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Research

Papers for “question answering”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

TitleAuthorsYearSource
60 Data Points are Sufficient to Fine-Tune LLMs for Question-AnsweringJunjie Ye, Yuming Yang, Qi Zhang2024arxiv 2409.15825
Integrating Neural and Symbolic Components in a Model of Pragmatic Question-AnsweringPolina Tsvilodub, Robert D. Hawkins, Michael Franke2025arxiv 2506.01474
AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark DatasetTobi Olatunji, Charles Nimo, Abraham Owodunni2024arxiv 2411.15640
Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 DatasetPragya Katyayan, Nisheeth Joshi2022arxiv 2204.09659
Prompt Generate Train (PGT): Few-shot Domain Adaption of Retrieval Augmented Generation Models for Open Book Question-AnsweringC. S. Krishna2023arxiv 2307.05915
Evaluating the Ebb and Flow: An In-depth Analysis of Question-Answering Trends across Diverse PlatformsRima Hazra, Agnik Saha, Somnath Banerjee2023arxiv 2309.05961
DragonVerseQA: Open-Domain Long-Form Context-Aware Question-AnsweringAritra Kumar Lahiri, Qinmin Vivian Hu2024arxiv 2412.16694
Hierarchical Question-Answering for Driving Scene Understanding Using Vision-Language ModelsSafaa Abdullahi Moallim Mohamud, Minjin Baek, Dong Seog Han2025arxiv 2506.02615
Knowledge Distillation of Domain-adapted LLMs for Question-Answering in TelecomRishika Sen, Sujoy Roychowdhury, Sumit Soman2025arxiv 2504.20000
Designing a Communication Bridge between Communities: Participatory Design for a Question-Answering AI AgentJeonghyun Lee, Vrinda Nandan, Harshvardhan Sikka2023arxiv 2308.00813
UIT-E10dot3 at SemEval-2021 Task 5: Toxic Spans Detection with Named Entity Recognition and Question-Answering ApproachesPhu Gia Hoang, Luan Thanh Nguyen, Kiet Van Nguyen2021arxiv 2104.07376
PAT-Questions: A Self-Updating Benchmark for Present-Anchored Temporal Question-AnsweringJannat Ara Meem, Muhammad Shihab Rashid, Yue Dong2024arxiv 2402.11034
KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-AnsweringIftitahu Ni'mah, Samaneh Khoshrou, Vlado Menkovski2023arxiv 2310.19650
EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge GraphsZixuan Dong, Baoyun Peng, Yufei Wang2024arxiv 2406.01238
Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over EvidenceWei Sun, Mingxiao Li, Damien Sileo2023arxiv 2310.01299
Framework for Question-Answering in Sanskrit through Automated Construction of Knowledge GraphsHrishikesh Terdalkar, Arnab Bhattacharya2023arxiv 2310.07848
Question-Answering Based Summarization of Electronic Health Records using Retrieval Augmented GenerationWalid Saba, Suzanne Wendelken, James. Shanahan2024arxiv 2401.01469
Pir\'a: A Bilingual Portuguese-English Dataset for Question-Answering about the OceanAndré F. A. Paschoal, Paulo Pirozelli, Valdinei Freire2022arxiv 2202.02398
STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical Question-AnsweringGuohao Sun, Can Qin, Huazhu Fu2024arxiv 2406.19973
Asking For It: Question-Answering for Predicting Rule Infractions in Online Content ModerationMattia Samory, Diana Pamfile, Andrew To2025arxiv 2510.06350