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 9051–9100 of 10817 papers

TitleStatusHype
Asking and Answering Questions to Extract Event-Argument StructuresCode0
Delving Deeper into Cross-lingual Visual Question AnsweringCode0
Defending Against Disinformation Attacks in Open-Domain Question AnsweringCode0
Deep Unordered Composition Rivals Syntactic Methods for Text ClassificationCode0
Deep Relevance Ranking Using Enhanced Document-Query InteractionsCode0
Integrating Image Features with Convolutional Sequence-to-sequence Network for Multilingual Visual Question AnsweringCode0
Adaptive loose optimization for robust question answeringCode0
RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question AnsweringCode0
OptLLM: Optimal Assignment of Queries to Large Language ModelsCode0
An Improved Attention for Visual Question AnsweringCode0
DeepREF: A Framework for Optimized Deep Learning-based Relation ClassificationCode0
Integrating question answering and text-to-SQL in PortugueseCode0
Human Attention during Goal-directed Reading Comprehension Relies on Task OptimizationCode0
Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity CategoriesCode0
Integrating Semantic Knowledge into Lexical Embeddings Based on Information Content MeasurementCode0
QAGAN: Adversarial Approach To Learning Domain Invariant Language FeaturesCode0
Order-Planning Neural Text Generation From Structured DataCode0
Deep Modular Co-Attention Networks for Visual Question AnsweringCode0
Deep Learning for Answer Sentence SelectionCode0
Intelligent Assistant for People with Low Vision AbilitiesCode0
QAGCN: Answering Multi-Relation Questions via Single-Step Implicit Reasoning over Knowledge GraphsCode0
Intent Classification in Question-Answering Using LSTM ArchitecturesCode0
Identifying relevant common sense information in knowledge graphsCode0
DEEPAGÉ: Answering Questions in Portuguese about the Brazilian EnvironmentCode0
I Could've Asked That: Reformulating Unanswerable QuestionsCode0
Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question AnsweringCode0
DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question AnsweringCode0
Aligning Large Language Models for Clinical TasksCode0
HyTE: Hyperplane-based Temporally aware Knowledge Graph EmbeddingCode0
QAInfomax: Learning Robust Question Answering System by Mutual Information MaximizationCode0
Interactive Instance-based Evaluation of Knowledge Base Question AnsweringCode0
Hypercube-RAG: Hypercube-Based Retrieval-Augmented Generation for In-domain Scientific Question-AnsweringCode0
Hyperbolic Representation Learning for Fast and Efficient Neural Question AnsweringCode0
Interactive Machine Comprehension with Information Seeking AgentsCode0
Hybrid Autoregressive Inference for Scalable Multi-hop Explanation RegenerationCode0
QA-It: Classifying Non-Referential It for Question Answer PairsCode0
Interactive Natural Language-based Person SearchCode0
Mixture-of-Subspaces in Low-Rank AdaptationCode0
OsmLocator: locating overlapping scatter marks with a non-training generative perspectiveCode0
A simple neural network module for relational reasoningCode0
Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and SummarisationCode0
DecoderLens: Layerwise Interpretation of Encoder-Decoder TransformersCode0
HRIBench: Benchmarking Vision-Language Models for Real-Time Human Perception in Human-Robot InteractionCode0
How Well Do Multi-hop Reading Comprehension Models Understand Date Information?Code0
Bridging the Gap Between Open-Source and Proprietary LLMs in Table QACode0
How Well Do Large Language Models Understand Syntax? An Evaluation by Asking Natural Language QuestionsCode0
Declarative Question Answering over Knowledge Bases containing Natural Language Text with Answer Set ProgrammingCode0
Leveraging QA Datasets to Improve Generative Data AugmentationCode0
Out of Style: RAG's Fragility to Linguistic VariationCode0
A Simple Loss Function for Improving the Convergence and Accuracy of Visual Question Answering ModelsCode0
Show:102550
← PrevPage 182 of 217Next →
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