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 7351–7375 of 10817 papers

TitleStatusHype
AMR Beyond the Sentence: the Multi-sentence AMR corpus—0
PolyUCOMP: Combining Semantic Vectors with Skip bigrams for Semantic Textual Similarity—0
Post-training an LLM for RAG? Train on Self-Generated Demonstrations—0
PEFT-MedAware: Large Language Model for Medical Awareness—0
GRS-QA -- Graph Reasoning-Structured Question Answering Dataset—0
Penalizing Confident Predictions on Largely Perturbed Inputs Does Not Improve Out-of-Distribution Generalization in Question Answering—0
Growing Multi-Domain Glossaries from a Few Seeds using Probabilistic Topic Models—0
Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation—0
Grover's Algorithm for Question Answering—0
ConceptEdit: Conceptualization-Augmented Knowledge Editing in Large Language Models for Commonsense Reasoning—0
A Study of Hybrid Similarity Measures for Semantic Relation Extraction—0
Group Non-negative Matrix Factorization with Natural Categories for Question Retrieval in Community Question Answer Archives—0
Grounding Task Assistance with Multimodal Cues from a Single Demonstration—0
Perception Test 2024: Challenge Summary and a Novel Hour-Long VideoQA Benchmark—0
Grounding Semantic Roles in Images—0
ComRAG: Retrieval-Augmented Generation with Dynamic Vector Stores for Real-time Community Question Answering in Industry—0
A Study of Heterogeneous Similarity Measures for Semantic Relation Extraction—0
AmQA: Amharic Question Answering Dataset—0
Performance Comparison of Large Language Models on VNHSGE English Dataset: OpenAI ChatGPT, Microsoft Bing Chat, and Google Bard—0
Performance Evaluation of Knowledge Graph Embedding Approaches under Non-adversarial Attacks—0
Performance Prediction for Multi-hop Questions—0
Exploring Temporal Vagueness with Mechanical Turk—0
Perhaps PTLMs Should Go to School -- A Task to Assess Open Book and Closed Book QA—0
Perhaps PTLMs Should Go to School – A Task to Assess Open Book and Closed Book QA—0
Grounding LLM Reasoning with Knowledge Graphs—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