question stringclasses 1
value | subject stringclasses 1
value | choices listlengths 4 4 | answer class label 4
classes |
|---|---|---|---|
Predict which model least fits with the others | model_modality | [
"Sinkhorn Transformer",
"Tokens-To-Token Vision Transformer",
"Weighted Recurrent Quality Enhancement",
"Segment Sorting"
] | 0A |
Predict which model least fits with the others | model_modality | [
"LiteSeg",
"Multi-partition Embedding Interaction",
"RoIPool",
"InstaBoost"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Genetic Algorithms",
"Recurrent Replay Distributed DQN",
"Rainbow DQN",
"Depth-wise Plane Sweeping"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Co-Correcting",
"OSCAR",
"Dual Contrastive Learning",
"Fourier Contour Embedding"
] | 2C |
Predict which model least fits with the others | model_modality | [
"RFB Net",
"SentencePiece",
"Guided Language to Image Diffusion for Generation and Editing",
"LocalViT"
] | 1B |
Predict which model least fits with the others | model_modality | [
"PermuteFormer",
"ERNIE",
"Flan-T5",
"Random Gaussian Blur"
] | 3D |
Predict which model least fits with the others | model_modality | [
"NoisyNet-A3C",
"RTMDet: An Empirical Study of Designing Real-Time Object Detectors",
"nnFormer",
"Position-Sensitive RoI Pooling"
] | 0A |
Predict which model least fits with the others | model_modality | [
"ViP-DeepLab",
"Diffusion-Convolutional Neural Networks",
"MultiGrain",
"SqueezeNeXt"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Mutual Guidance",
"Invertible NxN Convolution",
"Animatable Reconstruction of Clothed Humans",
"MushroomRL"
] | 3D |
Predict which model least fits with the others | model_modality | [
"YOLOv2",
"Transposed convolution",
"Segmentation of patchy areas in biomedical images based on local edge density estimation",
"Twin Delayed Deep Deterministic"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Active Convolution",
"GLM",
"Pansharpening Network",
"VisualBERT"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Graph Attention Network",
"Hierarchical Entity Graph Convolutional Network",
"PP-YOLOv2",
"Variational Graph Auto Encoder"
] | 2C |
Predict which model least fits with the others | model_modality | [
"bilayer convolutional neural network",
"Attribute2Font",
"Longformer",
"FCOS"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Focus",
"CascadePSP",
"CSPDenseNet",
"Adaptive Bezier-Curve Network"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Fourier Contour Embedding",
"Root-of-Mean-Squared Pooling",
"Kalman Optimization for Value Approximation",
"Asynchronous Interaction Aggregation"
] | 2C |
Predict which model least fits with the others | model_modality | [
"XLNet",
"DynaBERT",
"Transformer-XL",
"Darknet-19"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Style-based Recalibration Module",
"SqueezeBERT",
"RoI Tanh-polar Transform",
"Anycost GAN"
] | 1B |
Predict which model least fits with the others | model_modality | [
"ShuffleNet",
"Drafting Network",
"Stochastic Steady-state Embedding",
"Non-Local Operation"
] | 2C |
Predict which model least fits with the others | model_modality | [
"IFBlock",
"Mobile DenseNet",
"Eligibility Trace",
"ScaleNet"
] | 2C |
Predict which model least fits with the others | model_modality | [
"A2C",
"ACTKR",
"Global and Sliding Window Attention",
"Primal Wasserstein Imitation Learning"
] | 2C |
Predict which model least fits with the others | model_modality | [
"CSPPeleeNet",
"Electric",
"Switch Transformer",
"Categorical Modularity"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Pansharpening Network",
"Taylor Expansion Policy Optimization",
"UNIMO",
"ESPNet"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Hierarchical Entity Graph Convolutional Network",
"Directed Acyclic Graph Neural Network",
"NormFormer",
"LLaMA"
] | 1B |
Predict which model least fits with the others | model_modality | [
"DeepLabv2",
"Stein Variational Policy Gradient",
"Masked Convolution",
"Grab"
] | 1B |
Predict which model least fits with the others | model_modality | [
"ooJpiued",
"High-level backbone",
"AutoAugment",
"MoGA-A"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Position-Sensitive RoIAlign",
"Graph Echo State Network",
"Fast-OCR",
"Probabilistic Anchor Assignment"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Deep Q-Network",
"MushroomRL",
"Double Q-learning",
"Color Jitter"
] | 3D |
Predict which model least fits with the others | model_modality | [
"DynaBERT",
"Primer",
"PAR Transformer",
"Deep Extreme Cut"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Topographic VAE",
"Graph Attention Network v2",
"Feature Intertwiner",
"Dimension-wise Fusion"
] | 1B |
Predict which model least fits with the others | model_modality | [
"PReLU-Net",
"An Easier Data Augmentation",
"Negative Face Recognition",
"UCNet"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Random elastic image morphing",
"Prime Dilated Convolution",
"HITNet",
"Sandwich Transformer"
] | 3D |
Predict which model least fits with the others | model_modality | [
"AutoAugment",
"mBERT",
"DeLighT",
