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 3051–3075 of 10817 papers

TitleStatusHype
API Is Enough: Conformal Prediction for Large Language Models Without Logit-Access—0
VBART: The Turkish LLM—0
MediSwift: Efficient Sparse Pre-trained Biomedical Language Models—0
LocalRQA: From Generating Data to Locally Training, Testing, and Deploying Retrieval-Augmented QA SystemsCode0
Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models—0
Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering BenchmarkCode1
TV-TREES: Multimodal Entailment Trees for Neuro-Symbolic Video Reasoning—0
Survey in Characterization of Semantic Change—0
OpenMedLM: Prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models—0
Prompting Explicit and Implicit Knowledge for Multi-hop Question Answering Based on Human Reading Process—0
Learning to Generate Instruction Tuning Datasets for Zero-Shot Task AdaptationCode4
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic DimensionCode1
Benchmarking Large Language Models on Answering and Explaining Challenging Medical QuestionsCode1
Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented GenerationCode2
Can GPT Improve the State of Prior Authorization via Guideline Based Automated Question Answering?—0
A Cognitive Evaluation Benchmark of Image Reasoning and Description for Large Vision-Language Models—0
The First Place Solution of WSDM Cup 2024: Leveraging Large Language Models for Conversational Multi-Doc QACode2
Self-Refinement of Language Models from External Proxy Metrics Feedback—0
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A SurveyCode2
BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational AlgebraCode2
JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering CapabilityCode0
Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language ModelsCode0
ArcSin: Adaptive ranged cosine Similarity injected noise for Language-Driven Visual Tasks—0
Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and SundaneseCode1
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
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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