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 351–400 of 10817 papers

TitleStatusHype
LOVA3: Learning to Visual Question Answering, Asking and AssessmentCode2
AGILE: A Novel Reinforcement Learning Framework of LLM AgentsCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
ProtT3: Protein-to-Text Generation for Text-based Protein UnderstandingCode2
MTVQA: Benchmarking Multilingual Text-Centric Visual Question AnsweringCode2
Grounded 3D-LLM with Referent TokensCode2
FreeVA: Offline MLLM as Training-Free Video AssistantCode2
HMT: Hierarchical Memory Transformer for Long Context Language ProcessingCode2
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific LiteratureCode2
Overview of the EHRSQL 2024 Shared Task on Reliable Text-to-SQL Modeling on Electronic Health RecordsCode2
IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic LanguagesCode2
Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question AnsweringCode2
GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist CollaborationCode2
FakeBench: Probing Explainable Fake Image Detection via Large Multimodal ModelsCode2
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language ModelsCode2
LLoCO: Learning Long Contexts OfflineCode2
Superposition Prompting: Improving and Accelerating Retrieval-Augmented GenerationCode2
Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarksCode2
LongVLM: Efficient Long Video Understanding via Large Language ModelsCode2
Direct Preference Optimization of Video Large Multimodal Models from Language Model RewardCode2
How Much are Large Language Models Contaminated? A Comprehensive Survey and the LLMSanitize LibraryCode2
Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You WantCode2
VHM: Versatile and Honest Vision Language Model for Remote Sensing Image AnalysisCode2
Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language ModelsCode2
Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous DrivingCode2
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory PredictionCode2
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLMCode2
OmniVid: A Generative Framework for Universal Video UnderstandingCode2
Visually Guided Generative Text-Layout Pre-training for Document IntelligenceCode2
LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal ModelsCode2
Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based RetrieversCode2
VL-ICL Bench: The Devil in the Details of Multimodal In-Context LearningCode2
RAGGED: Towards Informed Design of Retrieval Augmented Generation SystemsCode2
Beyond Text: Frozen Large Language Models in Visual Signal ComprehensionCode2
ERA-CoT: Improving Chain-of-Thought through Entity Relationship AnalysisCode2
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking TechniquesCode2
Debiasing Multimodal Large Language ModelsCode2
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual ScenariosCode2
QAQ: Quality Adaptive Quantization for LLM KV CacheCode2
Are Language Models Puzzle Prodigies? Algorithmic Puzzles Unveil Serious Challenges in Multimodal ReasoningCode2
Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented GenerationCode2
The First Place Solution of WSDM Cup 2024: Leveraging Large Language Models for Conversational Multi-Doc QACode2
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A SurveyCode2
BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational AlgebraCode2
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question AnsweringCode2
Data Science with LLMs and Interpretable ModelsCode2
ActiveRAG: Autonomously Knowledge Assimilation and Accommodation through Retrieval-Augmented AgentsCode2
FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language ModelsCode2
Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMsCode2
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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