7 citations · 31 across the 21 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
PARSE: An Open-Domain Reasoning Question Answering Benchmark for Persian
Jamshid Mozafari, Seyed Parsa Mousavinasab, Adam Jatowt
Reasoning-focused Question Answering (QA) has advanced rapidly with Large Language Models (LLMs), yet high-quality benchmarks for low-resource languages remain scarce. Persian, spo…
Inferential Question Answering
Jamshid Mozafari, Hamed Zamani, Guido Zuccon +1
Despite extensive research on a wide range of question answering (QA) systems, most existing work focuses on answer containment-i.e., assuming that answers can be directly extracte…