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 3901–3925 of 10817 papers

TitleStatusHype
Finely Tuned, 2 Billion Token Based Word Embeddings for Portuguese—0
FINET: Context-Aware Fine-Grained Named Entity Typing—0
GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation—0
Domain Adaptation with Active Learning for Coreference Resolution—0
Domain Adaptation of VLM for Soccer Video Understanding—0
Beyond Attention: Toward Machines with Intrinsic Higher Mental States—0
Classifier Combination Approach for Question Classification for Bengali Question Answering System—0
Finetuning Language Models to Emit Linguistic Expressions of Uncertainty—0
Fine-Tuning Large Language Models and Evaluating Retrieval Methods for Improved Question Answering on Building Codes—0
Fine-Tuning Large Language Models for Answering Programming Questions with Code Snippets—0
Classifying Questions in Question Answering System Using Finite State Machines with a Simple Learning Approach—0
Fine-tuning Large Language Models with Sequential Instructions—0
Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths—0
Fine-Tuning LLMs for Reliable Medical Question-Answering Services—0
Fine-tuning Multi-hop Question Answering with Hierarchical Graph Network—0
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages—0
Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual Question Answering—0
Fine-tuning Smaller Language Models for Question Answering over Financial Documents—0
Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints—0
Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints—0
Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks—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
Annotating Educational Questions for Student Response Analysis—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