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 2901–2950 of 10817 papers

TitleStatusHype
Better RAG using Relevant Information GainCode0
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question AnsweringCode0
Learning to Perform Role-Filler Binding with Schematic KnowledgeCode0
Learning to Compose Neural Networks for Question AnsweringCode0
Adversarial Training with OCR Modality Perturbation for Scene-Text Visual Question AnsweringCode0
Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document MatchingCode0
Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word ProblemCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Discourse Representation Structure ParsingCode0
Learning Semantic Textual Similarity from ConversationsCode0
Learning from Explanations with Neural Execution TreeCode0
Discourse Comprehension: A Question Answering Framework to Represent Sentence ConnectionsCode0
Learning Representation Mapping for Relation Detection in Knowledge Base Question AnsweringCode0
Learning Recurrent Span Representations for Extractive Question AnsweringCode0
Learning Relation Entailment with Structured and Textual InformationCode0
Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question AnsweringCode0
Learning Representations of Sets through Optimized PermutationsCode0
Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context ExpansionCode0
Learning to Answer Biomedical Questions: OAQA at BioASQ 4BCode0
Learning to Deceive Knowledge Graph Augmented Models via Targeted PerturbationCode0
Learning to Represent Bilingual DictionariesCode0
Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question AnsweringCode0
Learning Distributed Representations of Texts and Entities from Knowledge BaseCode0
Learning from Lexical Perturbations for Consistent Visual Question AnsweringCode0
Learning content and context with language bias for Visual Question AnsweringCode0
Learning Conditioned Graph Structures for Interpretable Visual Question AnsweringCode0
Learning Intrinsic Sparse Structures within Long Short-Term MemoryCode0
Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning TaskCode0
Learning a Natural Language Interface with Neural ProgrammerCode0
Learning a Cost-Effective Annotation Policy for Question AnsweringCode0
Learned in Translation: Contextualized Word VectorsCode0
Leap-LSTM: Enhancing Long Short-Term Memory for Text CategorizationCode0
Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-TuningCode0
Beyond Language: Learning Commonsense from Images for ReasoningCode0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
Learning Musical Representations for Music Performance Question AnsweringCode0
Diffusion-Refined VQA Annotations for Semi-Supervised Gaze FollowingCode0
Difficult Task Yes but Simple Task No: Unveiling the Laziness in Multimodal LLMsCode0
BEEDS: Large-Scale Biomedical Event Extraction using Distant Supervision and Question AnsweringCode0
Differentiating Choices via Commonality for Multiple-Choice Question AnsweringCode0
Latent Entities Extraction: How to Extract Entities that Do Not Appear in the Text?Code0
Differential Attention for Visual Question AnsweringCode0
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language ModelsCode0
Latent Alignment and Variational AttentionCode0
Differentiable Outlier Detection Enable Robust Deep Multimodal AnalysisCode0
Large-scale Simple Question Answering with Memory NetworksCode0
Latent Alignment of Procedural Concepts in Multimodal RecipesCode0
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset ConstructionCode0
Large-scale Exploration of Neural Relation Classification ArchitecturesCode0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
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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