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 5601–5650 of 10817 papers

TitleStatusHype
Semantic-aware Dynamic Retrospective-Prospective Reasoning for Event-level Video Question Answering—0
Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering—0
Learning to Generalize for Cross-domain QACode0
SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative ExamplesCode0
HPE:Answering Complex Questions over Text by Hybrid Question Parsing and Execution—0
Improving Small Language Models on PubMedQA via Generative Data Augmentation—0
Implications of Deep Circuits in Improving Quality of Quantum Question Answering—0
When Giant Language Brains Just Aren't Enough! Domain Pizzazz with Knowledge Sparkle Dust—0
A Memory Model for Question Answering from Streaming Data Supported by Rehearsal and Anticipation of Coreference Information—0
Overinformative Question Answering by Humans and Machines—0
Think Twice: Measuring the Efficiency of Eliminating Prediction Shortcuts of Question Answering ModelsCode0
Long-Tailed Question Answering in an Open World—0
Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks—0
Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answering—0
A Glimpse in ChatGPT Capabilities and its impact for AI research—0
Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense KnowledgeCode0
Unsupervised Dense Retrieval Training with Web AnchorsCode0
MAUPQA: Massive Automatically-created Polish Question Answering Dataset—0
Large Language Models Need Holistically Thought in Medical Conversational QACode0
Large Language Model Programs—0
Event Knowledge Incorporation with Posterior Regularization for Event-Centric Question AnsweringCode0
A Frustratingly Easy Improvement for Position Embeddings via Random Padding—0
Knowledge-enhanced Agents for Interactive Text Games—0
SkillQG: Learning to Generate Question for Reading Comprehension Assessment—0
FACTIFY-5WQA: 5W Aspect-based Fact Verification through Question Answering—0
OpenViVQA: Task, Dataset, and Multimodal Fusion Models for Visual Question Answering in VietnameseCode0
Adaptive loose optimization for robust question answeringCode0
From Parse-Execute to Parse-Execute-Refine: Improving Semantic Parser for Complex Question Answering over Knowledge Base—0
NewsQuote: A Dataset Built on Quote Extraction and Attribution for Expert Recommendation in Fact-CheckingCode0
Multi-View Graph Representation Learning for Answering Hybrid Numerical Reasoning QuestionCode0
Faithful Question Answering with Monte-Carlo PlanningCode0
DomainInv: Domain Invariant Fine Tuning and Adversarial Label Correction For QA Domain Adaptation—0
ANetQA: A Large-scale Benchmark for Fine-grained Compositional Reasoning over Untrimmed VideosCode0
An automatically discovered chain-of-thought prompt generalizes to novel models and datasets—0
VideoOFA: Two-Stage Pre-Training for Video-to-Text Generation—0
Analysis of Visual Question Answering Algorithms with attention model—0
Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing—0
Pay More Attention to Relation Exploration for Knowledge Base Question Answering—0
AttenWalker: Unsupervised Long-Document Question Answering via Attention-based Graph WalkingCode0
Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings—0
Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime—0
MAFiD: Moving Average Equipped Fusion-in-Decoder for Question Answering over Tabular and Textual DataCode0
CHIC: Corporate Document for Visual question Answering—0
Multimodal Graph Transformer for Multimodal Question Answering—0
Prompt Engineering for Healthcare: Methodologies and Applications—0
ChatGPT in the Classroom: An Analysis of Its Strengths and Weaknesses for Solving Undergraduate Computer Science Questions—0
Analyzing Vietnamese Legal Questions Using Deep Neural Networks with Biaffine ClassifiersCode0
q2d: Turning Questions into Dialogs to Teach Models How to Search—0
HeySQuAD: A Spoken Question Answering DatasetCode0
Semantic Compression With Large Language Models—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