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 7076–7100 of 10817 papers

TitleStatusHype
Distilling Knowledge from Reader to Retriever for Question AnsweringCode1
TAP: Text-Aware Pre-training for Text-VQA and Text-CaptionCode1
CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractionsCode1
KgPLM: Knowledge-guided Language Model Pre-training via Generative and Discriminative Learning—0
Conversational BrowsingCode0
Grammar-aware sentence classification on quantum computers—0
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene UnderstandingCode1
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation—0
WeaQA: Weak Supervision via Captions for Visual Question Answering—0
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering—0
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training—0
How Can We Know When Language Models Know? On the Calibration of Language Models for Question AnsweringCode1
Using the Poly-encoder for a COVID-19 Question Answering SystemCode0
Transformer based Natural Language Generation for Question-Answering—0
Bridging Question Answering and Discourse The case of Multi-Sentence Questions—0
Domino at FinCausal 2020, Task 1 and 2: Causal Extraction SystemCode0
Automatic Evaluation vs. User Preference in Neural Textual QuestionAnswering over COVID-19 Scientific Literature—0
Transformer Semantic Parsing—0
Red Dragon AI at TextGraphs 2020 Shared Task : LIT : LSTM-Interleaved Transformer for Multi-Hop Explanation Ranking—0
A Semi-Supervised BERT Approach for Arabic Named Entity Recognition—0
Multichannel LSTM-CNN for Telugu Text Classification—0
MUCS@TechDOfication using FineTuned Vectors and n-grams—0
Development of Hybrid Algorithm for Automatic Extraction of Multiword Expressions from Monolingual and Parallel Corpus of English and Punjabi—0
Question and Answer pair generation for Telugu short stories—0
Creation of Corpus and Analysis in Code-Mixed Kannada-English Social Media Data for POS Tagging—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