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 6651–6700 of 10817 papers

TitleStatusHype
Semantic Aligned Multi-modal Transformer for Vision-LanguageUnderstanding: A Preliminary Study on Visual QA—0
CLEVR\_HYP: A Challenge Dataset and Baselines for Visual Question Answering with Hypothetical Actions over ImagesCode0
NAMER: A Node-Based Multitasking Framework for Multi-Hop Knowledge Base Question AnsweringCode0
Adaptable and Interpretable Neural MemoryOver Symbolic Knowledge—0
MM-AVS: A Full-Scale Dataset for Multi-modal Summarization—0
Breadth First Reasoning Graph for Multi-hop Question Answering—0
MIMOQA: Multimodal Input Multimodal Output Question Answering—0
Discovering Better Model Architectures for Medical Query Understanding—0
SPARTQA: A Textual Question Answering Benchmark for Spatial ReasoningCode1
AVA: an Automatic eValuation Approach for Question Answering Systems—0
An Emotional Comfort Framework for Improving User Satisfaction in E-Commerce Customer Service Chatbots—0
Improving Zero-Shot Cross-lingual Transfer for Multilingual Question Answering over Knowledge Graph—0
If You Want to Go Far Go Together: Unsupervised Joint Candidate Evidence Retrieval for Multi-hop Question Answering—0
Goodwill Hunting: Analyzing and Repurposing Off-the-Shelf Named Entity Linking Systems—0
Explainable Multi-hop Verbal Reasoning Through Internal Monologue—0
EaSe: A Diagnostic Tool for VQA based on Answer DiversityCode0
Looking Beyond Sentence-Level Natural Language Inference for Question Answering and Text Summarization—0
Worldly Wise (WoW) - Cross-Lingual Knowledge Fusion for Fact-based Visual Spoken-Question Answering—0
DeCEMBERT: Learning from Noisy Instructional Videos via Dense Captions and Entropy MinimizationCode1
Using Integrated Gradients and Constituency Parse Trees to explain Linguistic Acceptability learnt by BERT—0
RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering—0
Game-theoretic Vocabulary Selection via the Shapley Value and Banzhaf Index—0
Parameter-Efficient Neural Question Answering Models via Graph-Enriched Document Representations—0
DoT: An efficient Double Transformer for NLP tasks with tables—0
Question-aware Transformer Models for Consumer Health Question Summarization—0
What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks?Code0
CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction—0
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument MiningCode1
Iterative Hierarchical Attention for Answering Complex Questions over Long Documents—0
Adversarial VQA: A New Benchmark for Evaluating the Robustness of VQA Models—0
A Coarse to Fine Question Answering System based on Reinforcement Learning—0
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition—0
A Semantic-based Method for Unsupervised Commonsense Question AnsweringCode1
Corpus-Based Paraphrase Detection Experiments and Review—0
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods—0
A Compression-Compilation Framework for On-mobile Real-time BERT Applications—0
Pre-training Universal Language Representation—0
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical ReasoningCode1
LPF: A Language-Prior Feedback Objective Function for De-biased Visual Question AnsweringCode0
Is Sluice Resolution really just Question Answering?—0
SciFive: a text-to-text transformer model for biomedical literatureCode1
Towards More Equitable Question Answering Systems: How Much More Data Do You Need?Code0
Feature extraction and evaluation for BioMedical Question Answering—0
ByT5: Towards a token-free future with pre-trained byte-to-byte modelsCode1
Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering—0
MixQA: Embedding and Answer Mixing for Question Answering—0
CoSQA: 20,000+ Web Queries for Code Search and Question AnsweringCode1
Improve Query Focused Abstractive Summarization by Incorporating Answer RelevanceCode0
Dynamic Semantic Graph Construction and Reasoning for Explainable Multi-hop Science Question AnsweringCode1
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions—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