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 4651–4675 of 10817 papers

TitleStatusHype
Curriculum Learning Effectively Improves Low Data VQA—0
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level—0
Interpreting Consumer Health Questions: The Role of Anaphora and Ellipsis—0
Curriculum Learning Based on Reward Sparseness for Deep Reinforcement Learning of Task Completion Dialogue Management—0
Automated Extraction of Number of Subjects in Randomised Controlled Trials—0
Curio SmartChat : A system for Natural Language Question Answering for Self-Paced K-12 Learning—0
CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning—0
An Automatic and Cost-Efficient Peer-Review Framework for Language Generation Evaluation—0
CUNI Submission to MRL 2023 Shared Task on Multi-lingual Multi-task Information Retrieval—0
Cultural Palette: Pluralising Culture Alignment via Multi-agent Palette—0
Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks—0
An automatically discovered chain-of-thought prompt generalizes to novel models and datasets—0
Automated Discovery of Mathematical Definitions in Text—0
A Cognitive Evaluation Benchmark of Image Reasoning and Description for Large Vision-Language Models—0
Interpreting Anaphoric Shell Nouns using Antecedents of Cataphoric Shell Nouns as Training Data—0
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension—0
CUB: Benchmarking Context Utilisation Techniques for Language Models—0
Automated CVE Analysis: Harnessing Machine Learning In Designing Question-Answering Models For Cybersecurity Information Extraction—0
CTRL-O: Language-Controllable Object-Centric Visual Representation Learning—0
CTPs: Contextual Temporal Profiles for Time Scoping Facts using State Change Detection—0
An Automated Question-Answering Framework Based on Evolution Algorithm—0
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering—0
Automated Construction of Theme-specific Knowledge Graphs—0
CT2C-QA: Multimodal Question Answering over Chinese Text, Table and Chart—0
CS-VQA: Visual Question Answering with Compressively Sensed Images—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