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 1451–1500 of 10817 papers

TitleStatusHype
Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer FrameworkCode1
Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering—0
The Limited Impact of Medical Adaptation of Large Language and Vision-Language ModelsCode0
Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial ApproachCode0
SparrowVQE: Visual Question Explanation for Course Content UnderstandingCode0
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models—0
Likelihood as a Performance Gauge for Retrieval-Augmented GenerationCode0
Greenback Bears and Fiscal Hawks: Finance is a Jungle and Text Embeddings Must Adapt—0
Controllable Context Sensitivity and the Knob Behind ItCode1
Toward Optimal Search and Retrieval for RAGCode0
Invar-RAG: Invariant LLM-aligned Retrieval for Better Generation—0
EVQAScore: Efficient Video Question Answering Data Evaluation—0
Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering—0
Self-Training Meets Consistency: Improving LLMs' Reasoning With Consistency-Driven Rationale EvaluationCode0
Exploring Knowledge Boundaries in Large Language Models for Retrieval Judgment—0
M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework—0
Leveraging Retrieval-Augmented Generation for Persian University Knowledge Retrieval—0
The Empirical Impact of Data Sanitization on Language Models—0
Multi-Document Financial Question Answering using LLMs—0
GUIDEQ: Framework for Guided Questioning for progressive informational collection and classificationCode0
Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models—0
Integrating Object Detection Modality into Visual Language Model for Enhanced Autonomous Driving Agent—0
SciDQA: A Deep Reading Comprehension Dataset over Scientific PapersCode0
Unmasking the Limits of Large Language Models: A Systematic Evaluation of Masked Text Processing Ability through MskQA and MskCalCode0
Poze: Sports Technique Feedback under Data Constraints—0
End-to-End Navigation with Vision Language Models: Transforming Spatial Reasoning into Question-AnsweringCode2
Seeing Through the Fog: A Cost-Effectiveness Analysis of Hallucination Detection Systems—0
WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning—0
Survey on Semantic Interpretation of Tabular Data: Challenges and Directions—0
A Brief History of Named Entity Recognition—0
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding—0
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning—0
SaSR-Net: Source-Aware Semantic Representation Network for Enhancing Audio-Visual Question Answering—0
DELIFT: Data Efficient Language model Instruction Fine TuningCode1
Seeing is Deceiving: Exploitation of Visual Pathways in Multi-Modal Language Models—0
Lexicalization Is All You Need: Examining the Impact of Lexical Knowledge in a Compositional QALD SystemCode0
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models—0
VQA^2: Visual Question Answering for Video Quality AssessmentCode2
Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval—0
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA—0
MEG: Medical Knowledge-Augmented Large Language Models for Question AnsweringCode1
Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?Code0
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing—0
Leveraging Large Language Models in Code Question Answering: Baselines and IssuesCode0
PersianRAG: A Retrieval-Augmented Generation System for Persian Language—0
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning AgentCode3
VERITAS: A Unified Approach to Reliability Evaluation—0
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning—0
Multimodal Commonsense Knowledge Distillation for Visual Question Answering—0
A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessCode3
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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