1 citations · 1 across the 4 of their papers we have counts for
5 papers
Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation
Xinyu Wang, Sai Koneru, Wenbo Zhang +3
Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior work has often treated fake ne…
Context Selection for Hypothesis and Statistical Evidence Extraction from Full-Text Scientific Articles
Sai Koneru, Jian Wu, Sarah Rajtmajer
Extracting hypotheses and their supporting statistical evidence from full-text scientific articles is central to the synthesis of empirical findings, but remains difficult due to d…
Evaluating Evidence Grounding Under User Pressure in Instruction-Tuned Language Models
Sai Koneru, Elphin Joe, Christine Kirchhoff +2
In contested domains, instruction-tuned language models must balance user-alignment pressures against faithfulness to the in-context evidence. To evaluate this tension, we introduc…
Social Scientists on the Role of AI in Research
Tatiana Chakravorti, Xinyu Wang, Pranav Narayanan Venkit +3
The integration of artificial intelligence (AI) into social science research practices raises significant technological, methodological, and ethical issues. We present a community-…
Have LLMs Reopened the Pandora's Box of AI-Generated Fake News?
Xinyu Wang, Wenbo Zhang, Sai Koneru +5
With the rise of AI-generated content spewed at scale from large language models (LLMs), genuine concerns about the spread of fake news have intensified. The perceived ability of L…