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cs.CL2026
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…
cs.CL2026
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…
cs.CL2026
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…