Split (1)

train · 300k rows

paper_url stringlengths 36 81	paper_title stringlengths 1 242 ⌀	paper_arxiv_id stringlengths 9 16 ⌀	paper_url_abs stringlengths 18 314	paper_url_pdf stringlengths 21 935 ⌀	repo_url stringlengths 26 200	is_official bool 2 classes	mentioned_in_paper bool 2 classes	mentioned_in_github bool 2 classes	framework stringclasses 9 values
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-large	Very Deep Convolutional Networks for Large-Scale Image Recognition	1409.1556	http://arxiv.org/abs/1409.1556v6	http://arxiv.org/pdf/1409.1556v6.pdf	https://github.com/RuoyuGuo/Visualising-Image-Classification-Models-and-Saliency-Maps	false	false	true	tf
https://paperswithcode.com/paper/exploring-modern-gpu-memory-system-design	Exploring Modern GPU Memory System Design Challenges through Accurate Modeling	1810.07269	http://arxiv.org/abs/1810.07269v1	http://arxiv.org/pdf/1810.07269v1.pdf	https://github.com/prdalmia/gpgpu-sim-tlb	false	false	true	pytorch
https://paperswithcode.com/paper/a-simple-exponential-family-framework-for	A Simple Exponential Family Framework for Zero-Shot Learning	1707.08040	http://arxiv.org/abs/1707.08040v3	http://arxiv.org/pdf/1707.08040v3.pdf	https://github.com/vkverma01/Zero-Shot	true	true	true	none
https://paperswithcode.com/paper/from-word-embeddings-to-item-recommendation	From Word Embeddings to Item Recommendation	1601.01356	http://arxiv.org/abs/1601.01356v3	http://arxiv.org/pdf/1601.01356v3.pdf	https://github.com/mgulcin/DL_Rec	false	false	true	none
https://paperswithcode.com/paper/190807906	PCRNet: Point Cloud Registration Network using PointNet Encoding	1908.07906	https://arxiv.org/abs/1908.07906v2	https://arxiv.org/pdf/1908.07906v2.pdf	https://github.com/vinits5/pcrnet_pytorch	true	false	true	pytorch
https://paperswithcode.com/paper/flavio-a-python-package-for-flavour-and	flavio: a Python package for flavour and precision phenomenology in the Standard Model and beyond	1810.08132	http://arxiv.org/abs/1810.08132v1	http://arxiv.org/pdf/1810.08132v1.pdf	https://github.com/smelli/smelli	false	false	true	none
https://paperswithcode.com/paper/nvisii-a-scriptable-tool-for-photorealistic	NViSII: A Scriptable Tool for Photorealistic Image Generation	2105.13962	https://arxiv.org/abs/2105.13962v1	https://arxiv.org/pdf/2105.13962v1.pdf	https://github.com/owl-project/ViSII	false	false	true	none
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-text	Very Deep Convolutional Networks for Text Classification	1606.01781	http://arxiv.org/abs/1606.01781v2	http://arxiv.org/pdf/1606.01781v2.pdf	https://github.com/nithishkaviyan/Sentiment-Analysis-of-Yelp-Reviews	false	false	true	pytorch
https://paperswithcode.com/paper/estimating-seal-pup-production-in-the	Estimating seal pup production in the Greenland Sea using Bayesian hierarchical modeling	1808.09254	https://arxiv.org/abs/1808.09254v2	https://arxiv.org/pdf/1808.09254v2.pdf	https://github.com/PointProcess/SealCoxProcess-JRSSC-code	false	false	true	none
https://paperswithcode.com/paper/democratizing-contrastive-language-image-pre	Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision	2203.05796	https://arxiv.org/abs/2203.05796v1	https://arxiv.org/pdf/2203.05796v1.pdf	https://github.com/sense-gvt/declip	true	true	true	pytorch
https://paperswithcode.com/paper/pose-normalized-image-generation-for-person	Pose-Normalized Image Generation for Person Re-identification	1712.02225	http://arxiv.org/abs/1712.02225v6	http://arxiv.org/pdf/1712.02225v6.pdf	https://github.com/NVlabs/DG-Net	false	false	false	pytorch
