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 3351–3375 of 10817 papers

TitleStatusHype
CAD -- Contextual Multi-modal Alignment for Dynamic AVQA—0
Enhancing Temporal Sensitivity and Reasoning for Time-Sensitive Question Answering—0
A Novel Approach for Automatic Bengali Question Answering System using Semantic Similarity Analysis—0
Enhancing Temporal Understanding in LLMs for Semi-structured Tables—0
CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability—0
Any-language frame-semantic parsing—0
Bidirectional Long Short-Term Memory Networks for Relation Classification—0
Enhancing Trust in Large Language Models with Uncertainty-Aware Fine-Tuning—0
AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset—0
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines—0
CALF: Benchmarking Evaluation of LFQA Using Chinese Examinations—0
Bidirectional Language Models Are Also Few-shot Learners—0
A Constituent-Centric Neural Architecture for Reading Comprehension—0
Fair comparison of knowledge graphs for question answering—0
FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering—0
ENIAM: Categorial Syntactic-Semantic Parser for Polish—0
DSNDM: Deep Siamese Neural Discourse Model with Attention for Text Pairs Categorization and Ranking—0
Enriching Knowledge Bases with Interesting Negative Statements—0
DSC-IITISM at FinCausal 2021: Combining POS tagging with Attention-based Contextual Representations for Identifying Causal Relationships in Financial Documents—0
Ensemble ALBERT and RoBERTa for Span Prediction in Question Answering—0
Calibrating Sequence likelihood Improves Conditional Language Generation—0
Ensemble approach for natural language question answering problem—0
Ensemble Transfer Learning for Multilingual Coreference Resolution—0
Calibrating Structured Output Predictors for Natural Language Processing—0
FACTIFY-5WQA: 5W Aspect-based Fact Verification through Question Answering—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