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 6126–6150 of 10817 papers

TitleStatusHype
Elaboration-Generating Commonsense Question Answering at ScaleCode0
Zero-shot Event Causality Identification with Question Answering—0
Unsupervised Domain Adaptation on Question-Answering System with Conversation Data—0
A Visually-Aware Conversational Robot Receptionist—0
GRILLBot: A multi-modal conversational agent for complex real-world tasks—0
Continuous QA Learning with Structured Prompts—0
A topic-aware graph neural network model for knowledge base updating—0
Faithful Reasoning Using Large Language Models—0
Efficient and Interpretable Neural Models for Entity Tracking—0
Exploring and Evaluating Personalized Models for Code Generation—0
Conversion of Legal Agreements into Smart Legal Contracts using NLP—0
Building the Intent Landscape of Real-World Conversational Corpora with Extractive Question-Answering Transformers—0
Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Tasks—0
Bidirectional Contrastive Split Learning for Visual Question Answering—0
FashionVQA: A Domain-Specific Visual Question Answering System—0
Evaluate Confidence Instead of Perplexity for Zero-shot Commonsense Reasoning—0
Unsupervised Question Answering via Answer DiversifyingCode0
How good are deep models in understanding the generated images?—0
Neuro-Symbolic Visual DialogCode0
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language TasksCode0
VLMAE: Vision-Language Masked Autoencoder—0
UnCommonSense: Informative Negative Knowledge about Everyday Concepts—0
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification—0
NECE: Narrative Event Chain Extraction Toolkit—0
Knowledge Graph Curation: A Practical Framework—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