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 2901–2950 of 10817 papers

TitleStatusHype
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory PredictionCode2
Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check—0
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical TextCode4
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLMCode2
Non-Linear Inference Time Intervention: Improving LLM TruthfulnessCode1
mALBERT: Is a Compact Multilingual BERT Model Still Worth It?—0
Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal PerspectiveCode1
GPTs and Language Barrier: A Cross-Lingual Legal QA Examination—0
ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper PagesCode1
Visual Hallucination: Definition, Quantification, and Prescriptive Remediations—0
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language ModelsCode0
The Unreasonable Ineffectiveness of the Deeper LayersCode3
ArabicaQA: A Comprehensive Dataset for Arabic Question AnsweringCode1
Can multiple-choice questions really be useful in detecting the abilities of LLMs?Code0
PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language ModelsCode3
OmniVid: A Generative Framework for Universal Video UnderstandingCode2
A Gaze-grounded Visual Question Answering Dataset for Clarifying Ambiguous Japanese Questions—0
Denoising Table-Text Retrieval for Open-Domain Question AnsweringCode0
Intrinsic Subgraph Generation for Interpretable Graph based Visual Question AnsweringCode0
Make-It-Vivid: Dressing Your Animatable Biped Cartoon Characters from Text—0
PropTest: Automatic Property Testing for Improved Visual Programming—0
Task-Agnostic Detector for Insertion-Based Backdoor Attacks—0
Attribute First, then Generate: Locally-attributable Grounded Text GenerationCode1
Synthesize Step-by-Step: Tools, Templates and LLMs as Data Generators for Reasoning-Based Chart VQA—0
Visually Guided Generative Text-Layout Pre-training for Document IntelligenceCode2
ProCQA: A Large-scale Community-based Programming Question Answering Dataset for Code SearchCode0
CBT-LLM: A Chinese Large Language Model for Cognitive Behavioral Therapy-based Mental Health Question Answering—0
Improving Retrieval for RAG based Question Answering Models on Financial Documents—0
Explore until Confident: Efficient Exploration for Embodied Question Answering—0
MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training—0
General LLMs as Instructors for Domain-Specific LLMs: A Sequential Fusion Method to Integrate Extraction and Editing—0
Surgical-LVLM: Learning to Adapt Large Vision-Language Model for Grounded Visual Question Answering in Robotic Surgery—0
Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based RetrieversCode2
LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal ModelsCode2
Sphere Neural-Networks for Rational Reasoning—0
Multi-Review Fusion-in-Context—0
Awakening Augmented Generation: Learning to Awaken Internal Knowledge of Large Language Models for Question AnsweringCode0
Extracting Emotion Phrases from Tweets using BART—0
Multi-Agent VQA: Exploring Multi-Agent Foundation Models in Zero-Shot Visual Question AnsweringCode1
LLM-based Extraction of Contradictions from Patents—0
Large Language Models for Multi-Choice Question Classification of Medical Subjects—0
gTBLS: Generating Tables from Text by Conditional Question Answering—0
MyVLM: Personalizing VLMs for User-Specific Queries—0
Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels—0
Language Repository for Long Video UnderstandingCode1
Context Quality Matters in Training Fusion-in-Decoder for Extractive Open-Domain Question Answering—0
Multi-Level Explanations for Generative Language Models—0
FIT-RAG: Black-Box RAG with Factual Information and Token Reduction—0
Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question ComplexityCode3
Vi-Mistral-X: Building a Vietnamese Language Model with Advanced Continual Pre-training—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