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 2651–2675 of 10817 papers

TitleStatusHype
Limited Ability of LLMs to Simulate Human Psychological Behaviours: a Psychometric AnalysisCode0
ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering—0
Prompting Large Language Models with Knowledge Graphs for Question Answering Involving Long-tail Facts—0
Federated Document Visual Question Answering: A Pilot StudyCode0
Aspect-oriented Consumer Health Answer Summarization—0
G-SAP: Graph-based Structure-Aware Prompt Learning over Heterogeneous Knowledge for Commonsense Reasoning—0
Parameter-Efficient Fine-Tuning With Adapters—0
Redefining Information Retrieval of Structured Database via Large Language Models—0
HMT: Hierarchical Memory Transformer for Long Context Language ProcessingCode2
ChatSOS: Vector Database Augmented Generative Question Answering Assistant in Safety Engineering—0
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages—0
CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization—0
Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering—0
Improving Long Text Understanding with Knowledge Distilled from Summarization Model—0
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific LiteratureCode2
CleanGraph: Human-in-the-loop Knowledge Graph Refinement and CompletionCode0
ERATTA: Extreme RAG for Table To Answers with Large Language Models—0
Switchable Decision: Dynamic Neural Generation Networks—0
Mitigating Clickbait: An Approach to Spoiler Generation Using Multitask Learning—0
Hire Me or Not? Examining Language Model's Behavior with Occupation AttributesCode0
ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and PersonalizationCode1
VSA4VQA: Scaling a Vector Symbolic Architecture to Visual Question Answering on Natural Images—0
GOVERN: Gradient Orientation Vote Ensemble for Multi-Teacher Reinforced Distillation—0
Advancing Multimodal Medical Capabilities of Gemini—0
Language-Image Models with 3D Understanding—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