prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the PaLI-X (Multi-task FT) model in the PaLI-X: On Scaling up a Multilingual Vision and Language Model paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the PaLI-X (Single-task FT) model in the PaLI-X: On Scaling up a Multilingual Vision and Language Model paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the GPT-3.5 + LATIN-Prompt model in the Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the DocFormerv2-large model in the DocFormerv2: Local Features for Document Understanding paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the UDOP model in the Unifying Vision, Text, and Layout for Universal Document Processing paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the DUBLIN (variable resolution) model in the DUBLIN -- Document Understanding By Language-Image Network paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the Pix2Struct-large model in the Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the Pix2Struct-base model in the Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the MatCha model in the MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the DUBLIN model in the DUBLIN -- Document Understanding By Language-Image Network paper on the InfographicVQA dataset? | ANLS |
What metrics were used to measure the Graph VQA model in the Graph-Structured Representations for Visual Question Answering paper on the COCO Visual Question Answering (VQA) abstract images 1.0 open ended dataset? | Percentage correct |
What metrics were used to measure the Dualnet ensemble model in the VQA: Visual Question Answering paper on the COCO Visual Question Answering (VQA) abstract images 1.0 open ended dataset? | Percentage correct |
What metrics were used to measure the LSTM + global features model in the VQA: Visual Question Answering paper on the COCO Visual Question Answering (VQA) abstract images 1.0 open ended dataset? | Percentage correct |
What metrics were used to measure the LSTM blind model in the VQA: Visual Question Answering paper on the COCO Visual Question Answering (VQA) abstract images 1.0 open ended dataset? | Percentage correct |
What metrics were used to measure the DUBLIN model in the DUBLIN -- Document Understanding By Language-Image Network paper on the DeepForm dataset? | F1 |
What metrics were used to measure the ProTo model in the ProTo: Program-Guided Transformer for Program-Guided Tasks paper on the GQA test-std 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-std dataset? | Accuracy |
What metrics were used to measure the MDETR-ENB5 model in the MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding paper on the GQA test-std dataset? | Accuracy |
What metrics were used to measure the LXMERT model in the LXMERT: Learning Cross-Modality Encoder Representations from Transformers paper on the GQA test-std 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-std dataset? | Accuracy |
What metrics were used to measure the MAC model in the GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering paper on the GQA test-std dataset? | Accuracy |
What metrics were used to measure the CNN+LSTM model in the GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering paper on the GQA test-std dataset? | Accuracy |
What metrics were used to measure the DUBLIN model in the DUBLIN -- Document Understanding By Language-Image Network paper on the WebSRC dataset? | EM |
What metrics were used to measure the GPT4RoI model in the GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest paper on the VCR (Q-AR) test dataset? | Accuracy |
What metrics were used to measure the ERNIE-ViL-large(ensemble of 15 models) model in the ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph paper on the VCR (Q-AR) test dataset? | Accuracy |
What metrics were used to measure the UNITER (Large) model in the UNITER: UNiversal Image-TExt Representation Learning paper on the VCR (Q-AR) test dataset? | Accuracy |
What metrics were used to measure the KVL-BERTLARGE model in the KVL-BERT: Knowledge Enhanced Visual-and-Linguistic BERT for Visual Commonsense Reasoning paper on the VCR (Q-AR) test dataset? | Accuracy |
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-AR) test dataset? | Accuracy |
What metrics were used to measure the VL-T5 model in the Unifying Vision-and-Language Tasks via Text Generation paper on the VCR (Q-AR) test 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-AR) test dataset? | Accuracy |
What metrics were used to measure the Human model in the DocVQA: A Dataset for VQA on Document Images paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the PaLI-3 (w/ OCR) model in the PaLI-3 Vision Language Models: Smaller, Faster, Stronger paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the ERNIE-Layout large (ensemble) model in the ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the GPT-4 model in the Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the DocFormerv2-large model in the DocFormerv2: Local Features for Document Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the UDOP (aux) model in the Unifying Vision, Text, and Layout for Universal Document Processing paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the PaLI-3 model in the PaLI-3 Vision Language Models: Smaller, Faster, Stronger paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the TILT-Large model in the Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the PaLI-X (Single-task FT w/ OCR) model in the PaLI-X: On Scaling up a Multilingual Vision and Language Model paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the LayoutLMv2LARGE model in the LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the ERNIE-Layout large model in the ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the UDOP model in the Unifying Vision, Text, and Layout for Universal Document Processing paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the TILT-Base model in the Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Claude + LATIN-Prompt model in the Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the GPT-3.5 + LATIN-Prompt model in the Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the PaLI-X (Multi-task FT) model in the PaLI-X: On Scaling up a Multilingual Vision and Language Model paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the DUBLIN (variable resolution) model in the DUBLIN -- Document Understanding By Language-Image Network paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the