6 papers
GS-QA: A Benchmark for Geospatial Question Answering
Majid Saeedan, Muhammad Shihab Rashid, Ahmed Eldawy +1
Recent advances in Large Language Models (LLMs) have led to dramatic improvements in question answering (QA). To address the challenge of evaluating QA systems, standardized benchm…
Progressive Query Expansion for Retrieval Over Cost-constrained Data Sources
Muhammad Shihab Rashid, Jannat Ara Meem, Yue Dong +1
Query expansion has been employed for a long time to improve the accuracy of query retrievers. Earlier works relied on pseudo-relevance feedback (PRF) techniques, which augment a q…
NORMY: Non-Uniform History Modeling for Open Retrieval Conversational Question Answering
Muhammad Shihab Rashid, Jannat Ara Meem, Vagelis Hristidis
Open Retrieval Conversational Question Answering (OrConvQA) answers a question given a conversation as context and a document collection. A typical OrConvQA pipeline consists of th…
PAT-Questions: A Self-Updating Benchmark for Present-Anchored Temporal Question-Answering
Jannat Ara Meem, Muhammad Shihab Rashid, Yue Dong +1
Existing work on Temporal Question Answering (TQA) has predominantly focused on questions anchored to specific timestamps or events (e.g. "Who was the US president in 1970?"). Litt…
EcoRank: Budget-Constrained Text Re-ranking Using Large Language Models
Muhammad Shihab Rashid, Jannat Ara Meem, Yue Dong +1
Large Language Models (LLMs) have achieved state-of-the-art performance in text re-ranking. This process includes queries and candidate passages in the prompts, utilizing pointwise…
Emotion Recognition with Forearm-based Electromyography
Muhammad Shihab Rashid, Zubayet Zaman, Hasan Mahmud +1
Electromyography is an unexplored field of study when it comes to alternate input modality while interacting with a computer. However, to make computers understand human emotions i…