2024★ 1 cited

Character is Destiny: Can Role-Playing Language Agents Make Persona-Driven Decisions?

Rui Xu, Xintao Wang, Jiangjie Chen +6

Can Large Language Models (LLMs) simulate humans in making important decisions? Recent research has unveiled the potential of using LLMs to develop role-playing language agents (RP…

cs.CL2024

TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation

Yikai Zhang, Siyu Yuan, Caiyu Hu +3

Despite remarkable advancements in emulating human-like behavior through Large Language Models (LLMs), current textual simulations do not adequately address the notion of time. To…

cs.CL2024★ 4 cited

EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction

Siyu Yuan, Kaitao Song, Jiangjie Chen +5

To address intricate real-world tasks, there has been a rising interest in tool utilization in applications of large language models (LLMs). To develop LLM-based agents, it usually…