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 401–450 of 10817 papers

TitleStatusHype
GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning AbilitiesCode2
GOFA: A Generative One-For-All Model for Joint Graph Language ModelingCode2
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
MuGER^2: Multi-Granularity Evidence Retrieval and Reasoning for Hybrid Question AnsweringCode2
Multi-Agent Large Language Models for Conversational Task-SolvingCode2
From CLIP to DINO: Visual Encoders Shout in Multi-modal Large Language ModelsCode2
Cross-Task Generalization via Natural Language Crowdsourcing InstructionsCode2
ConceptLab: Creative Concept Generation using VLM-Guided Diffusion Prior ConstraintsCode2
Neptune: The Long Orbit to Benchmarking Long Video UnderstandingCode2
From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning TasksCode2
Can AI Assistants Know What They Don't Know?Code2
FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Visual Language ModelsCode2
FreeVA: Offline MLLM as Training-Free Video AssistantCode2
F-LMM: Grounding Frozen Large Multimodal ModelsCode2
CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuningCode2
FortisAVQA and MAVEN: a Benchmark Dataset and Debiasing Framework for Robust Multimodal ReasoningCode2
Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMsCode2
PA-LLaVA: A Large Language-Vision Assistant for Human Pathology Image UnderstandingCode2
PaLM-E: An Embodied Multimodal Language ModelCode2
Frozen Transformers in Language Models Are Effective Visual Encoder LayersCode2
PEDANTS: Cheap but Effective and Interpretable Answer EquivalenceCode2
An Embodied Generalist Agent in 3D WorldCode2
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character DesignCode2
PeFoMed: Parameter Efficient Fine-tuning of Multimodal Large Language Models for Medical ImagingCode2
Pengi: An Audio Language Model for Audio TasksCode2
Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question AnsweringCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
PG-Video-LLaVA: Pixel Grounding Large Video-Language ModelsCode2
Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingCode2
FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model EvaluationCode2
Atlas: Few-shot Learning with Retrieval Augmented Language ModelsCode2
FanOutQA: A Multi-Hop, Multi-Document Question Answering Benchmark for Large Language ModelsCode2
EyeCLIP: A visual-language foundation model for multi-modal ophthalmic image analysisCode2
Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerCode2
AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction SimulatorCode2
FakeBench: Probing Explainable Fake Image Detection via Large Multimodal ModelsCode2
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous DrivingCode2
FinBERT-QA: Financial Question Answering with pre-trained BERT Language ModelsCode2
Evaluating LLM Reasoning in the Operations Research Domain with ORQACode2
Evaluating RAG-Fusion with RAGElo: an Automated Elo-based FrameworkCode2
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training QuantizationCode2
E.T. Bench: Towards Open-Ended Event-Level Video-Language UnderstandingCode2
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language ModelsCode2
ERA-CoT: Improving Chain-of-Thought through Entity Relationship AnalysisCode2
Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for EnsemblingCode2
End-to-End Navigation with Vision Language Models: Transforming Spatial Reasoning into Question-AnsweringCode2
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-ImprovementCode2
Explore the Limits of Omni-modal Pretraining at ScaleCode2
Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based RetrieversCode2
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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