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 3226–3250 of 10817 papers

TitleStatusHype
SPARQL Generation: an analysis on fine-tuning OpenLLaMA for Question Answering over a Life Science Knowledge GraphCode1
ScreenAI: A Vision-Language Model for UI and Infographics UnderstandingCode2
NORMY: Non-Uniform History Modeling for Open Retrieval Conversational Question AnsweringCode0
SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark—0
INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionCode1
Training Language Models to Generate Text with Citations via Fine-grained RewardsCode1
Empowering Language Models with Active Inquiry for Deeper Understanding—0
Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification—0
Convincing Rationales for Visual Question Answering ReasoningCode0
A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications—0
Enhancing textual textbook question answering with large language models and retrieval augmented generationCode0
LB-KBQA: Large-language-model and BERT based Knowledge-Based Question and Answering System—0
Text-Guided Image ClusteringCode1
Position: What Can Large Language Models Tell Us about Time Series AnalysisCode2
Large Language Model for Table Processing: A Survey—0
Knowledge Generation for Zero-shot Knowledge-based VQACode0
eXplainable Bayesian Multi-Perspective Generative Retrieval—0
GeReA: Question-Aware Prompt Captions for Knowledge-based Visual Question AnsweringCode2
A Survey of Large Language Models in Finance (FinLLMs)Code3
PuzzleBench: Can LLMs Solve Challenging First-Order Combinatorial Reasoning Problems?—0
SemPool: Simple, robust, and interpretable KG pooling for enhancing language models—0
Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern RetrievalCode1
CABINET: Content Relevance based Noise Reduction for Table Question AnsweringCode1
Efficient Prompt Caching via Embedding Similarity—0
LLMs May Perform MCQA by Selecting the Least Incorrect Option—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