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 8201–8225 of 10817 papers

TitleStatusHype
A Mathematical Abstraction for Balancing the Trade-off Between Creativity and Reality in Large Language Models—0
Retrieving Supporting Evidence for LLMs Generated Answers—0
GenSco: Can Question Decomposition based Passage Alignment improve Question Answering?—0
Community Answer Summarization for Multi-Sentence Question with Group L1 Regularization—0
GenRE: A Generative Model for Relation Extraction—0
CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models—0
Assessing Image Quality Issues for Real-World Problems—0
Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics—0
Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness—0
Genie: Achieving Human Parity in Content-Grounded Datasets Generation—0
Commonsense Video Question Answering through Video-Grounded Entailment Tree Reasoning—0
AmaSQuAD: A Benchmark for Amharic Extractive Question Answering—0
Retrieving Supporting Evidence for Generative Question Answering—0
Retrieving-to-Answer: Zero-Shot Video Question Answering with Frozen Large Language Models—0
Generic Attention-model Explainability by Weighted Relevance Accumulation—0
Generative Visual Question Answering—0
Generative Stock Question Answering—0
Assessing Crowdsourcing Quality through Objective Tasks—0
Retrieve, Summarize, Plan: Advancing Multi-hop Question Answering with an Iterative Approach—0
Generative retrieval-augmented ontologic graph and multi-agent strategies for interpretive large language model-based materials design—0
Generative Relation Linking for Question Answering over Knowledge Bases—0
Assessing and Enhancing Large Language Models in Rare Disease Question-answering—0
Commonsense Knowledge in Wikidata—0
Generative Question Answering: Learning to Answer the Whole Question—0
AMAQA: A Metadata-based QA Dataset for RAG Systems—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