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 5151–5175 of 10817 papers

TitleStatusHype
Enhancing Explainability in Multimodal Large Language Models Using Ontological Context—0
Enhancing Event Causality Identification with Rationale and Structure-Aware Causal Question Answering—0
Building a Question Answering System for the Manufacturing Domain—0
Mitigating the Risk of Health Inequity Exacerbated by Large Language Models—0
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval—0
Building a Question and Answer System for News Domain—0
A Grounded Memory System For Smart Personal Assistants—0
Enhancing Document Information Analysis with Multi-Task Pre-training: A Robust Approach for Information Extraction in Visually-Rich Documents—0
Building and Exploring Semantic Equivalences Resources—0
Enhancing Biosecurity in Tamper-Resistant Large Language Models With Quantum Gradient Descent—0
Enhancing Biomedical Text Summarization and Question-Answering: On the Utility of Domain-Specific Pre-Training—0
Building a Knowledge Graph from Natural Language Definitions for Interpretable Text Entailment Recognition—0
Building a Human-Verified Clinical Reasoning Dataset via a Human LLM Hybrid Pipeline for Trustworthy Medical AI—0
A Graph Traversal Based Approach to Answer Non-Aggregation Questions Over DBpedia—0
ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition—0
SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation—0
Enhancing BERT-Based Visual Question Answering through Keyword-Driven Sentence Selection—0
Enhancing Answer Selection in Community Question Answering with Pre-trained and Large Language Models—0
Enhance Long Text Understanding via Distilled Gist Detector from Abstractive Summarization—0
Building a Dataset for Automatically Learning to Detect Questions Requiring Clarification—0
Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering—0
Enhanced Textual Feature Extraction for Visual Question Answering: A Simple Convolutional Approach—0
Enhanced vectors for top-k document retrieval in Question Answering—0
Building a Crisis Management Term Resource for Social Media: The Case of Floods and Protests—0
Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension—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