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 8151–8200 of 10817 papers

TitleStatusHype
Why can't memory networks read effectively?—0
NumNet: Machine Reading Comprehension with Numerical ReasoningCode0
Enhancing the Transformer with Explicit Relational Encoding for Math Problem SolvingCode0
Efficiently Embedding Dynamic Knowledge Graphs—0
Answering Complex Open-domain Questions Through Iterative Query GenerationCode0
Structured Pruning of a BERT-based Question Answering Model—0
Whatcha lookin' at? DeepLIFTing BERT's Attention in Question AnsweringCode0
Neural Memory Plasticity for Anomaly Detection—0
Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge BaseCode0
Multi-modal Deep Analysis for Multimedia—0
Learning Analogy-Preserving Sentence Embeddings for Answer Selection—0
Multilingual Question Answering from Formatted Text applied to Conversational Agents—0
Domain-Relevant Embeddings for Medical Question Similarity—0
Modulated Self-attention Convolutional Network for VQA—0
Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context ExpansionCode0
Multi-hop Question Answering via Reasoning ChainsCode0
REMIND Your Neural Network to Prevent Catastrophic ForgettingCode0
Measuring Sentences Similarity: A Survey—0
Multi-level Gated Recurrent Neural Network for Dialog Act Classification—0
From Strings to Things: Knowledge-Enabled VQA Model That Can Read and Reason—0
SegEQA: Video Segmentation Based Visual Attention for Embodied Question Answering—0
Neural Question Generation using Interrogative Phrases—0
MMM: Multi-stage Multi-task Learning for Multi-choice Reading ComprehensionCode0
BERT for Question Generation—0
基於特徵粒度之訓練策略於中文口語問答系統之應用(A Feature-granularity Training Strategy for Chinese Spoken Question Answering)—0
基於深度學習之簡答題問答系統初步探討(A Preliminary Study on Deep Learning-based Short Answer Question Answering System)—0
Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word RepresentationsCode0
Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks—0
On Incorporating Semantic Prior Knowledge in Deep Learning Through Embedding-Space Constraints—0
A Simple and Effective Model for Answering Multi-span QuestionsCode0
Named Entity Recognition System for Sindhi Language—0
Distantly Supervised Question ParsingCode0
Spoken Conversational Search for General Knowledge—0
Compact Trilinear Interaction for Visual Question AnsweringCode0
AlignNet: Self-supervised Alignment Module—0
ASGen: Answer-containing Sentence Generation to Pre-Train Question Generator for Scale-up Data in Question Answering—0
Question Answering is a Format; When is it Useful?—0
On Incorporating Semantic Prior Knowlegde in Deep Learning Through Embedding-Space Constraints—0
Linguistic Embeddings as a Common-Sense Knowledge Repository: Challenges and Opportunities—0
Leveraging Entanglement Entropy for Deep Understanding of Attention Matrix in Text Matching—0
Learning to Recognize the Unseen Visual Predicates—0
Latent Question Reformulation and Information Accumulation for Multi-Hop Machine Reading—0
AdvCodec: Towards A Unified Framework for Adversarial Text Generation—0
UNITER: Learning UNiversal Image-TExt Representations—0
Why Does the VQA Model Answer No?: Improving Reasoning through Visual and Linguistic Inference—0
Technical report on Conversational Question Answering—0
An Empirical Study of Content Understanding in Conversational Question AnsweringCode0
Portuguese Named Entity Recognition using BERT-CRFCode0
Non-monotonic Logical Reasoning Guiding Deep Learning for Explainable Visual Question Answering—0
TinyBERT: Distilling BERT for Natural Language UnderstandingCode0
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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