2 papers
cs.IR2026
Led to Mislead: Adversarial Content Injection for Attacks on Neural Ranking Models
Amin Bigdeli, Amir Khosrojerdi, Radin Hamidi Rad +3
Neural Ranking Models (NRMs) are central to modern information retrieval but remain highly vulnerable to adversarial manipulation. Existing attacks often rely on heuristics or surr…
cs.CL2025
Benchmarking Prompt Sensitivity in Large Language Models
Amirhossein Razavi, Mina Soltangheis, Negar Arabzadeh +3
Large language Models (LLMs) are highly sensitive to variations in prompt formulation, which can significantly impact their ability to generate accurate responses. In this paper, w…