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 3701–3750 of 10817 papers

TitleStatusHype
DoQA -- Accessing Domain-Specific FAQs via Conversational QA—0
Annotating Zero Anaphora for Question Answering—0
GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation—0
GenDec: A robust generative Question-decomposition method for Multi-hop reasoning—0
General Embedding vs. Task-Specific Embedding: A Comparative Approach to Enhancing NLP Performance—0
Generalized Hadamard-Product Fusion Operators for Visual Question Answering—0
Generating Dialogue Agents via Automated Planning—0
Generating Training Data for Semantic Role Labeling based on Label Transfer from Linked Lexical Resources—0
Character-Aware Neural Networks for Arabic Named Entity Recognition for Social Media—0
How Additional Knowledge can Improve Natural Language Commonsense Question Answering?—0
Don’t Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering—0
Beyond Plain Spatial Knowledge: Determining Where Entities Are and Are Not Located, and For How Long—0
Don't Read Too Much into It: Adaptive Computation for Open-Domain Question Answering—0
Annotating the Focus of Negation in Japanese Text—0
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis—0
Annotating Relation Inference in Context via Question Answering—0
Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan—0
Do not let the history haunt you: Mitigating Compounding Errors in Conversational Question Answering—0
Extending Neural Question Answering with Linguistic Input Features—0
Extending the Frontier of ChatGPT: Code Generation and Debugging—0
EKTVQA: Generalized use of External Knowledge to empower Scene Text in Text-VQA—0
Extracting Context-Rich Entailment Rules from Wikipedia Revision History—0
Do not let the history haunt you -- Mitigating Compounding Errors in Conversational Question Answering—0
Extracting Definitions and Hypernym Relations relying on Syntactic Dependencies and Support Vector Machines—0
Extracting Emotion Phrases from Tweets using BART—0
Extracting Factual Min/Max Age Information from Clinical Trial Studies—0
Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs—0
Extracting Opinion Expressions with semi-Markov Conditional Random Fields—0
Extracting Procedural Knowledge from Technical Documents—0
Extracting Psychological Indicators Using Question Answering—0
Extracting Semantics from Maintenance Records—0
Extracting Spatial Entities and Relations in Korean Text—0
Extracting Time Expressions from Clinical Text—0
Extracting Training Data from Document-Based VQA Models—0
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity—0
GEMeX-ThinkVG: Towards Thinking with Visual Grounding in Medical VQA via Reinforcement Learning—0
Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs—0
Extraction of Product Specifications from the Web -- Going Beyond Tables and Lists—0
Extractive Headline Generation Based on Learning to Rank for Community Question Answering—0
Extractive NarrativeQA with Heuristic Pre-Training—0
Extractive Question Answering on Queries in Hindi and Tamil—0
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution—0
Annotating Question Decomposition on Complex Medical Questions—0
GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performance—0
Extrinsic Evaluation of Machine Translation Metrics—0
Do Multi-Hop Question Answering Systems Know How to Answer the Single-Hop Sub-Questions?—0
EyeFound: A Multimodal Generalist Foundation Model for Ophthalmic Imaging—0
Look Before You Decide: Prompting Active Deduction of MLLMs for Assumptive Reasoning—0
Annotating Opinions in German Political News—0
DOMLIN at SemEval-2019 Task 8: Automated Fact Checking exploiting Ratings in Community Question Answering Forums—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