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 5251–5300 of 10817 papers

TitleStatusHype
LAVIS: A Library for Language-Vision Intelligence—0
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks—0
Pre-training for Information Retrieval: Are Hyperlinks Fully Explored?—0
Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual Question Answering—0
PaLI: A Jointly-Scaled Multilingual Language-Image Model—0
WildQA: In-the-Wild Video Question Answering—0
Prompt-based Conservation Learning for Multi-hop Question Answering—0
UIT-ViCoV19QA: A Dataset for COVID-19 Community-based Question Answering on Vietnamese LanguageCode0
MUST-VQA: MUltilingual Scene-text VQA—0
KSG: Knowledge and Skill Graph—0
Domain Adaptation for Question Answering via Question ClassificationCode0
MaXM: Towards Multilingual Visual Question AnsweringCode1
Knowledge Base Question Answering: A Semantic Parsing Perspective—0
PreSTU: Pre-Training for Scene-Text Understanding—0
Evaluation of Question Answering Systems: Complexity of judging a natural language—0
Activity report analysis with automatic single or multispan answer extraction—0
Pre-training image-language transformers for open-vocabulary tasks—0
Frame-Subtitle Self-Supervision for Multi-Modal Video Question Answering—0
Knowledge-enhanced Iterative Instruction Generation and Reasoning for Knowledge Base Question Answering—0
Improving the Cross-Lingual Generalisation in Visual Question AnsweringCode0
The BLue Amazon Brain (BLAB): A Modular Architecture of Services about the Brazilian Maritime TerritoryCode0
Query-focused Extractive Summarisation for Biomedical and COVID-19 Complex Question AnsweringCode0
An Empirical Study of End-to-End Video-Language Transformers with Masked Visual ModelingCode1
Interactive Question Answering Systems: Literature Review—0
Elaboration-Generating Commonsense Question Answering at ScaleCode0
Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering Over Knowledge Graphs—0
Zero-shot Event Causality Identification with Question Answering—0
Unsupervised Domain Adaptation on Question-Answering System with Conversation Data—0
A Visually-Aware Conversational Robot Receptionist—0
GRILLBot: A multi-modal conversational agent for complex real-world tasks—0
Why Do Neural Language Models Still Need Commonsense Knowledge to Handle Semantic Variations in Question Answering?Code1
Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal RetrievalCode1
Continuous QA Learning with Structured Prompts—0
A topic-aware graph neural network model for knowledge base updating—0
Faithful Reasoning Using Large Language Models—0
Efficient and Interpretable Neural Models for Entity Tracking—0
Exploring and Evaluating Personalized Models for Code Generation—0
Conversion of Legal Agreements into Smart Legal Contracts using NLP—0
Building the Intent Landscape of Real-World Conversational Corpora with Extractive Question-Answering Transformers—0
Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Tasks—0
Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA TaskCode1
FashionVQA: A Domain-Specific Visual Question Answering System—0
Bidirectional Contrastive Split Learning for Visual Question Answering—0
Evaluate Confidence Instead of Perplexity for Zero-shot Commonsense Reasoning—0
How good are deep models in understanding the generated images?—0
Prompting as Probing: Using Language Models for Knowledge Base ConstructionCode1
Unsupervised Question Answering via Answer DiversifyingCode0
Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question AnsweringCode1
Neuro-Symbolic Visual DialogCode0
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language TasksCode0
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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