most citedToo Good to be Bad: On the Failure of LLMs to Role-Play Villains

2 citations · 5 across the 11 of their papers we have counts for

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cs.CL2026

Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding

Weixu Zhang, Fanghua Ye, Qiang Gao +7

Large language models (LLMs) often produce content that contradicts or overlooks information provided in the input context, a phenomenon known as faithfulness hallucination. In thi…

cs.CL20252 cited

Too Good to be Bad: On the Failure of LLMs to Role-Play Villains

Zihao Yi, Qingxuan Jiang, Ruotian Ma +8

Large Language Models (LLMs) are increasingly tasked with creative generation, including the simulation of fictional characters. However, their ability to portray non-prosocial, an…

cs.CL2025

Social Welfare Function Leaderboard: When LLM Agents Allocate Social Welfare

Zhengliang Shi, Ruotian Ma, Jen-tse Huang +14

Large language models (LLMs) are increasingly entrusted with high-stakes decisions that affect human welfare. However, the principles and values that guide these models when distri…

cs.CL2025

BatonVoice: An Operationalist Framework for Enhancing Controllable Speech Synthesis with Linguistic Intelligence from LLMs

Yue Wang, Ruotian Ma, Xingyu Chen +12

The rise of Large Language Models (LLMs) is reshaping multimodel models, with speech synthesis being a prominent application. However, existing approaches often underutilize the li…

cs.CL20251 cited

The Hunger Game Debate: On the Emergence of Over-Competition in Multi-Agent Systems

Xinbei Ma, Ruotian Ma, Xingyu Chen +14

LLM-based multi-agent systems demonstrate great potential for tackling complex problems, but how competition shapes their behavior remains underexplored. This paper investigates th…

cs.CL2025

CogDual: Enhancing Dual Cognition of LLMs via Reinforcement Learning with Implicit Rule-Based Rewards

Cheng Liu, Yifei Lu, Fanghua Ye +5

Role-Playing Language Agents (RPLAs) have emerged as a significant application direction for Large Language Models (LLMs). Existing approaches typically rely on prompt engineering…