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 7251–7275 of 10817 papers

TitleStatusHype
FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation FrameworkCode0
TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguation—0
UPB at SemEval-2021 Task 8: Extracting Semantic Information on Measurements as Multi-Turn Question Answering—0
Video Question Answering with Phrases via Semantic Roles—0
How Transferable are Reasoning Patterns in VQA?—0
PQA: Perceptual Question AnsweringCode0
A Question-answering Based Framework for Relation Extraction Validation—0
Multimodal Continuous Visual Attention Mechanisms—0
Distantly Supervised Transformers For E-Commerce Product QA—0
Paired Examples as Indirect Supervision in Latent Decision Models—0
Compressing Visual-linguistic Model via Knowledge Distillation—0
ASPER: Attention-based Approach to Extract Syntactic Patterns denoting Semantic Relations in Sentential Context—0
Type Prediction Systems—0
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training—0
Exploring Neural Language Models via Analysis of Local and Global Self-Attention SpacesCode0
Structural Encoding and Pre-training Matter: Adapting BERT for Table-Based Fact Verification—0
Retrieval, Re-ranking and Multi-task Learning for Knowledge-Base Question Answering—0
A View From the Crowd: Evaluation Challenges for Time-Offset Interaction Applications—0
Knowledge Base Question Answering through Recursive Hypergraphs—0
Keep Learning: Self-supervised Meta-learning for Learning from Inference—0
`Just because you are right, doesn't mean I am wrong': Overcoming a bottleneck in development and evaluation of Open-Ended VQA tasks—0
CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning—0
Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering—0
Complex Question Answering on knowledge graphs using machine translation and multi-task learning—0
Analysis on Image Set Visual Question Answering—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