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 2901–2925 of 10817 papers

TitleStatusHype
Bridge Damage Cause Estimation Using Multiple Images Based on Visual Question Answering—0
Answering Science Exam Questions Using Query Reformulation with Background Knowledge—0
Answering Science Exam Questions Using Query Rewriting with Background Knowledge—0
Answering Questions Requiring Cross-passage Evidence—0
Breaking Neural Network Scaling Laws with Modularity—0
Bridging the Language Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs—0
Breaking Language Barriers: A Question Answering Dataset for Hindi and Marathi—0
Acquiring Predicate Paraphrases from News Tweets—0
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations—0
Breaking Down Questions for Outside-Knowledge Visual Question Answering—0
Breaking Down Questions for Outside-Knowledge VQA—0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images—0
Breaking Character: Are Subwords Good Enough for MRLs After All?—0
Answering Questions from Multiple Documents -- the Role of Multi-Document Summarization—0
Aggregated Word Pair Features for Implicit Discourse Relation Disambiguation—0
Breaking Character: Are Subwords Good Enough for MRLs After All?—0
Breadth First Reasoning Graph for Multi-hop Question Answering—0
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM—0
Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models—0
A2P-MANN: Adaptive Attention Inference Hops Pruned Memory-Augmented Neural Networks—0
Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Models—0
BrainChat: Decoding Semantic Information from fMRI using Vision-language Pretrained Models—0
Brahmi-Net: A transliteration and script conversion system for languages of the Indian subcontinent—0
Answering Product-related Questions with Heterogeneous Information—0
BQA: Body Language Question Answering Dataset for Video Large Language Models—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