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 7551–7575 of 10817 papers

TitleStatusHype
Large-Scale Adversarial Training for Vision-and-Language Representation LearningCode1
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic ReasoningCode1
Exploring Weaknesses of VQA Models through Attribution Driven Insights—0
ClarQ: A large-scale and diverse dataset for Clarification Question GenerationCode1
Estimating semantic structure for the VQA answer space—0
Foreseeing the Benefits of Incidental SupervisionCode0
Roses Are Red, Violets Are Blue... but Should Vqa Expect Them To?Code1
Knowledge-Aided Open-Domain Question Answering—0
Counterfactual VQA: A Cause-Effect Look at Language BiasCode1
Pre-training Polish Transformer-based Language Models at ScaleCode1
Language Models as Fact Checkers?—0
SERank: Optimize Sequencewise Learning to Rank Using Squeeze-and-Excitation NetworkCode1
A Cross-Task Analysis of Text Span RepresentationsCode1
DeBERTa: Decoding-enhanced BERT with Disentangled AttentionCode2
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too—0
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension—0
Open-Domain Question Answering with Pre-Constructed Question Spaces—0
Subjective Question Answering: Deciphering the inner workings of Transformers in the realm of subjectivityCode0
BERT Based Multilingual Machine Comprehension in English and HindiCode0
Question Answering on Scholarly Knowledge Graphs—0
Building a Swedish Question-Answering ModelCode0
TA-Student VQA: Multi-Agents Training by Self-Questioning—0
Counterfactual Vision and Language Learning—0
Attention-Based Context Aware Reasoning for Situation RecognitionCode1
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features—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