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 4801–4825 of 10817 papers

TitleStatusHype
Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World—0
Joint Modeling of Structure Identification and Nuclearity Recognition in Macro Chinese Discourse Treebank—0
Joint Passage Ranking for Diverse Multi-Answer Retrieval—0
InCA: Rethinking In-Car Conversational System Assessment Leveraging Large Language Models—0
INAOE\_UPV-CORE: Extracting Word Associations from Document Corpora to estimate Semantic Textual Similarity—0
CPSDBench: A Large Language Model Evaluation Benchmark and Baseline for Chinese Public Security Domain—0
IM-RAG: Multi-Round Retrieval-Augmented Generation Through Learning Inner Monologues—0
CP-Router: An Uncertainty-Aware Router Between LLM and LRM—0
mSTEB: Massively Multilingual Evaluation of LLMs on Speech and Text Tasks—0
BioRAG: A RAG-LLM Framework for Biological Question Reasoning—0
Improving Zero-shot Reader by Reducing Distractions from Irrelevant Documents in Open-Domain Question Answering—0
Improving Zero-Shot Event Extraction via Sentence Simplification—0
CPopQA: Ranking Cultural Concept Popularity by LLMs—0
Improving Zero-Shot Cross-lingual Transfer for Multilingual Question Answering over Knowledge Graph—0
Improving Word Representations via Global Context and Multiple Word Prototypes—0
In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT—0
In-Context Ability Transfer for Question Decomposition in Complex QA—0
In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models—0
CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology—0
In-Context Learning with Topological Information for Knowledge Graph Completion—0
Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)—0
Attentive Recurrent Tensor Model for Community Question Answering—0
Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling—0
Incorporating External Knowledge into Machine Reading for Generative Question Answering—0
Improving VQA and its Explanations \\ by Comparing Competing Explanations—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