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Generative Question Answering

Papers

Showing 125 of 45 papers

TitleStatusHype
Verif.ai: Towards an Open-Source Scientific Generative Question-Answering System with Referenced and Verifiable AnswersCode2
ANAH: Analytical Annotation of Hallucinations in Large Language ModelsCode2
ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language GenerationCode1
Retrieval-Augmented Generative Question Answering for Event Argument ExtractionCode1
General-Purpose Question-Answering with MacawCode1
PALM: Pre-training an Autoencoding&Autoregressive Language Model for Context-conditioned GenerationCode1
KPQA: A Metric for Generative Question Answering Using Keyphrase WeightsCode1
CoQA: A Conversational Question Answering ChallengeCode0
Reshaping Free-Text Radiology Notes Into Structured Reports With Generative TransformersCode0
Unified Language Model Pre-training for Natural Language Understanding and GenerationCode0
Neural Generative Question AnsweringCode0
Sequence-to-Sequence Spanish Pre-trained Language ModelsCode0
Evaluation of medium-large Language Models at zero-shot closed book generative question answering0
Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answering0
EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering0
Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems0
Flexible End-to-End Dialogue System for Knowledge Grounded Conversation0
Generative Question Answering: Learning to Answer the Whole Question0
HIT&QMUL at SemEval-2022 Task 9: Label-Enclosed Generative Question Answering (LEG-QA)0
Incorporating External Knowledge into Machine Reading for Generative Question Answering0
Mitigating LLM Hallucinations via Conformal Abstention0
Modeling Multi-hop Question Answering as Single Sequence Prediction0
Modeling Multi-hop Question Answering as Single Sequence Prediction0
PALM: Pre-training an Autoencoding\&Autoregressive Language Model for Context-conditioned Generation0
Prompt Generate Train (PGT): Few-shot Domain Adaption of Retrieval Augmented Generation Models for Open Book Question-Answering0
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