Papers by Jennifer Pan

3 papers
Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies (D18-1)

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Challenge: Amidst growing concern over media manipulation, NLP studies focus on overt strategies like censorship and “fake news”.
Approach: They propose to use two concepts from political science literature to identify subtler media manipulation strategies . they propose to apply embedding-based methods to cross-lingually project English frames to Russian .
Outcome: The proposed techniques can be applied to 13 years of the Russian newspaper Izvestia and show that they highlight U.S. moral failings and threats to the U.s.
Biased LLMs can Influence Political Decision-Making (2025.acl-long)

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Challenge: Recent studies have found that biased LLMs can influence decisions in areas such as medical classifications and educational hiring.
Approach: They conducted two interactive experiments on partisan bias in large language models while completing tasks with either a biased liberal, biased conservative, or unbiased control model.
Outcome: The results show that prior knowledge of AI is weakly correlated with a reduction of the bias, suggesting that AI education can be crucial for mitigating bias effects.
GenTool: Enhancing Tool Generalization in Language Models through Zero-to-One and Weak-to-Strong Simulation (2025.findings-acl)

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Challenge: Large Language Models (LLMs) can expand their capabilities by integrating external tools.
Approach: They propose a training framework that prepares LLMs for diverse generalization challenges in tool utilization.
Outcome: The proposed framework improves the tool-usage capabilities of LLMs by up to 8B parameters, surpassing GPT-4o.

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