SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 7901–7925 of 10817 papers

TitleStatusHype
Structured Knowledge Grounding for Question Answering—0
Question-to-Question Retrieval for Hallucination-Free Knowledge Access: An Approach for Wikipedia and Wikidata Question Answering—0
Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing—0
GPT-3 Models are Few-Shot Financial Reasoners—0
GOVERN: Gradient Orientation Vote Ensemble for Multi-Teacher Reinforced Distillation—0
Flexible Frame Selection for Efficient Video Reasoning—0
Complex Question Answering: Unsupervised Learning Approaches and Experiments—0
QUINT: Interpretable Question Answering over Knowledge Bases—0
AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis—0
QU-IR at SemEval 2016 Task 3: Learning to Rank on Arabic Community Question Answering Forums with Word Embedding—0
Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review—0
GoT-CQA: Graph-of-Thought Guided Compositional Reasoning for Chart Question Answering—0
QuOTE: Question-Oriented Text Embeddings—0
QurAna: Corpus of the Quran annotated with Pronominal Anaphora—0
Goodwill Hunting: Analyzing and Repurposing Off-the-Shelf Named Entity Linking Systems—0
Complex Question Answering on knowledge graphs using machine translation and multi-task learning—0
Good, Great, Excellent: Global Inference of Semantic Intensities—0
Complex QA and language models hybrid architectures, Survey—0
R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Education—0
R3: A Reading Comprehension Benchmark Requiring Reasoning Processes—0
R3 : Refined Retriever-Reader pipeline for Multidoc2dial—0
FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts—0
R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models—0
RA-BLIP: Multimodal Adaptive Retrieval-Augmented Bootstrapping Language-Image Pre-training—0
ReAgent: Reversible Multi-Agent Reasoning for Knowledge-Enhanced Multi-Hop QA—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified