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 6301–6325 of 10817 papers

TitleStatusHype
Neural Retriever and Go Beyond: A Thesis Proposal—0
Visual Superordinate Abstraction for Robust Concept Learning—0
V-Doc : Visual questions answers with Documents—0
Prompt-based Learning for Unpaired Image Captioning—0
Grammar Detection for Sentiment Analysis through Improved Viterbi Algorithm—0
Asking the Right Questions in Low Resource Template Extraction—0
Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models—0
Reasoning over Logically Interacted Conditions for Question Answering—0
Investigating Information Inconsistency in Multilingual Open-Domain Question Answering—0
Leveraging QA Datasets to Improve Generative Data AugmentationCode0
Re-Examining Calibration: The Case of Question AnsweringCode0
Guiding Visual Question Answering with Attention Priors—0
From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answering—0
FabKG: A Knowledge graph of Manufacturing Science domain utilizing structured and unconventional unstructured knowledge source—0
On Advances in Text Generation from Images Beyond Captioning: A Case Study in Self-Rationalization—0
Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization—0
Policy Compliance Detection via Expression Tree Inference—0
A Survey on Neural Open Information Extraction: Current Status and Future Directions—0
Community Question Answering Entity Linking via Leveraging Auxiliary DataCode0
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticityCode0
VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering—0
Interpretable Proof Generation via Iterative Backward ReasoningCode0
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models—0
NS3: Neuro-Symbolic Semantic Code SearchCode0
Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection—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