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 1001–1025 of 10817 papers

TitleStatusHype
Cross-Language Approach for Quranic QA—0
Comprehensive Evaluation for a Large Scale Knowledge Graph Question Answering Service—0
3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow—0
LLM-AutoDiff: Auto-Differentiate Any LLM WorkflowCode7
Multiple Abstraction Level Retrieve Augment Generation—0
A Comprehensive Study on Fine-Tuning Large Language Models for Medical Question Answering Using Classification Models and Comparative Analysis—0
Options-Aware Dense Retrieval for Multiple-Choice query Answering—0
Provence: efficient and robust context pruning for retrieval-augmented generation—0
URAG: Implementing a Unified Hybrid RAG for Precise Answers in University Admission Chatbots -- A Case Study at HCMUT—0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
LUCY: Linguistic Understanding and Control Yielding Early Stage of HerCode2
PISCO: Pretty Simple Compression for Retrieval-Augmented Generation—0
Complete Chess Games Enable LLM Become A Chess Master—0
How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback—0
Adapting Biomedical Abstracts into Plain language using Large Language Models—0
Scaling Large Vision-Language Models for Enhanced Multimodal Comprehension In Biomedical Image Analysis—0
LLM Evaluation Based on Aerospace Manufacturing Expertise: Automated Generation and Multi-Model Question Answering—0
ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval—0
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement LearningCode2
Federated Retrieval Augmented Generation for Multi-Product Question Answering—0
Knowledge Hierarchy Guided Biological-Medical Dataset Distillation for Domain LLM Training—0
CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs—0
An Attempt to Unraveling Token Prediction Refinement and Identifying Essential Layers of Large Language Models—0
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language ModelsCode2
MASTER: A Multi-Agent System with LLM Specialized MCTS—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