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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5576–5600 of 10817 papers

TitleStatusHype
Beyond the Frame: Generating 360° Panoramic Videos from Perspective Videos—0
DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection—0
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation—0
Beyond the Destination: A Novel Benchmark for Exploration-Aware Embodied Question Answering—0
Do You Know That Florence Is Packed with Visitors? Evaluating State-of-the-art Models of Speaker Commitment—0
LLMs May Perform MCQA by Selecting the Least Incorrect Option—0
Do We Need to Differentiate Negative Candidates Before Training a Neural Ranker?—0
Beyond Text: Implementing Multimodal Large Language Model-Powered Multi-Agent Systems Using a No-Code Platform—0
An Online Question Answering System based on Sub-graph Searching—0
A Framework for the Construction of Monolingual and Cross-lingual Word Similarity Datasets—0
A Concrete Chinese NLP Pipeline—0
On the Need of Cross Validation for Discourse Relation Classification—0
Do Vision-Language Transformers Exhibit Visual Commonsense? An Empirical Study of VCR—0
Double Visual Defense: Adversarial Pre-training and Instruction Tuning for Improving Vision-Language Model Robustness—0
Double Topic Shifts in Open Domain Conversations: Natural Language Interface for a Wikipedia-based Robot Application—0
Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers—0
Annotation Scheme for Constructing Sentiment Corpus in Korean—0
Double Retrieval and Ranking for Accurate Question Answering—0
Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules?—0
Do Transformer Networks Improve the Discovery of Rules from Text?—0
Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering—0
Annotation Methodologies for Vision and Language Dataset Creation—0
A Framework for the Classification and Annotation of Multiword Expressions in Dialectal Arabic—0
DoT: An efficient Double Transformer for NLP tasks with tables—0
Do Smaller Language Models Answer Contextualised Questions Through Memorisation Or Generalisation?—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