prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the VLC-BERT model in the VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the ReVeaL model in the REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the HDU-USYD-UNCC model in the VQA: Visual Question Answering paper on the COCO Visual Question Answering (VQA) real images 2.0 open ended dataset? | Percentage correct |
What metrics were used to measure the DLAIT model in the VQA: Visual Question Answering paper on the COCO Visual Question Answering (VQA) real images 2.0 open ended dataset? | Percentage correct |
What metrics were used to measure the MCB model in the Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering paper on the COCO Visual Question Answering (VQA) real images 2.0 open ended dataset? | Percentage correct |
What metrics were used to measure the d-LSTM+nI model in the Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering paper on the COCO Visual Question Answering (VQA) real images 2.0 open ended dataset? | Percentage correct |
What metrics were used to measure the BERT LARGE Baseline model in the DocVQA: A Dataset for VQA on Document Images paper on the DocVQA val dataset? | ANLS, Accuracy |
What metrics were used to measure the ensemble_two_best model in the paper on the VizWiz 2018 Answerability dataset? | average_precision, f1_score |
What metrics were used to measure the VL-BERTLARGE model in the VL-BERT: Pre-training of Generic Visual-Linguistic Representations paper on the VCR (Q-A) dev dataset? | Accuracy |
What metrics were used to measure the VL-BERTBASE model in the VL-BERT: Pre-training of Generic Visual-Linguistic Representations paper on the VCR (Q-A) dev dataset? | Accuracy |
What metrics were used to measure the VisualBERT model in the VisualBERT: A Simple and Performant Baseline for Vision and Language paper on the VCR (Q-A) dev dataset? | Accuracy |
What metrics were used to measure the BEiT-3 model in the Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the mPLUG-Huge model in the mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the ONE-PEACE model in the ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the X2-VLM (large) model in the X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the VLMo model in the VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Florence model in the Florence: A New Foundation Model for Computer Vision paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the SimVLM model in the SimVLM: Simple Visual Language Model Pretraining with Weak Supervision paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the X2-VLM (base) model in the X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the VAST model in the VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the VALOR model in the VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Prompt Tuning model in the Prompt Tuning for Generative Multimodal Pretrained Models paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Prismer model in the Prismer: A Vision-Language Model with An Ensemble of Experts paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MSR + MS Cog. Svcs., X10 models model in the VinVL: Revisiting Visual Representations in Vision-Language Models paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MSR + MS Cog. Svcs. model in the VinVL: Revisiting Visual Representations in Vision-Language Models paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the ALBEF (14M) model in the Align before Fuse: Vision and Language Representation Learning with Momentum Distillation paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the BGN, ensemble model in the Bilinear Graph Networks for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the ERNIE-ViL-single model model in the ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Single, w/o VLP model in the In Defense of Grid Features for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Single, w/o VLP model in the Deep Multimodal Neural Architecture Search paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the UNITER (Large) model in the UNITER: UNiversal Image-TExt Representation Learning paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the X-101 grid features + MCAN model in the In Defense of Grid Features for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the LXMERT model in the LXMERT: Learning Cross-Modality Encoder Representations from Transformers paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the VL-BERTLARGE model in the VL-BERT: Pre-training of Generic Visual-Linguistic Representations paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MCAN+VC model in the Visual Commonsense R-CNN paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the VisualBERT model in the VisualBERT: A Simple and Performant Baseline for Vision and Language paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MCANed-6 model in the Deep Modular Co-Attention Networks for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Unified VLP model in the Unified Vision-Language Pre-Training for Image Captioning and VQA paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the BAN+Glove+Counter model in the Bilinear Attention Networks paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Up-Down model in the Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Image features from bottom-up attention (adaptive K, ensemble) model in the Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Caption VQA model in the Generating Question Relevant Captions to Aid Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MuRel model in the MUREL: Multimodal Relational Reasoning for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the DMN model in the Learning to Count Objects in Natural Images for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the BLOCK model in the BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MUTAN model in the MUTAN: Multimodal Tucker Fusion for Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the 2D continuous softmax model in the Sparse and Continuous Attention Mechanisms paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the MCB [11, 12] model in the Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Language-only model in the Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the Prior model in the Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering paper on the VQA v2 test-std dataset? | overall, yes/no, number, other |