"Linformer"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Deformable Convolution",
"SPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings",
"Kaleido-BERT",
"Q-Learning"
] | 3D |
Predict which model least fits with the others | model_modality | [
"VisualBERT",
"ReasonBERT",
"RepPoints",
"MaxUp"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Submanifold Convolution",
"Informative Sample Mining Network",
"Co-Scale Conv-attentional Image Transformer",
"Reformer"
] | 3D |
Predict which model least fits with the others | model_modality | [
"PnP",
"Deep Graph Infomax",
"ManifoldPlus",
"DeepSIM"
] | 1B |
Predict which model least fits with the others | model_modality | [
"A3C",
"Fixed Factorized Attention",
"Augmented SBERT",
"CodeBERT"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Conditional Variational Auto Encoder",
"CenterNet",
"Squeeze-and-Excitation Block",
"Linformer"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Contextual Graph Markov Model",
"Hyperboloid Embeddings",
"Graph Convolutional Networks for Fake News Detection",
"Hierarchical Variational Autoencoder"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Galactica",
"Grid R-CNN",
"PrivacyNet",
"DAMO-YOLO"
] | 0A |
Predict which model least fits with the others | model_modality | [
"MetaFormer",
"TrOCR",
"Ghost Module",
"GeniePath"
] | 3D |
Predict which model least fits with the others | model_modality | [
"EfficientNet",
"Residual gating mechanism to compose adverb-action representations",
"Low-resolution input",
"wav2vec Unsupervised"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Decentralized Distributed Proximal Policy Optimization",
"Global Convolutional Network",
"Bayesian Reward Extrapolation",
"True Online TD Lambda"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Expected Sarsa",
"Conditional Convolutions for Instance Segmentation",
"You Only Hypothesize Once",
"ShuffleNet V2 Downsampling Block"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Policy Similarity Metric",
"Blended Diffusion",
"Recurrent Replay Distributed DQN",
"TD-Gammon"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Tokens-To-Token Vision Transformer",
"Center-pivot convolution",
"Bort",
"PoolFormer"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Blind Image Decomposition Network",
"PixelCNN",
"Dialogue-Adaptive Pre-training Objective",
"MixNet"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Dimension-wise Fusion",
"Noisy Linear Layer",
"Dutch Eligibility Trace",
"Attention Model"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Neural Cache",
"AutoAugment",
"Flan-T5",
"BP-Transformer"
] | 1B |
Predict which model least fits with the others | model_modality | [
"LR-Net",
"Contextual Word Vectors",
"PReLU-Net",
"Scale-wise Feature Aggregation Module"
] | 1B |
Predict which model least fits with the others | model_modality | [
"FFB6D",
"Sentence-BERT",
"Compact Convolutional Transformers",
"DenseNAS-A"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Local Relation Network",
"AutoEncoder",
"Transformer-XL",
"Sparse Convolutions"
] | 2C |
Predict which model least fits with the others | model_modality | [
"GradientDICE",
"Support-set Based Cross-Supervision",
"HITNet",
"Adversarial Color Enhancement"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Accumulating Eligibility Trace",
"Lbl2Vec",
"Neural Cache",
"CPM-2"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Universal Transformer",
"Parallel Layers",
"Transformer Decoder",
"Dreamix: video diffusion models are general video editors"
] | 3D |
Predict which model least fits with the others | model_modality | [
"MnasNet",
"CubeRE",
"k-Sparse Autoencoder",
"Pixel-BERT"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Generative Adversarial Transformer",
"PGC-DGCNN",
"Diffusion",
"BinaryBERT"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Fragmentation",
"Style Transfer Module",
"Graph Neural Networks with Continual Learning",
"CutMix"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Double Q-learning",
"ClipBERT",
"StyleMapGAN",
"LAPGAN"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Cross-resolution features",
"Rainbow DQN",
"Channel-wise Cross Fusion Transformer",
"EdgeBoxes"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Double DQN",
"LLaMA",
"PLATO-2",
"Gated Convolution Network"
] | 0A |
Predict which model least fits with the others | model_modality | [
"TransferQA",
"CS-GAN",
"Circular Smooth Label",
"Cutout"
] | 0A |
Predict which model least fits with the others | model_modality | [
"RealFormer",
"VL-T5",
"Deep Boltzmann Machine",
"PnP"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Levenshtein Transformer",
"Synthesizer",
"Review-guided Answer Helpfulness Prediction",
"Stochastic Steady-state Embedding"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Orientation Regularized Network",
"PermuteFormer",
"NesT",
"Non Maximum Suppression"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Feature Fusion Module v1",
"FRILL",
"HiFi-GAN",
"wav2vec Unsupervised"
] | 0A |
Predict which model least fits with the others | model_modality | [
"XLSR",