https://paperswithcode.com/paper/simulating-content-consistent-vehicle	Simulating Content Consistent Vehicle Datasets with Attribute Descent	1912.08855	https://arxiv.org/abs/1912.08855v2	https://arxiv.org/pdf/1912.08855v2.pdf	https://github.com/yorkeyao/VehicleX	true	true	true	pytorch
https://paperswithcode.com/paper/robust-group-synchronization-via-cycle-edge	Robust Group Synchronization via Cycle-Edge Message Passing	1912.11347	https://arxiv.org/abs/1912.11347v3	https://arxiv.org/pdf/1912.11347v3.pdf	https://github.com/yunpeng-shi/CEMP	true	true	false	none
https://paperswithcode.com/paper/partial-fc-training-10-million-identities-on	Partial FC: Training 10 Million Identities on a Single Machine	2010.05222	https://arxiv.org/abs/2010.05222v2	https://arxiv.org/pdf/2010.05222v2.pdf	https://github.com/JDAI-CV/fast-reid	false	false	false	pytorch
https://paperswithcode.com/paper/tab2know-building-a-knowledge-base-from	Tab2Know: Building a Knowledge Base from Tables in Scientific Papers	2107.13306	https://arxiv.org/abs/2107.13306v1	https://arxiv.org/pdf/2107.13306v1.pdf	https://github.com/karmaresearch/tab2know	true	true	false	none
https://paperswithcode.com/paper/inference-and-forecasting-for-continuous-time	Inference and forecasting for continuous-time integer-valued trawl processes	2107.03674	https://arxiv.org/abs/2107.03674v3	https://arxiv.org/pdf/2107.03674v3.pdf	https://github.com/mbennedsen/Likelihood-based-IVT	true	true	false	none
https://paperswithcode.com/paper/mintrec2-0-a-large-scale-benchmark-dataset	MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations	2403.10943	https://arxiv.org/abs/2403.10943v4	https://arxiv.org/pdf/2403.10943v4.pdf	https://github.com/thuiar/mintrec2.0	true	true	false	pytorch
https://paperswithcode.com/paper/faultnet-a-deep-convolutional-neural-network	FaultNet: A Deep Convolutional Neural Network for bearing fault classification	2010.02146	https://arxiv.org/abs/2010.02146v2	https://arxiv.org/pdf/2010.02146v2.pdf	https://github.com/BaratiLab/FaultNet	true	true	true	none
https://paperswithcode.com/paper/physics-informed-neural-networks-for-power	Physics-Informed Neural Networks for Power Systems	1911.03737	https://arxiv.org/abs/1911.03737v3	https://arxiv.org/pdf/1911.03737v3.pdf	https://github.com/gmisy/Phycics-informed-NN-for-Power-Systems	false	false	true	tf
https://paperswithcode.com/paper/proximal-policy-optimization-algorithms	Proximal Policy Optimization Algorithms	1707.06347	http://arxiv.org/abs/1707.06347v2	http://arxiv.org/pdf/1707.06347v2.pdf	https://github.com/jfpettit/flare	false	false	true	pytorch
https://paperswithcode.com/paper/susy-les-houches-accord-2	SUSY Les Houches Accord 2	0801.0045	http://arxiv.org/abs/0801.0045v3	http://arxiv.org/pdf/0801.0045v3.pdf	https://github.com/misho104/yaslha	false	false	true	none
https://paperswithcode.com/paper/a-guide-to-convolution-arithmetic-for-deep	A guide to convolution arithmetic for deep learning	1603.07285	http://arxiv.org/abs/1603.07285v2	http://arxiv.org/pdf/1603.07285v2.pdf	https://github.com/marbleton/FPGA_MNIST	false	false	true	pytorch
https://paperswithcode.com/paper/don-t-stop-pretraining-adapt-language-models	Don't Stop Pretraining: Adapt Language Models to Domains and Tasks	2004.10964	https://arxiv.org/abs/2004.10964v3	https://arxiv.org/pdf/2004.10964v3.pdf	https://github.com/allenai/dont-stop-pretraining	true	true	false	pytorch
