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 4351–4375 of 10817 papers

TitleStatusHype
CLEAR: Contrastive Learning for Sentence Representation—0
AsdKB: A Chinese Knowledge Base for the Early Screening and Diagnosis of Autism Spectrum Disorder—0
FinMath: Injecting a Tree-structured Solver for Question Answering over Financial Reports—0
FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models—0
Fine-tuning vs From Scratch: Do Vision & Language Models Have Similar Capabilities on Out-of-Distribution Visual Question Answering?—0
CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering—0
A scoping review on multimodal deep learning in biomedical images and texts—0
Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks—0
Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints—0
Clause-based Discourse Segmentation of Arabic Texts—0
Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints—0
Fine-tuning Smaller Language Models for Question Answering over Financial Documents—0
Claude 3.5 Sonnet Model Card Addendum—0
ASBERT: Siamese and Triplet network embedding for open question answering—0
Aligning Verb Senses in Two Italian Lexical Semantic Resources—0
Adapting Pre-trained Generative Models for Extractive Question Answering—0
Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual Question Answering—0
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages—0
Class-Imbalanced-Aware Adaptive Dataset Distillation for Scalable Pretrained Model on Credit Scoring—0
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
Fine-tuning Multi-hop Question Answering with Hierarchical Graph Network—0
Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths—0
Fine-Tuning LLMs for Reliable Medical Question-Answering Services—0
Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths—0
Fine-tuning Large Language Models with Sequential Instructions—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