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 8726–8750 of 10817 papers

TitleStatusHype
Structured Knowledge Grounding for Question Answering—0
Flexible End-to-End Dialogue System for Knowledge Grounded Conversation—0
Flexible Frame Selection for Efficient Video Reasoning—0
FlippedRAG: Black-Box Opinion Manipulation Adversarial Attacks to Retrieval-Augmented Generation Models—0
FloodBrain: Flood Disaster Reporting by Web-based Retrieval Augmented Generation with an LLM—0
FlowMind: Automatic Workflow Generation with LLMs—0
FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts—0
FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding—0
FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks—0
Focused Evaluation for Image Description with Binary Forced-Choice Tasks—0
Focused Hierarchical RNNs for Conditional Sequence Processing—0
FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering—0
Focus on FoCus: Is FoCus focused on Context, Knowledge and Persona?—0
Folheador: browsing through Portuguese semantic relations—0
Follow-Up Questions Improve Documents Generated by Large Language Models—0
FONDUE: A Framework for Node Disambiguation Using Network Embeddings—0
Font-Agent: Enhancing Font Understanding with Large Language Models—0
Fooling Vision and Language Models Despite Localization and Attention Mechanism—0
FoQA: A Faroese Question-Answering Dataset—0
FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering—0
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data—0
Forewords—0
Formally Specifying the High-Level Behavior of LLM-Based Agents—0
FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining—0
Fortifying Ethical Boundaries in AI: Advanced Strategies for Enhancing Security in Large Language Models—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