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 9201–9225 of 10817 papers

TitleStatusHype
Importance sampling for unbiased on-demand evaluation of knowledge base population—0
Improved Alignment of Modalities in Large Vision Language Models—0
Improved and Efficient Conversational Slot Labeling through Question Answering—0
Improved and Efficient Conversational Slot Labeling through Question Answering—0
Improved Baselines for Data-efficient Perceptual Augmentation of LLMs—0
Improved Bilinear Pooling with CNNs—0
Improved CCG Parsing with Semi-supervised Supertagging—0
Improve Dense Passage Retrieval with Entailment Tuning—0
Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting—0
Improved LLM Agents for Financial Document Question Answering—0
Improved Neural Relation Detection for Knowledge Base Question Answering—0
Improved Recognition and Normalisation of Polish Temporal Expressions—0
Improved Representation Learning for Question Answer Matching—0
Improvement of VerbNet-like resources by frame typing—0
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding—0
Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection—0
Improving Automatic VQA Evaluation Using Large Language Models—0
Improving Biomedical Information Retrieval with Neural Retrievers—0
Improving Chinese Semantic Role Labeling using High-quality Surface and Deep Case Frames—0
Improving Clinical Diagnosis Inference through Integration of Structured and Unstructured Knowledge—0
Improving Clinical Question Answering with Multi-Task Learning: A Joint Approach for Answer Extraction and Medical Categorization—0
Improving Commonsense Question Answering by Graph-based Iterative Retrieval over Multiple Knowledge Sources—0
Improving Conditioning in Context-Aware Sequence to Sequence Models—0
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization—0
Improving Cross-lingual Representation for Semantic Retrieval with Code-switching—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