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 1401–1450 of 10817 papers

TitleStatusHype
Task Progressive Curriculum Learning for Robust Visual Question Answering—0
Augmenting Multimodal LLMs with Self-Reflective Tokens for Knowledge-based Visual Question AnsweringCode2
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis—0
VideoOrion: Tokenizing Object Dynamics in Videos—0
Context Awareness Gate For Retrieval Augmented GenerationCode1
AtomR: Atomic Operator-Empowered Large Language Models for Heterogeneous Knowledge ReasoningCode1
Text-Guided Coarse-to-Fine Fusion Network for Robust Remote Sensing Visual Question Answering—0
Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ DocumentsCode0
Seed-Free Synthetic Data Generation Framework for Instruction-Tuning LLMs: A Case Study in ThaiCode1
AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset—0
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity—0
freePruner: A Training-free Approach for Large Multimodal Model Acceleration—0
ReWind: Understanding Long Videos with Instructed Learnable Memory—0
KBAlign: Efficient Self Adaptation on Specific Knowledge BasesCode0
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame SelectionCode2
GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AICode2
Visual Contexts Clarify Ambiguous Expressions: A Benchmark DatasetCode0
Knowledge Graphs, Large Language Models, and Hallucinations: An NLP Perspective—0
FastRAG: Retrieval Augmented Generation for Semi-structured Data—0
Uni-Mlip: Unified Self-supervision for Medical Vision Language Pre-training—0
Retrieval-Augmented Generation for Domain-Specific Question Answering: A Case Study on Pittsburgh and CMU—0
Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios—0
Teaching VLMs to Localize Specific Objects from In-context ExamplesCode1
LaVida Drive: Vision-Text Interaction VLM for Autonomous Driving with Token Selection, Recovery and Enhancement—0
Evaluating LLMs Capabilities Towards Understanding Social Dynamics—0
Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model—0
CATCH: Complementary Adaptive Token-level Contrastive Decoding to Mitigate Hallucinations in LVLMs—0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction—0
Neon: News Entity-Interaction Extraction for Enhanced Question Answering—0
DynFocus: Dynamic Cooperative Network Empowers LLMs with Video Understanding—0
A Survey of Medical Vision-and-Language Applications and Their TechniquesCode1
Do LLMs Understand Ambiguity in Text? A Case Study in Open-world Question Answering—0
Mitigating Knowledge Conflicts in Language Model-Driven Question Answering—0
Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media ContextsCode0
MC-LLaVA: Multi-Concept Personalized Vision-Language ModelCode2
ForPKG: A Framework for Constructing Forestry Policy Knowledge Graph and Application AnalysisCode0
Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question AnsweringCode0
Memory-Augmented Multimodal LLMs for Surgical VQA via Self-Contained Inquiry—0
Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-TuningCode0
A Comprehensive Survey on Visual Question Answering Datasets and Algorithms—0
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
LLaSA: Large Language and Structured Data Assistant—0
Large Vision-Language Models for Remote Sensing Visual Question Answering—0
Everything is a Video: Unifying Modalities through Next-Frame Prediction—0
Layer Importance and Hallucination Analysis in Large Language Models via Enhanced Activation Variance-Sparsity—0
SlimLM: An Efficient Small Language Model for On-Device Document Assistance—0
LLaVA-CoT: Let Vision Language Models Reason Step-by-StepCode7
Visual question answering based evaluation metrics for text-to-image generation—0
AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference—0
A Benchmark for Long-Form Medical 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