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 8651–8700 of 10817 papers

TitleStatusHype
Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters—0
Blindfold Baselines for Embodied QACode0
An Introductory Survey on Attention Mechanisms in NLP Problems—0
CQASUMM: Building References for Community Question Answering Summarization CorporaCode0
Holistic Multi-modal Memory Network for Movie Question Answering—0
ReDecode Framework for Iterative Improvement in Paraphrase Generation—0
Encoding Implicit Relation Requirements for Relation Extraction: A Joint Inference Approach—0
Adversarial Sampling and Training for Semi-Supervised Information Retrieval—0
Towards Compositional Distributional Discourse Analysis—0
Compositional Language Understanding with Text-based Relational ReasoningCode0
Parser Extraction of Triples in Unstructured TextCode0
Improving Span-based Question Answering Systems with Coarsely Labeled Data—0
ATP: Directed Graph Embedding with Asymmetric Transitivity PreservationCode0
Learning to Rank Query Graphs for Complex Question Answering over Knowledge GraphsCode0
Zero-Shot Transfer VQA Dataset—0
SIRIUS-LTG: An Entity Linking Approach to Fact Extraction and Verification—0
Zero-shot Relation Classification as Textual Entailment—0
Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension—0
Semantic role labeling tools for biomedical question answering: a study of selected tools on the BioASQ datasets—0
Team SWEEPer: Joint Sentence Extraction and Fact Checking with Pointer Networks—0
UNCC QA: Biomedical Question Answering system—0
Shifting the Baseline: Single Modality Performance on Visual Navigation & QA—0
Exploiting Attention to Reveal Shortcomings in Memory Models—0
On the Generation of Medical Question-Answer Pairs—0
MindLab Neural Network Approach at BioASQ 6B—0
Retrieve and Re-rank: A Simple and Effective IR Approach to Simple Question Answering over Knowledge Graphs—0
Results of the sixth edition of the BioASQ Challenge—0
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering—0
Extraction Meets Abstraction: Ideal Answer Generation for Biomedical Questions—0
CogCompTime: A Tool for Understanding Time in Natural Language—0
Frame- and Entity-Based Knowledge for Common-Sense Argumentative ReasoningCode0
An Interactive Web-Interface for Visualizing the Inner Workings of the Question Answering LSTM—0
Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering—0
AttentionMeSH: Simple, Effective and Interpretable Automatic MeSH Indexer—0
How much should you ask? On the question structure in QA systems.—0
Ontology-Based Retrieval \& Neural Approaches for BioASQ Ideal Answer Generation—0
Expletives in Universal Dependency TreebanksCode0
Automatic Opinion Question GenerationCode0
An Adaption of BIOASQ Question Answering dataset for Machine Reading systems by Manual Annotations of Answer Spans.—0
Explaining non-linear Classifier Decisions within Kernel-based Deep Architectures—0
Macquarie University at BioASQ 6b: Deep learning and deep reinforcement learning for query-based summarisation—0
Interactive Instance-based Evaluation of Knowledge Base Question AnsweringCode0
OpenKE: An Open Toolkit for Knowledge EmbeddingCode0
Preferred Answer Selection in Stack Overflow: Better Text Representations ... and Metadata, Metadata, Metadata—0
Improving Machine Reading Comprehension with General Reading StrategiesCode0
On the Effectiveness of Minimal Context Selection for Robust Question Answering—0
Compositional Attention Networks for Interpretability in Natural Language Question Answering—0
ReviewQA: a relational aspect-based opinion reading dataset—0
Do Explanations make VQA Models more Predictable to a Human?—0
TallyQA: Answering Complex Counting QuestionsCode0
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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