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 3176–3200 of 10817 papers

TitleStatusHype
Question-Instructed Visual Descriptions for Zero-Shot Video Question AnsweringCode0
Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks—0
Construction of a Syntactic Analysis Map for Yi Shui School through Text Mining and Natural Language Processing Research—0
Exploring Hybrid Question Answering via Program-based Prompting—0
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsCode2
Prompt-based Personalized Federated Learning for Medical Visual Question Answering—0
Enhancing Large Language Models with Pseudo- and Multisource- Knowledge Graphs for Open-ended Question Answering—0
AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction SimulatorCode2
Answer is All You Need: Instruction-following Text Embedding via Answering the QuestionCode1
LAPDoc: Layout-Aware Prompting for Documents—0
ControlLM: Crafting Diverse Personalities for Language ModelsCode1
A Dataset of Open-Domain Question Answering with Multiple-Span Answers—0
Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-raysCode0
Reasoning over Uncertain Text by Generative Large Language ModelsCode0
Multi-Query Focused Disaster Summarization via Instruction-Based Prompting—0
OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLMCode4
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models—0
Visually Dehallucinative Instruction GenerationCode0
Visual Question Answering Instruction: Unlocking Multimodal Large Language Model To Domain-Specific Visual Multitasks—0
Plausible Extractive Rationalization through Semi-Supervised Entailment SignalCode0
PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal RetrieversCode3
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-AnsweringCode0
Lumos : Empowering Multimodal LLMs with Scene Text Recognition—0
GRILLBot In Practice: Lessons and Tradeoffs Deploying Large Language Models for Adaptable Conversational Task AssistantsCode1
Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited ExamplesCode1
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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