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 1501–1525 of 10817 papers

TitleStatusHype
MILU: A Multi-task Indic Language Understanding BenchmarkCode1
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees—0
AVSS: Layer Importance Evaluation in Large Language Models via Activation Variance-Sparsity Analysis—0
A Multi-Task Role-Playing Agent Capable of Imitating Character Linguistic Styles—0
One VLM to Keep it Learning: Generation and Balancing for Data-free Continual Visual Question Answering—0
Can Language Models Enable In-Context Database?—0
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI—0
Goal-Oriented Semantic Communication for Wireless Visual Question Answering—0
A Visual Question Answering Method for SAR Ship: Breaking the Requirement for Multimodal Dataset Construction and Model Fine-Tuning—0
RS-MoE: Mixture of Experts for Remote Sensing Image Captioning and Visual Question Answering—0
Diagnosing Medical Datasets with Training DynamicsCode0
Designing a Robust Radiology Report Generation System—0
LoRA-Contextualizing Adaptation of Large Multimodal Models for Long Document Understanding—0
GRS-QA -- Graph Reasoning-Structured Question Answering Dataset—0
Enhancing Question Answering Precision with Optimized Vector Retrieval and Instructions—0
Provenance: A Light-weight Fact-checker for Retrieval Augmented LLM Generation Output—0
Magnitude Pruning of Large Pretrained Transformer Models with a Mixture Gaussian Prior—0
Rationale-Guided Retrieval Augmented Generation for Medical Question AnsweringCode1
Right this way: Can VLMs Guide Us to See More to Answer Questions?Code0
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language ModelsCode0
AttackQA: Development and Adoption of a Dataset for Assisting Cybersecurity Operations using Fine-tuned and Open-Source LLMs—0
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking—0
Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change DetectionCode1
Dynamic Uncertainty Ranking: Enhancing In-Context Learning for Long-Tail Knowledge in LLMs—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