PaLI-X (Single-task FT) model in the PaLI-X: On Scaling up a Multilingual Vision and Language Model paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the DUBLIN model in the DUBLIN -- Document Understanding By Language-Image Network paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the LayoutLMv2BASE model in the LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Pix2Struct-large model in the Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the MatCha model in the MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Pix2Struct-base model in the Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Donut model in the OCR-free Document Understanding Transformer paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the BERT_LARGE_SQUAD_DOCVQA_FINETUNED_Baseline model in the DocVQA: A Dataset for VQA on Document Images paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Qwen-VL model in the Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Dessurt model in the End-to-end Document Recognition and Understanding with Dessurt paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the Qwen-VL-Chat model in the Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond paper on the DocVQA test dataset? | ANLS, Accuracy |
What metrics were used to measure the VLAB model in the VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the MaMMUT (ours) model in the MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the VALOR model in the VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset paper on the MSVD-QA dataset? | Accuracy |
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 MSVD-QA dataset? | Accuracy |
What metrics were used to measure the mPLUG-2 model in the mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the VideoCoCa model in the VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the GIT model in the GIT: A Generative Image-to-text Transformer for Vision and Language paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the FrozenBiLM+ model in the Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the HiTeA model in the HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the InternVideo model in the InternVideo: General Video Foundation Models via Generative and Discriminative Learning paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the UMT-L (ViT-L/16) model in the Unmasked Teacher: Towards Training-Efficient Video Foundation Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the FrozenBiLM model in the Zero-Shot Video Question Answering via Frozen Bidirectional Language Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the VIOLETv2 model in the An Empirical Study of End-to-End Video-Language Transformers with Masked Visual Modeling paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the MuLTI model in the MuLTI: Efficient Video-and-Language Understanding with MultiWay-Sampler and Multiple Choice Modeling paper on the MSVD-QA dataset? | Accuracy |
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 MSVD-QA dataset? | Accuracy |
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 MSVD-QA dataset? | Accuracy |
What metrics were used to measure the Clover model in the Clover: Towards A Unified Video-Language Alignment and Fusion Model paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the VIOLET + MELTR model in the MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the OmniVL model in the OmniVL:One Foundation Model for Image-Language and Video-Language Tasks paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the VIOLET+ model in the Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the Co-Tokenization model in the Video Question Answering with Iterative Video-Text Co-Tokenization paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the All-in-one-B model in the All in One: Exploring Unified Video-Language Pre-training paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the LRCE model in the Lightweight Recurrent Cross-modal Encoder for Video Question Answering paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the JustAsk+ model in the Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the Just Ask model in the Just Ask: Learning to Answer Questions from Millions of Narrated Videos paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the ALPRO model in the Align and Prompt: Video-and-Language Pre-training with Entity Prompts paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the All-in-one+ model in the Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the DualVGR model in the DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question Answering paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the HCRN model in the Hierarchical Conditional Relation Networks for Video Question Answering paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the SSML model in the Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the HMEMA model in the Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the Co-Mem model in the Motion-Appearance Co-Memory Networks for Video Question Answering paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the ST-VQA model in the TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering paper on the MSVD-QA dataset? | Accuracy |
What metrics were used to measure the Prophet model in the Prompting Large Language Models with Answer Heuristics for Knowledge-based Visual Question Answering paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the PromptCap model in the PromptCap: Prompt-Guided Task-Aware Image Captioning paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the GPV-2 model in the Webly Supervised Concept Expansion for General Purpose Vision Models paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the KRISP model in the KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the ViLBERT - VQA model in the ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the LXMERT model in the LXMERT: Learning Cross-Modality Encoder Representations from Transformers paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the ViLBERT model in the ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the Pythia model in the Pythia v0.1: the Winning Entry to the VQA Challenge 2018 paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
What metrics were used to measure the ViLBERT - OK-VQA model in the ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks paper on the A-OKVQA dataset? | MC Accuracy, DA VQA Score, Accuracy |
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