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 6026–6050 of 10817 papers

TitleStatusHype
Disease Identification From Unstructured User Input—0
Learning to Collaborate for Question Answering and Asking—0
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training—0
Making Language Models Robust Against Negation—0
Learning to Clarify by Reinforcement Learning Through Reward-Weighted Fine-Tuning—0
Making question answering more robust through relevant context selection—0
Discriminating between Similar Languages with Word-level Convolutional Neural Networks—0
Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime—0
Malayalam Clause Boundary Identifier: Annotation and Evaluation—0
Benchmarking Large Multimodal Models for Ophthalmic Visual Question Answering with OphthalWeChat—0
DiscreteSLU: A Large Language Model with Self-Supervised Discrete Speech Units for Spoken Language Understanding—0
Discrete Cosine Transform as Universal Sentence Encoder—0
Learning to Answer Questions from Wikipedia Infoboxes—0
Learning to Answer Questions From Image Using Convolutional Neural Network—0
Benchmarking Large Language Models in Complex Question Answering Attribution using Knowledge Graphs—0
An Exploration of Data Augmentation and RNN Architectures for Question Ranking in Community Question Answering—0
Advice for Diabetes Self-Management by ChatGPT Models: Challenges and Recommendations—0
A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis—0
Learning to answer questions—0
Learning to Answer Multilingual and Code-Mixed Questions—0
Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds—0
Discovering the Real Association: Multimodal Causal Reasoning in Video Question Answering—0
Benchmarking Large Language Models for Conversational Question Answering in Multi-instructional Documents—0
Learning to Answer Ambiguous Questions with Knowledge Graph—0
Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network—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