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 2801–2850 of 10817 papers

TitleStatusHype
Learning Visual Question Answering by Bootstrapping Hard AttentionCode0
Learning What is Essential in QuestionsCode0
Learning to Skim TextCode0
Beneath Surface Similarity: Large Language Models Make Reasonable Scientific Analogies after Structure AbductionCode0
Learning to Search in Long Documents Using Document StructureCode0
Learning to Rank Query Graphs for Complex Question Answering over Knowledge GraphsCode0
Visuo-Linguistic Question Answering (VLQA) ChallengeCode0
Learning to Represent Bilingual DictionariesCode0
Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMsCode0
Learning to Follow Object-Centric Image Editing Instructions FaithfullyCode0
Benchmarking Vision-Language Contrastive Methods for Medical Representation LearningCode0
Learning to Generalize for Cross-domain QACode0
Learning to Model and Ignore Dataset Bias with Mixed Capacity EnsemblesCode0
Distributed Representations of Sentences and DocumentsCode0
Distributed Associative Memory Network with Memory Refreshing LossCode0
Learning to Deceive Knowledge Graph Augmented Models via Targeted PerturbationCode0
AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective IntelligenceCode0
Learning to Compose Neural Networks for Question AnsweringCode0
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question AnsweringCode0
Learning to Exploit Structured Resources for Lexical InferenceCode0
Learning to Perform Role-Filler Binding with Schematic KnowledgeCode0
Learning from Explanations with Neural Execution TreeCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Learning to Answer Biomedical Questions: OAQA at BioASQ 4BCode0
LEGAL-UQA: A Low-Resource Urdu-English Dataset for Legal Question AnsweringCode0
Leveraging Large Language Models in Code Question Answering: Baselines and IssuesCode0
Benchmarking Multimodal RAG through a Chart-based Document Question-Answering Generation FrameworkCode0
DisGeM: Distractor Generation for Multiple Choice Questions with Span MaskingCode0
An Improved Attention for Visual Question AnsweringCode0
Learning Recurrent Span Representations for Extractive Question AnsweringCode0
Benchmarking Long-tail Generalization with Likelihood SplitsCode0
Learning Intrinsic Sparse Structures within Long Short-Term MemoryCode0
Benchmarking LLM-based Relevance Judgment MethodsCode0
Learning Musical Representations for Music Performance Question AnsweringCode0
Learning Relation Entailment with Structured and Textual InformationCode0
A Nil-Aware Answer Extraction Framework for Question AnsweringCode0
Discriminative Information Retrieval for Question Answering Sentence SelectionCode0
Discrete Subgraph Sampling for Interpretable Graph based Visual Question AnsweringCode0
Discrete-State Variational Autoencoders for Joint Discovery and Factorization of RelationsCode0
Learning Distributed Representations of Texts and Entities from Knowledge BaseCode0
Discovery and Recognition of Formula Concepts using Machine LearningCode0
Learning to Select from Multiple OptionsCode0
Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question AnsweringCode0
Diversity Enhanced Narrative Question Generation for StorybooksCode0
Learning from Lexical Perturbations for Consistent Visual Question AnsweringCode0
DCR: Divide-and-Conquer Reasoning for Multi-choice Question Answering with LLMsCode0
Learning Representation Mapping for Relation Detection in Knowledge Base Question AnsweringCode0
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question AnsweringCode0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning TaskCode0
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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