Ebrahim Bagheri

Large Language Models (LLMs) are now widely used for query reformulation and expansion in Information Retrieval, with many studies reporting substantial effectiveness gains. However, these results are typically obtained under heterogeneous experimental conditions, making it difficult to assess wh...

Peer review is central to scientific decision-making, yet it is rarely evaluated or audited at scale. Growing submission volumes and the increasing use of large language models (LLMs) in drafting reviews have introduced new challenges for transparency, accountability, and quality control. Today,...

Information Retrieval systems can amplify societal inequalities when training data and ranking algorithms encode biases toward certain gender identities. Query reformulation methods are known to improve retrieval effectiveness, yet they seldom treat retrieval fairness as a first-class criterion....

Neural rankers are typically trained with surrogate objectives because target evaluation metrics such as Normalized Discounted Cumulative Gain (NDCG) are non-differentiable. Existing approaches rely on hand-designed surrogate losses or fixed smooth relaxations, which can be misaligned with the ta...

Peer review is central to scientific publishing, yet reviewers frequently include claims that are subjective, rhetorical, or misaligned with the submitted work. Assessing whether review statements are factual and verifiable is crucial for fairness and accountability. At the scale of modern confer...

Large Language Models (LLMs) are increasingly used in scientific peer review, assisting with drafting, rewriting, and refinement. However, existing peer-review LLM detection methods largely treat authorship as a binary problem (human vs. AI) without accounting for the hybrid nature of modern revi...

Modern information retrieval pipelines combine retrieval, LLM-based generation, and LLM-based judgment, and a poor outcome may originate in any of the three stages. Existing work studies these failures in isolation. This paper instead asks whether query difficulty itself transfers across the thre...