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 5701–5725 of 10817 papers

TitleStatusHype
MaMMUT: A Simple Architecture for Joint Learning for MultiModal TasksCode0
Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding—0
Comparative Analysis of CHATGPT and the evolution of language models—0
ChatGPT as a Factual Inconsistency Evaluator for Text Summarization—0
Curriculum Learning for Compositional Visual Reasoning—0
DBLP-QuAD: A Question Answering Dataset over the DBLP Scholarly Knowledge GraphCode0
GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question AnsweringCode0
Explainable Semantic Communication for Text Tasks—0
Salient Span Masking for Temporal Understanding—0
Integrating Image Features with Convolutional Sequence-to-sequence Network for Multilingual Visual Question AnsweringCode0
GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering—0
PanGu-Σ: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing—0
3D Concept Learning and Reasoning from Multi-View Images—0
On-the-fly Text Retrieval for End-to-End ASR Adaptation—0
FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual Question Answering—0
A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering—0
An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question AnsweringCode0
Generate, Transform, Answer: Question Specific Tool Synthesis for Tabular Data—0
Secret-Keeping in Question Answering—0
Logical Implications for Visual Question Answering ConsistencyCode0
Vision-Language Models as Success Detectors—0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images—0
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region—0
Generating multiple-choice questions for medical question answering with distractors and cue-masking—0
LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension—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