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 6301–6350 of 10817 papers

TitleStatusHype
Generating Justifications in a Spatial Question-Answering Dialogue System for a Blocks World—0
A Flexible and Extensible Framework for Multiple Answer Modes Question Answering—0
Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real ImagesCode1
Self-Attentive Constituency Parsing for UCCA-based Semantic Parsing—0
Breaking Down Questions for Outside-Knowledge VQA—0
Variational Disentangled Attention for Regularized Visual Dialog—0
Interpretable Multi-hop Reasoning for Forecasting Future Links on Temporal Knowledge GraphsCode0
Measuring CLEVRness: Black-box Testing of Visual Reasoning Models—0
Crossformer: Transformer with Alternated Cross-Layer Guidance—0
How Much Can CLIP Benefit Vision-and-Language Tasks?—0
GreaseLM: Graph REASoning Enhanced Language Models—0
VUT: Versatile UI Transformer for Multimodal Multi-Task User Interface Modeling—0
Contrastive Pre-training for Zero-Shot Information Retrieval—0
Privacy Policy Question Answering Assistant: A Query-Guided Extractive Summarization Approach—0
Text Simplification for Comprehension-based Question-AnsweringCode0
Single-dataset Experts for Multi-dataset Question AnsweringCode1
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases—0
FQuAD2.0: French Question Answering and knowing that you know nothing—0
VQA-MHUG: A Gaze Dataset to Study Multimodal Neural Attention in Visual Question Answering—0
Multimodal Integration of Human-Like Attention in Visual Question Answering—0
Context-guided Triple Matching for Multiple Choice Question Answering—0
SUper Team at SemEval-2016 Task 3: Building a feature-rich system for community question answering—0
Entity Linking Meets Deep Learning: Techniques and Solutions—0
Improving Question Answering Performance Using Knowledge Distillation and Active LearningCode0
More Than Reading Comprehension: A Survey on Datasets and Metrics of Textual Question Answering—0
SD-QA: Spoken Dialectal Question Answering for the Real WorldCode1
Investigating Post-pretraining Representation Alignment for Cross-Lingual Question AnsweringCode0
How to find a good image-text embedding for remote sensing visual question answering?—0
Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical OverlapCode0
BiRdQA: A Bilingual Dataset for Question Answering on Tricky Riddles—0
ParaShoot: A Hebrew Question Answering DatasetCode0
Towards Universal Dense Retrieval for Open-domain Question Answering—0
A Simple Approach to Jointly Rank Passages and Select Relevant Sentences in the OBQA Context—0
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering DatasetCode0
Recursively Summarizing Books with Human Feedback—0
Salience-Aware Event Chain Modeling for Narrative Understanding—0
K-AID: Enhancing Pre-trained Language Models with Domain Knowledge for Question Answering—0
RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing—0
What Would it Take to get Biomedical QA Systems into Practice?—0
Blindness to Modality Helps Entailment Graph MiningCode0
Does Vision-and-Language Pretraining Improve Lexical Grounding?Code1
Relation-Guided Pre-Training for Open-Domain Question Answering—0
Modality and Negation in Event ExtractionCode0
Emily: Developing An Emotion-affective Open-Domain Chatbot with Knowledge Graph-based Persona—0
Complex Temporal Question Answering on Knowledge GraphsCode1
Supervised Relation Classification as Two-way Span-Prediction—0
Machine Reading Comprehension: Generative or Extractive Reader?—0
Transformers Can Compose Skills To Solve Novel Problems Without Finetuning—0
Benchmarking Answer Verification Methods for Question Answering-Based Summarization Evaluation Metrics—0
CodeQA: A Question Answering Dataset for Source Code ComprehensionCode1
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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