activity
20242026
collaborators

18 papers

cs.CL2026

Question Difficulty Estimation for Large Language Models via Answer Plausibility Scoring

Jamshid Mozafari, Bhawna Piryani, Adam Jatowt

Estimating question difficulty is a critical component in evaluating and improving large language models (LLMs) for question answering (QA). Existing approaches often rely on reada…

cs.CL2026

Pretraining Exposure Explains Popularity Judgments in Large Language Models

Jamshid Mozafari, Bhawna Piryani, Adam Jatowt

Large language models (LLMs) exhibit systematic preferences for well-known entities, a phenomenon often attributed to popularity bias. However, the extent to which these preference…

cs.CL2026

Context Convergence Improves Answering Inferential Questions

Jamshid Mozafari, Bhawna Piryani, Adam Jatowt

While Large Language Models (LLMs) are widely used in open-domain Question Answering (QA), their ability to handle inferential questions-where answers must be derived rather than d…

cs.CL2026

It's High Time: A Survey of Temporal Question Answering

Bhawna Piryani, Abdelrahman Abdallah, Jamshid Mozafari +2

Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Temporal Question Answering (TQA), a…

cs.IR2026

BracketRank: Large Language Model Document Ranking via Reasoning-based Competitive Elimination

Abdelrahman Abdallah, Mohammed Ali, Bhawna Piryani +1

Reasoning-intensive retrieval requires deep semantic inference beyond surface-level keyword matching, posing a challenge for current LLM-based rerankers limited by context constrai…

cs.CL2026

How often do Answers Change? Estimating Recency Requirements in Question Answering

Bhawna Piryani, Zehra Mert, Adam Jatowt

Large language models (LLMs) often rely on outdated knowledge when answering time-sensitive questions, leading to confident yet incorrect responses. Without explicit signals indica…