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Xinyi Mou

8 accepted papers

2025

AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios

NAACL 2025long

Large language models (LLMs) are increasingly leveraged to empower autonomous agents to simulate human beings in various fields of behavioral research. However, evaluating their capacity to navigate complex social interactions remains a challenge. Previous studies face limitations due to insufficien…

2025

EcoLANG: Efficient and Effective Agent Communication Language Induction for Social Simulation

EMNLP 2025

Large language models (LLMs) have demonstrated an impressive ability to role-play humans and replicate complex social dynamics. However, large-scale LLM-driven simulations still face significant challenges in high time and computational costs. We observe that there exists redundancy in current agent

2024

PASUM: A Pre-training Architecture for Social Media User Modeling Based on Text Graph

COLING 2024main

Modeling social media users is the core of social governance in the digital society. Existing works have incorporated different digital traces to better learn the representations of social media users, including text information encoded by pre-trained language models and social network information e…

2024

SoMeLVLM: A Large Vision Language Model for Social Media Processing

ACL 2024findings

The growth of social media, characterized by its multimodal nature, has led to the emergence of diverse phenomena and challenges, which calls for an effective approach to uniformly solve automated tasks. The powerful Large Vision Language Models make it possible to handle a variety of tasks simultan…

Cited by 7SourcePDFScholar
2024

Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation

ACL 2024findings

Social media has emerged as a cornerstone of social movements, wielding significant influence in driving societal change. Simulating the response of the public and forecasting the potential impact has become increasingly important. However, existing methods for simulating such phenomena encounter ch…

2023

UPPAM: A Unified Pre-training Architecture for Political Actor Modeling based on Language

ACL 2023long

Modeling political actors is at the core of quantitative political science. Existing works have incorporated contextual information to better learn the representation of political actors for specific tasks through graph models. However, they are limited to the structure and objective of training set…

2022

A Two Stage Adaptation Framework for Frame Detection via Prompt Learning

COLING 2022main

Framing is a communication strategy to bias discussion by selecting and emphasizing. Frame detection aims to automatically analyze framing strategy. Previous works on frame detection mainly focus on a single scenario or issue, ignoring the special characteristics of frame detection that new events e…

2021

Align Voting Behavior with Public Statements for Legislator Representation Learning

ACL 2021long

Ideology of legislators is typically estimated by ideal point models from historical records of votes. It represents legislators and legislation as points in a latent space and shows promising results for modeling voting behavior. However, it fails to capture more specific attitudes of legislators t…