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 5926–5950 of 10817 papers

TitleStatusHype
Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency—0
Benchmarking Retrieval-Augmented Large Language Models in Biomedical NLP: Application, Robustness, and Self-Awareness—0
An Inference Approach To Question Answering Over Knowledge Graphs—0
Learning to Order Natural Language Texts—0
Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approach—0
Learning to Navigate Wikipedia by Taking Random Walks—0
Learning to Model Multilingual Unrestricted Coreference in OntoNotes—0
Distilling Salient Reviews with Zero Labels—0
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks.—0
Learning to Map Natural Language Statements into Knowledge Base Representations for Knowledge Base Construction—0
Learning to Make Inferences in a Semantic Parsing Task—0
Distilling an End-to-End Voice Assistant Without Instruction Training Data—0
Learning to Jointly Predict Ellipsis and Comparison Structures—0
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation—0
An In-Context Schema Understanding Method for Knowledge Base Question Answering—0
Long-Tailed Question Answering in an Open World—0
Long-Term Memory Networks for Question Answering—0
Learning to Interactively Learn and Assist—0
Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?—0
Learning to Inference Adaptively for Multimodal Large Language Models—0
Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning—0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications—0
Learning to Identify Follow-Up Questions in Conversational Question Answering—0
Learning to Generate Word Representations using Subword Information—0
Learning to Generate Questions by Recovering Answer-containing Sentences—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