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 6276–6300 of 10817 papers

TitleStatusHype
MFORT-QA: Multi-hop Few-shot Open Rich Table Question Answering—0
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension—0
Learning and Evaluating General Linguistic Intelligence—0
Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification—0
Learning Analogy-Preserving Sentence Embeddings for Answer Selection—0
Learning Adaptable Patterns for Passage Reranking—0
MIA 2022 Shared Task Submission: Leveraging Entity Representations, Dense-Sparse Hybrids, and Fusion-in-Decoder for Cross-Lingual Question Answering—0
Differentiable End-to-End Program Executor for Sample and Computationally Efficient VQA—0
BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for Multi-hop Question Answering—0
MICRON: Multigranular Interaction for Contextualizing RepresentatiON in Non-factoid Question Answering—0
Microsoft AI Challenge India 2018: Learning to Rank Passages for Web Question Answering with Deep Attention Networks—0
An Evaluation of Recent Neural Sequence Tagging Models in Turkish Named Entity Recognition—0
Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary—0
Miko Team: Deep Learning Approach for Legal Question Answering in ALQAC 2022—0
Mildly Non-Projective Dependency Grammar—0
Different Contexts Lead to Different Word Embeddings—0
DIF: A Framework for Benchmarking and Verifying Implicit Bias in LLMs—0
DIESEL -- Dynamic Inference-Guidance via Evasion of Semantic Embeddings in LLMs—0
Lean Question Answering over Freebase from Scratch—0
LeanContext: Cost-Efficient Domain-Specific Question Answering Using LLMs—0
Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation—0
DIEM: Decomposition-Integration Enhancing Multimodal Insights—0
BDIQA: A New Dataset for Video Question Answering to Explore Cognitive Reasoning through Theory of Mind—0
An Evaluation of Image-Based Verb Prediction Models against Human Eye-Tracking Data—0
Adversarial Representation Learning for Text-to-Image Matching—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