"The Ikshana Hypothesis of Human Scene Understanding Mechanism",
"Jukebox",
"Phase Gradient Heap Integration"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Data-efficient Image Transformer",
"classifier-guidance",
"CenterMask",
"Principal Neighbourhood Aggregation"
] | 3D |
Predict which model least fits with the others | model_modality | [
"DeepIR",
"Composed Video Retrieval",
"Recurrent Event Network",
"GreedyNAS-A"
] | 2C |
Predict which model least fits with the others | model_modality | [
"CutBlur",
"Detailed Expression Capture and Animation",
"Invertible NxN Convolution",
"A3C"
] | 3D |
Predict which model least fits with the others | model_modality | [
"GPT-Neo",
"CDCC-NET",
"ENet Bottleneck",
"Convolutional LSTM based Residual Network"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Contextual Word Vectors",
"MelGAN",
"FRILL",
"Jukebox"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Self-Attention Network",
"CondConv",
"Parallel Layers",
"Bi3D"
] | 2C |
Predict which model least fits with the others | model_modality | [
"XLSR",
"Temporally Consistent Spatial Augmentation",
"Random Gaussian Blur",
"Models Genesis"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Libra R-CNN",
"Funnel Transformer",
"Dual Contrastive Learning",
"ClipBERT"
] | 0A |
Predict which model least fits with the others | model_modality | [
"BLOOMZ",
"Routing Transformer",
"Meena",
"REINFORCE"
] | 3D |
Predict which model least fits with the others | model_modality | [
"NoisyNet-DQN",
"Wasserstein GAN (Gradient Penalty)",
"RFB Net",
"Noise2Fast"
] | 0A |
Predict which model least fits with the others | model_modality | [
"GoogLeNet",
"Soft-NMS",
"MinCut Pooling",
"Convolutional Vision Transformer"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Contextual Word Vectors",
"Graph Attention Network",
"AdaGPR",
"Network Embedding as Matrix Factorization:"
] | 0A |
Predict which model least fits with the others | model_modality | [
"PointNet",
"RoIAlign",
"RESCAL with Relation Prediction",
"RandWire"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Diffusion-Convolutional Neural Networks",
"Ape-X DPG",
"DouZero",
"Experience Replay"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Genetic Algorithms",
"Topographic VAE",
"DeepMask",
"Poisson Flow Generative Models"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Continuous Kernel Convolution",
"Variational Graph Auto Encoder",
"VGG and variational Model Decomposition",
"Dilated convolution with learnable spacings"
] | 1B |
Predict which model least fits with the others | model_modality | [
"RAG",
"Grab",
"SqueezeNeXt",
"Self-Attention Guidance"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Improved Gravitational Search algorithm",
"Mirror Descent Policy Optimization",
"A2C",
"CSPResNeXt"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Spherical Graph Convolutional Network",
"Fire Module",
"LFPNet with test time augmentation",
"RIFE"
] | 0A |
Predict which model least fits with the others | model_modality | [
"Levenshtein Transformer",
"Funnel Transformer",
"Global and Sliding Window Attention",
"ACER"
] | 3D |
Predict which model least fits with the others | model_modality | [
"StyleGAN2",
"Partition Filter Network",
"Discriminative Adversarial Search",
"Categorical Modularity"
] | 0A |
Predict which model least fits with the others | model_modality | [
"A3C",
"FLAVR",
"True Online TD Lambda",
"Attention Model"
] | 1B |
Predict which model least fits with the others | model_modality | [
"Meta Face Recognition",
"YOLOv4",
"Spatial Group-wise Enhance",
"POMO"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Seq2Edits",
"Sinkhorn Transformer",
"GPT",
"Style-based Recalibration Module"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Adversarial Color Enhancement",
"Local Patch Interaction",
"Genetic Algorithms",
"Unified VLP"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Ape-X",
"Transformer",
"ReasonBERT",
"MuVER"
] | 0A |
Predict which model least fits with the others | model_modality | [
"ARMA GNN",
"Revision Network",
"Bilateral Grid",
"Feature Pyramid Grid"
] | 0A |
Predict which model least fits with the others | model_modality | [
"PrivacyNet",
"Inception-ResNet-v2",
"GPT-4",
"EdgeBoxes"
] | 2C |
Predict which model least fits with the others | model_modality | [
"SepFormer",
"WaveNet",
"IoU-Net",
"wav2vec Unsupervised"
] | 2C |
Predict which model least fits with the others | model_modality | [
"Phase Gradient Heap Integration",
"Tacotron2",
"Differentiable Digital Signal Processing",
"DouZero"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Cascade Mask R-CNN",
"CenterMask",
"MoCo v3",
"SentencePiece"
] | 3D |
Predict which model least fits with the others | model_modality | [
"Proximal Policy Optimization",
"Topographic VAE",
"SRGAN",
"Class activation guide"
] | 0A |
Predict which model least fits with the others | model_modality | [
"SCARLET",
"DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement",
"Dreamix: video diffusion models are general video editors",
"PAUSE"
] | 3D |
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