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 8851–8900 of 10817 papers

TitleStatusHype
Generalizing Question Answering System with Pre-trained Language Model Fine-tuning—0
General-Purpose Robotic Navigation via LVLM-Orchestrated Perception, Reasoning, and Acting—0
General Table Question Answering via Answer-Formula Joint Generation—0
Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution—0
Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering—0
Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge—0
Generate, Transform, Answer: Question Specific Tool Synthesis for Tabular Data—0
Generating Answer Candidates for Quizzes and Answer-Aware Question Generators—0
Generating Answering Patterns from Factoid Arabic Questions—0
Generating clickbait spoilers with an ensemble of large language models—0
Generating Dialogue Agents via Automated Planning—0
Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidence—0
Generating Extractive Summaries of Scientific Paradigms—0
Generating Fact Checking Briefs—0
Generating Followup Questions for Interpretable Multi-hop Question Answering—0
Generating High Quality Proposition Banks for Multilingual Semantic Role Labeling—0
Generating Justifications in a Spatial Question-Answering Dialogue System for a Blocks World—0
Generating Lexicalization Patterns for Linked Open Data—0
Generating multiple-choice questions for medical question answering with distractors and cue-masking—0
Generating Natural Answers by Incorporating Copying and Retrieving Mechanisms in Sequence-to-Sequence Learning—0
Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention—0
Generating Natural Language Inference Chains—0
Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model—0
Generating Natural Questions from Images for Multimodal Assistants—0
Generating Questions from Wikidata Triples—0
Generating Rationales in Visual Question Answering—0
Generating Responses that Reflect Meta Information in User-Generated Question Answer Pairs—0
Generating Semantically Valid Adversarial Questions for TableQA—0
Generating Supplementary Travel Guides from Social Media—0
Generating Syntactic Paraphrases—0
Generating Synthetic Comparable Questions for News Articles—0
Generating titles for millions of browse pages on an e-Commerce site—0
Generating Training Data for Semantic Role Labeling based on Label Transfer from Linked Lexical Resources—0
Generating Triples with Adversarial Networks for Scene Graph Construction—0
Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact—0
Generative Context Pair Selection for Multi-hop Question Answering—0
Generative Distribution Prediction: A Unified Approach to Multimodal Learning—0
Generative Entity Networks: Disentangling Entitites and Attributes in Visual Scenes using Partial Natural Language Descriptions—0
Generative Language Models for Paragraph-Level Question Generation—0
Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitations—0
Generative Long-form Question Answering: Relevance, Faithfulness and Succinctness—0
Generative Pre-trained Transformer for Vietnamese Community-based COVID-19 Question Answering—0
Generative Question Answering: Learning to Answer the Whole Question—0
Generative Relation Linking for Question Answering over Knowledge Bases—0
Generative retrieval-augmented ontologic graph and multi-agent strategies for interpretive large language model-based materials design—0
Generative Stock Question Answering—0
Generative Visual Question Answering—0
Generic Attention-model Explainability by Weighted Relevance Accumulation—0
Genie: Achieving Human Parity in Content-Grounded Datasets Generation—0
GenRE: A Generative Model for Relation Extraction—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