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 3501–3525 of 10817 papers

TitleStatusHype
Evaluating the Representational Hub of Language and Vision Models—0
Evaluating the Retrieval Component in LLM-Based Question Answering Systems—0
Fine-tuning and aligning question answering models for complex information extraction tasks—0
Evaluating the Symbol Binding Ability of Large Language Models for Multiple-Choice Questions in Vietnamese General Education—0
DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection—0
Evaluating Variable-Length Multiple-Option Lists in Chatbots and Mobile Search—0
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation—0
Beyond the Destination: A Novel Benchmark for Exploration-Aware Embodied Question Answering—0
Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models—0
Evaluation for Partial Event Coreference—0
Finetuning Language Models to Emit Linguistic Expressions of Uncertainty—0
Do You Know That Florence Is Packed with Visitors? Evaluating State-of-the-art Models of Speaker Commitment—0
LLMs May Perform MCQA by Selecting the Least Incorrect Option—0
A Concrete Chinese NLP Pipeline—0
Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformers—0
Evaluation of Dataset Selection for Pre-Training and Fine-Tuning Transformer Language Models for Clinical Question Answering—0
Evaluation of Faithfulness Using the Longest Supported Subsequence—0
Evaluation of General Large Language Models in Contextually Assessing Semantic Concepts Extracted from Adult Critical Care Electronic Health Record Notes—0
Beyond Text: Implementing Multimodal Large Language Model-Powered Multi-Agent Systems Using a No-Code Platform—0
Evaluation of medium-large Language Models at zero-shot closed book generative question answering—0
Evaluation of Question Answering Systems: Complexity of judging a natural language—0
Evaluation of RAG Metrics for Question Answering in the Telecom Domain—0
Evaluation of Review Summaries via Question-Answering—0
Can You Unpack That? Learning to Rewrite Questions-in-Context—0
Do We Need to Differentiate Negative Candidates Before Training a Neural Ranker?—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