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 7476–7500 of 10817 papers

TitleStatusHype
Automatic Evaluation of Summary Using Textual Entailment—0
An Emotional Comfort Framework for Improving User Satisfaction in E-Commerce Customer Service Chatbots—0
Post-training an LLM for RAG? Train on Self-Generated Demonstrations—0
Advancing Chinese biomedical text mining with community challenges—0
A Combined Pattern-based and Distributional Approach for Automatic Hypernym Detection in Dutch.—0
Power in Numbers: Robust reading comprehension by finetuning with four adversarial sentences per example—0
Poze: Sports Technique Feedback under Data Constraints—0
PPT: A Process-based Preference Learning Framework for Self Improving Table Question Answering Models—0
(2.5+1)D Spatio-Temporal Scene Graphs for Video Question Answering—0
MMPKUBase: A Comprehensive and High-quality Chinese Multi-modal Knowledge Graph—0
Explainable High-order Visual Question Reasoning: A New Benchmark and Knowledge-routed Network—0
1-800-SHARED-TASKS at RegNLP: Lexical Reranking of Semantic Retrieval (LeSeR) for Regulatory Question Answering—0
Practical Parsing for Downstream Applications—0
Joint Learning with Global Inference for Comment Classification in Community Question Answering—0
Practice in Synonym Extraction at Large Scale—0
Joint learning of object graph and relation graph for visual question answering—0
DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure—0
Joint Learning of Entity Linking Constraints Using a Markov-Logic Network—0
Data-efficient Meta-models for Evaluation of Context-based Questions and Answers in LLMs—0
Precise Length Control in Large Language Models—0
Precise Model Benchmarking with Only a Few Observations—0
Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models—0
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute—0
Joint Learning of a Dual SMT System for Paraphrase Generation—0
Joint Information Extraction and Reasoning: A Scalable Statistical Relational Learning Approach—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