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 8326–8350 of 10817 papers

TitleStatusHype
Risks and NLP Design: A Case Study on Procedural Document QA—0
RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning—0
Combining dependency information and generalization in a pattern-based approach to the classification of lexical-semantic relation instances—0
RLAS-BIABC: A Reinforcement Learning-Based Answer Selection Using the BERT Model Boosted by an Improved ABC Algorithm—0
RL-CSDia: Representation Learning of Computer Science Diagrams—0
R-LLaVA: Improving Med-VQA Understanding through Visual Region of Interest—0
RMLVQA: A Margin Loss Approach for Visual Question Answering With Language Biases—0
Generating clickbait spoilers with an ensemble of large language models—0
RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering—0
Ask Your Neurons: A Neural-based Approach to Answering Questions about Images—0
Generating Answering Patterns from Factoid Arabic Questions—0
Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets—0
Robotic Environmental State Recognition with Pre-Trained Vision-Language Models and Black-Box Optimization—0
Generating Natural Questions from Images for Multimodal Assistants—0
Robust Computational Semantics—0
Robust Computer Algebra, Theorem Proving, and Oracle AI—0
Robust Coreference Resolution and Entity Linking on Dialogues: Character Identification on TV Show Transcripts—0
Generating Rationales in Visual Question Answering—0
Robust Domain Adaptation for Relation Extraction via Clustering Consistency—0
Generating Responses that Reflect Meta Information in User-Generated Question Answer Pairs—0
Robust Few-shot Transfer Learning for Knowledge Base Question Answering with Unanswerable Questions—0
Robustifying Multi-hop QA through Pseudo-Evidentiality Training—0
Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization—0
Robust Machine Comprehension Models via Adversarial Training—0
Revisiting the Superficial Alignment Hypothesis—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