Papers by Xun Guan

2 papers
MimicLM: Zero-Shot Voice Imitation through Autoregressive Modeling of Pseudo-Parallel Speech Corpora (2026.findings-acl)

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Challenge: Existing approaches to voice imitation use complex model design and a quality ceiling when synthetic speech is used as training *sources*.
Approach: They propose a model that uses synthetic speech as training *sources* while retaining real recordings as *targets*.
Outcome: The proposed model outperforms existing methods in naturalness while maintaining competitive similarity scores across speaker identity, accent, and emotion dimensions.
ALYMPICS: LLM Agents Meet Game Theory (2025.coling-main)

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Challenge: Alympics provides a framework for simulating human-like strategic interactions with Large Language Model (LLM) agents.
Approach: They propose a framework utilizing Large Language Models (LLM) agents for empirical game theory research.
Outcome: The proposed framework can be used to study human-like strategic interactions with large language model (LLM) agents in a game on the multi-round auction of scarce survival resources.

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