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 7326–7350 of 10817 papers

TitleStatusHype
Optimizing Inference Performance of Transformers on CPUs—0
Biomedical Question Answering: A Survey of Approaches and Challenges—0
Information Extraction From Co-Occurring Similar Entities—0
Decontextualization: Making Sentences Stand-Alone—0
Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering—0
Model Agnostic Answer Reranking System for Adversarial Question Answering—0
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge—0
Answer Questions with Right Image Regions: A Visual Attention Regularization ApproachCode0
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics—0
Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users—0
Do Question Answering Modeling Improvements Hold Across Benchmarks?—0
Self-Teaching Machines to Read and Comprehend with Large-Scale Multi-Subject Question-Answering Data—0
Commonsense Knowledge Mining from Term DefinitionsCode0
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games—0
Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoning—0
Modeling Context in Answer Sentence Selection Systems on a Latency Budget—0
VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs—0
Powering COVID-19 community Q&A with Curated Side Information—0
Knowledge-driven Natural Language Understanding of English Text and its Applications—0
Muppet: Massive Multi-task Representations with Pre-FinetuningCode0
Representations for Question Answering from Documents with Tables and Text—0
Meta-Learning for Effective Multi-task and Multilingual ModellingCode0
Unanswerable Questions about Images and Texts—0
A2P-MANN: Adaptive Attention Inference Hops Pruned Memory-Augmented Neural Networks—0
Towards Natural Language Question Answering over Earth Observation Linked Data using Attention-based Neural Machine Translation—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