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 2851–2875 of 10817 papers

TitleStatusHype
SMART-RAG: Selection using Determinantal Matrices for Augmented Retrieval—0
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval—0
Enhancing Event Causality Identification with Rationale and Structure-Aware Causal Question Answering—0
BR-TaxQA-R: A Dataset for Question Answering with References for Brazilian Personal Income Tax Law, including case law—0
BRIT: Bidirectional Retrieval over Unified Image-Text Graph—0
Answer ranking in Community Question Answering: a deep learning approach—0
Bring Remote Sensing Object Detect Into Nature Language Model: Using SFT Method—0
Answer Ranking for Product-Related Questions via Multiple Semantic Relations Modeling—0
A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering—0
A Graph-guided Multi-round Retrieval Method for Conversational Open-domain Question Answering—0
A Crowdsourcing Approach for Annotating Causal Relation Instances in Wikipedia—0
Exploring and Analyzing Machine Commonsense Benchmarks—0
Enhancing Explainability in Multimodal Large Language Models Using Ontological Context—0
Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens—0
Answer Presentation in Question Answering over Linked Data using Typed Dependency Subtree Patterns—0
Bridging the Training-Inference Gap for Dense Phrase Retrieval—0
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets—0
A Graph-Based Approach to String Regeneration—0
Bridging the Preference Gap between Retrievers and LLMs—0
Bridging the Language Gap: Knowledge Injected Multilingual Question Answering—0
Answer-Me: Multi-Task Open-Vocabulary Visual Question Answering—0
Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge—0
AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings—0
Abacus: A Cost-Based Optimizer for Semantic Operator Systems—0
Bridging the Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs—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