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 2001–2050 of 10817 papers

TitleStatusHype
Towards Continual Knowledge Learning of Language ModelsCode1
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning StrategiesCode1
Clover: Towards A Unified Video-Language Alignment and Fusion ModelCode1
Towards Fine-grained Causal Reasoning and QACode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question AnsweringCode1
AmbigQA: Answering Ambiguous Open-domain QuestionsCode1
CDLM: Cross-Document Language ModelingCode1
Clues Before Answers: Generation-Enhanced Multiple-Choice QACode1
Differentiable Reasoning on Large Knowledge Bases and Natural LanguageCode1
A Simple LLM Framework for Long-Range Video Question-AnsweringCode1
Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a SummaryCode1
LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language ModelsCode1
Toward Subgraph-Guided Knowledge Graph Question Generation with Graph Neural NetworksCode1
Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under DiscussionCode1
CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language TransformersCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic EventsCode1
Detecting Hate Speech in Multi-modal MemesCode1
Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training DataCode1
Training Language Models to Generate Text with Citations via Fine-grained RewardsCode1
DeVLBert: Learning Deconfounded Visio-Linguistic RepresentationsCode1
Detecting and Preventing Hallucinations in Large Vision Language ModelsCode1
DEXTER: A Benchmark for open-domain Complex Question Answering using LLMsCode1
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language ModelsCode1
Transformers to Learn Hierarchical Contexts in Multiparty Dialogue for Span-based Question AnsweringCode1
Dense Passage Retrieval for Open-Domain Question AnsweringCode1
TRAR: Routing the Attention Spans in Transformer for Visual Question AnsweringCode1
Asking Clarification Questions to Handle Ambiguity in Open-Domain QACode1
TreeHop: Generate and Filter Next Query Embeddings Efficiently for Multi-hop Question AnsweringCode1
Densely Connected Attention Propagation for Reading ComprehensionCode1
Describe Anything Model for Visual Question Answering on Text-rich ImagesCode1
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM CollaborationCode1
TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic TasksCode1
A Dataset and Baselines for Visual Question Answering on ArtCode1
Coarse-to-Fine Vision-Language Pre-training with Fusion in the BackboneCode1
Asking Questions the Human Way: Scalable Question-Answer Generation from Text CorpusCode1
T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Mixed Large Language Model Signals for Science Question AnsweringCode1
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic SurgeryCode1
COBRA: Contrastive Bi-Modal Representation AlgorithmCode1
TVLT: Textless Vision-Language TransformerCode1
TWEAC: Transformer with Extendable QA Agent ClassifiersCode1
Dense Hierarchical Retrieval for Open-Domain Question AnsweringCode1
UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language ModelsCode1
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document AnalysisCode1
CodeQA: A Question Answering Dataset for Source Code ComprehensionCode1
Designing a Minimal Retrieve-and-Read System for Open-Domain Question AnsweringCode1
Dialog Inpainting: Turning Documents into DialogsCode1
DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoningCode1
DeFormer: Decomposing Pre-trained Transformers for Faster Question AnsweringCode1
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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