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 3326–3350 of 10817 papers

TitleStatusHype
Reinforcement Learning for Conversational Question Answering over Knowledge Graph—0
MMToM-QA: Multimodal Theory of Mind Question AnsweringCode2
Large Language Models are Null-Shot Learners—0
Are self-explanations from Large Language Models faithful?Code1
Towards Efficient Methods in Medical Question Answering using Knowledge Graph EmbeddingsCode0
Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future TrendsCode1
Uncovering the Full Potential of Visual Grounding Methods in VQACode0
Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering—0
Wikidata as a seed for Web Extraction—0
A Study on Large Language Models' Limitations in Multiple-Choice Question AnsweringCode0
Bridging the Preference Gap between Retrievers and LLMs—0
Automated Answer Validation using Text Similarity—0
EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health RecordsCode2
BOK-VQA: Bilingual outside Knowledge-Based Visual Question Answering via Graph Representation Pretraining—0
The Unreasonable Effectiveness of Easy Training Data for Hard TasksCode1
Generalizing Visual Question Answering from Synthetic to Human-Written Questions via a Chain of QA with a Large Language ModelCode0
Hallucination Benchmark in Medical Visual Question AnsweringCode0
Cross-modal Retrieval for Knowledge-based Visual Question AnsweringCode1
Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing ConstraintCode1
How Proficient Are Large Language Models in Formal Languages? An In-Depth Insight for Knowledge Base Question Answering—0
Reinforcement Learning for Optimizing RAG for Domain Chatbots—0
MISS: A Generative Pretraining and Finetuning Approach for Med-VQACode1
DCR: Divide-and-Conquer Reasoning for Multi-choice Question Answering with LLMsCode0
AutoAct: Automatic Agent Learning from Scratch for QA via Self-PlanningCode3
Answer Retrieval in Legal Community Question AnsweringCode0
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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