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

Showing 91019125 of 10817 papers

TitleStatusHype
How much should you ask? On the question structure in QA systems.0
How much should you ask? On the question structure in QA systems0
Challenges in Explanation Quality Evaluation0
How Privacy-Savvy Are Large Language Models? A Case Study on Compliance and Privacy Technical Review0
How Relevant is Selective Memory Population in Lifelong Language Learning?0
How Self-Attention Improves Rare Class Performance in a Question-Answering Dialogue Agent0
How Stable is Knowledge Base Knowledge?0
How State-Of-The-Art Models Can Deal With Long-Form Question Answering0
How Susceptible are LLMs to Influence in Prompts?0
How to Build an AI Tutor That Can Adapt to Any Course Using Knowledge Graph-Enhanced Retrieval-Augmented Generation (KG-RAG)0
How to Design Sample and Computationally Efficient VQA Models0
How to Evaluate Opinionated Keyphrase Extraction?0
How to find a good image-text embedding for remote sensing visual question answering?0
How to Make a BLT Sandwich? Learning to Reason towards Understanding Web Instructional Videos0
How to make qubits speak0
How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback0
How to Pre-Train Your Model? Comparison of Different Pre-Training Models for Biomedical Question Answering0
How to Seq2seq for SQL0
How Transferable are Reasoning Patterns in VQA?0
How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey0
How Well Can Vison-Language Models Understand Humans' Intention? An Open-ended Theory of Mind Question Evaluation Benchmark0
How Well can We Learn Interpretable Entity Types from Text?0
How well do Computers Solve Math Word Problems? Large-Scale Dataset Construction and Evaluation0
How You Ask Matters: The Effect of Paraphrastic Questions to BERT Performance on a Clinical SQuAD Dataset0
HPI Question Answering System in BioASQ 20160
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94Unverified
2FPNet (ensemble)EM90.87Unverified
3IE-NetV2 (ensemble)EM90.86Unverified
4SA-Net on Albert (ensemble)EM90.72Unverified
5SA-Net-V2 (ensemble)EM90.68Unverified
6FPNet (ensemble)EM90.6Unverified
7Retro-Reader (ensemble)EM90.58Unverified
8EntitySpanFocusV2 (ensemble)EM90.52Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49Unverified
10EntitySpanFocus+AT (ensemble)EM90.45Unverified