What metrics were used to measure the CMN model in the Modeling Relationships in Referential Expressions with Compositional Modular Networks paper on the Visual7W dataset? | Percentage correct |
What metrics were used to measure the CTI (with Boxes) model in the Compact Trilinear Interaction for Visual Question Answering paper on the Visual7W dataset? | Percentage correct |
What metrics were used to measure the CFR model in the Coarse-to-Fine Reasoning for Visual Question Answering paper on the Visual7W dataset? | Percentage correct |
What metrics were used to measure the MCB+Att. model in the Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding paper on the Visual7W dataset? | Percentage correct |
What metrics were used to measure the BLIP-2 ViT-G FlanT5 XXL (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the PNP-VQA model in the Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-G FlanT5 XL (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-L FlanT5 XL (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-G OPT 6.7B (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-G OPT 2.7B (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-L OPT 2.7B (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the Few VLM (zero-shot) model in the A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the MetaLM model in the Language Models are General-Purpose Interfaces paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the VLKD(ViT-B/16) model in the Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the Frozen model in the Multimodal Few-Shot Learning with Frozen Language Models paper on the VQA v2 val dataset? | Accuracy |
What metrics were used to measure the CSS model in the Counterfactual Samples Synthesizing for Robust Visual Question Answering paper on the VQA-CP dataset? | Score |
What metrics were used to measure the GGE-DQ model in the Greedy Gradient Ensemble for Robust Visual Question Answering paper on the VQA-CP dataset? | Score |
What metrics were used to measure the LMH+Entropy regularization (Ensemble) model in the Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies paper on the VQA-CP dataset? | Score |
What metrics were used to measure the LMH+Entropy regularization model in the Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies paper on the VQA-CP dataset? | Score |
What metrics were used to measure the Learned-Mixin +H model in the Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases paper on the VQA-CP dataset? | Score |
What metrics were used to measure the UpDn+SCR (VQA-X) model in the Self-Critical Reasoning for Robust Visual Question Answering paper on the VQA-CP dataset? | Score |
What metrics were used to measure the RUBi model in the RUBi: Reducing Unimodal Biases in Visual Question Answering paper on the VQA-CP dataset? | Score |
What metrics were used to measure the NSM model in the Learning by Abstraction: The Neural State Machine paper on the VQA-CP dataset? | Score |
What metrics were used to measure the MuRel model in the MUREL: Multimodal Relational Reasoning for Visual Question Answering paper on the VQA-CP dataset? | Score |
What metrics were used to measure the HAN model in the Learning Visual Question Answering by Bootstrapping Hard Attention paper on the VQA-CP dataset? | Score |
What metrics were used to measure the BLIP2 FlanT5-XXL (Fine-tuned) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Exact Match, BEM |
What metrics were used to measure the BLIP2 FlanT5-XL (Fine-tuned) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Exact Match, BEM |
What metrics were used to measure the BLIP2 FlanT5-XXL (Zero-shot) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Exact Match, BEM |
What metrics were used to measure the OFA Large model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Exact Match, BEM |
What metrics were used to measure the BLIP Large model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Exact Match, BEM |
What metrics were used to measure the BLIP2 FlanT5-XXL (Text-only FT) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Exact Match, BEM |
What metrics were used to measure the LXR955, No Ensemble model in the LXMERT: Learning Cross-Modality Encoder Representations from Transformers paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the fw_vqa_ model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the Pythia v0.3 model in the Towards VQA Models That Can Read paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the B-Ultra model in the Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the DVW model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the DVizWiz model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the BAN model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the ss model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the hdhs model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the Colin model in the paper on the VizWiz 2018 dataset? | overall, yes/no, number, other, unanswerable |
What metrics were used to measure the CFR model in the Coarse-to-Fine Reasoning for Visual Question Answering paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the NSM model in the Learning by Abstraction: The Neural State Machine paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the LXMERT (Pre-train + scratch) model in the LXMERT: Learning Cross-Modality Encoder Representations from Transformers paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the single-hop + LCGN (ours) model in the Language-Conditioned Graph Networks for Relational Reasoning paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-G FlanT5 XXL (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-L FlanT5 XL (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-G FlanT5 XL (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the PNP-VQA model in the Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training paper on the GQA test-dev dataset? | Accuracy |
What metrics were used to measure the BLIP-2 ViT-G OPT 6.7B (zero-shot) model in the BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models paper on the GQA test-dev dataset? | Accuracy |
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