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

Showing 15511600 of 10817 papers

TitleStatusHype
Ditch the Gold Standard: Re-evaluating Conversational Question AnsweringCode1
Making Retrieval-Augmented Language Models Robust to Irrelevant ContextCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
Towards General Natural Language Understanding with Probabilistic WorldbuildingCode1
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence AnnotationCode1
Distilled Dual-Encoder Model for Vision-Language UnderstandingCode1
Answering Complex Open-Domain Questions with Multi-Hop Dense RetrievalCode1
Diversify Question Generation with Retrieval-Augmented Style TransferCode1
MapperGPT: Large Language Models for Linking and Mapping EntitiesCode1
Block Pruning For Faster TransformersCode1
CBench: Towards Better Evaluation of Question Answering Over Knowledge GraphsCode1
MarkQA: A large scale KBQA dataset with numerical reasoningCode1
DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question AnsweringCode1
Disentangling 3D Prototypical Networks For Few-Shot Concept LearningCode1
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question AnsweringCode1
Match-Ignition: Plugging PageRank into Transformer for Long-form Text MatchingCode1
Discovering Spatio-Temporal Rationales for Video Question AnsweringCode1
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence AnnotationCode1
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and IntentsCode1
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset BiasesCode1
Agentic Keyframe Search for Video Question AnsweringCode1
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No QuestionsCode1
Boosting Audio Visual Question Answering via Key Semantic-Aware CuesCode1
Measuring Conversational Uptake: A Case Study on Student-Teacher InteractionsCode1
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge GraphsCode1
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning StrategiesCode1
DialSim: A Real-Time Simulator for Evaluating Long-Term Multi-Party Dialogue Understanding of Conversational AgentsCode1
MedBLIP: Bootstrapping Language-Image Pre-training from 3D Medical Images and TextsCode1
Differentiable Reasoning on Large Knowledge Bases and Natural LanguageCode1
MedCoT: Medical Chain of Thought via Hierarchical ExpertCode1
Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual NoiseCode1
Ascle: A Python Natural Language Processing Toolkit for Medical Text GenerationCode1
Dialog Inpainting: Turning Documents into DialogsCode1
DEXTER: A Benchmark for open-domain Complex Question Answering using LLMsCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
Detecting Hate Speech in Multi-modal MemesCode1
MemeCap: A Dataset for Captioning and Interpreting MemesCode1
Memory-Based Model Editing at ScaleCode1
MemSum-DQA: Adapting An Efficient Long Document Extractive Summarizer for Document Question AnsweringCode1
DeVLBert: Learning Deconfounded Visio-Linguistic RepresentationsCode1
MetaGen Blended RAG: Higher Accuracy for Domain-Specific Q&A Without Fine-TuningCode1
Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtCode1
Meta-Learning Online Adaptation of Language ModelsCode1
METGEN: A Module-Based Entailment Tree Generation Framework for Answer ExplanationCode1
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language ModelsCode1
Answering Questions on COVID-19 in Real-TimeCode1
MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge RepresentationCode1
A Survey on Efficient Vision-Language ModelsCode1
Designing a Minimal Retrieve-and-Read System for Open-Domain Question AnsweringCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94Unverified
2FPNet (ensemble)EM90.87Unverified
3IE-NetV2 (ensemble)EM90.86Unverified
4SA-Net on Albert (ensemble)EM90.72Unverified
5SA-Net-V2 (ensemble)EM90.68Unverified
6FPNet (ensemble)EM90.6Unverified
7Retro-Reader (ensemble)EM90.58Unverified
8EntitySpanFocusV2 (ensemble)EM90.52Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49Unverified
10EntitySpanFocus+AT (ensemble)EM90.45Unverified