https://paperswithcode.com/paper/hinglishnlp-fine-tuned-language-models-for	HinglishNLP: Fine-tuned Language Models for Hinglish Sentiment Detection	2008.09820	https://arxiv.org/abs/2008.09820v1	https://arxiv.org/pdf/2008.09820v1.pdf	https://github.com/NirantK/Hinglish	true	true	false	pytorch
https://paperswithcode.com/paper/a-low-cost-flexible-and-portable-volumetric	A Low-Cost, Flexible and Portable Volumetric Capturing System	1909.01207	https://arxiv.org/abs/1909.01207v1	https://arxiv.org/pdf/1909.01207v1.pdf	https://github.com/VCL3D/VolumetricCapture	true	true	true	none
https://paperswithcode.com/paper/deep-soft-procrustes-for-markerless	Deep Soft Procrustes for Markerless Volumetric Sensor Alignment	2003.10176	https://arxiv.org/abs/2003.10176v1	https://arxiv.org/pdf/2003.10176v1.pdf	https://github.com/VCL3D/VolumetricCapture	false	false	true	none
https://paperswithcode.com/paper/conversations-with-search-engines	Conversations with Search Engines: SERP-based Conversational Response Generation	2004.14162	https://arxiv.org/abs/2004.14162v2	https://arxiv.org/pdf/2004.14162v2.pdf	https://github.com/PengjieRen/CaSE-1.0	true	true	false	pytorch
https://paperswithcode.com/paper/boilerplate-removal-using-a-neural-sequence	Boilerplate Removal using a Neural Sequence Labeling Model	2004.14294	https://arxiv.org/abs/2004.14294v1	https://arxiv.org/pdf/2004.14294v1.pdf	https://github.com/mrjleo/boilernet	true	true	false	tf
https://paperswithcode.com/paper/lifelong-learning-in-evolving-graphs-with	Lifelong Learning on Evolving Graphs Under the Constraints of Imbalanced Classes and New Classes	2112.10558	https://arxiv.org/abs/2112.10558v2	https://arxiv.org/pdf/2112.10558v2.pdf	https://github.com/lgalke/lifelong-learning	true	true	false	pytorch
https://paperswithcode.com/paper/towards-efficient-covid-19-ct-annotation-a	Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection Segmentation	2004.12537	https://arxiv.org/abs/2004.12537v2	https://arxiv.org/pdf/2004.12537v2.pdf	https://github.com/JunMa11/COVID-19-CT-Seg-Benchmark	false	false	true	none
https://paperswithcode.com/paper/jack-the-reader-a-machine-reading-framework	Jack the Reader - A Machine Reading Framework	1806.08727	http://arxiv.org/abs/1806.08727v1	http://arxiv.org/pdf/1806.08727v1.pdf	https://github.com/uclnlp/jack	false	false	true	tf
https://paperswithcode.com/paper/making-neural-qa-as-simple-as-possible-but	Making Neural QA as Simple as Possible but not Simpler	1703.04816	http://arxiv.org/abs/1703.04816v3	http://arxiv.org/pdf/1703.04816v3.pdf	https://github.com/uclnlp/jack	false	false	true	tf
https://paperswithcode.com/paper/a-disentangling-invertible-interpretation	A Disentangling Invertible Interpretation Network for Explaining Latent Representations	2004.13166	https://arxiv.org/abs/2004.13166v1	https://arxiv.org/pdf/2004.13166v1.pdf	https://github.com/CompVis/iin	false	false	true	pytorch
https://paperswithcode.com/paper/weakly-supervised-open-retrieval	Weakly-Supervised Open-Retrieval Conversational Question Answering	2103.02537	https://arxiv.org/abs/2103.02537v1	https://arxiv.org/pdf/2103.02537v1.pdf	https://github.com/prdwb/ws-orconvqa	true	true	false	pytorch
https://paperswithcode.com/paper/aggregate-hardware-impairments-over-mixed-rf	Aggregate Hardware Impairments Over Mixed RF/FSO Relaying Systems With Outdated CSI	1902.03177	http://arxiv.org/abs/1902.03177v1	http://arxiv.org/pdf/1902.03177v1.pdf	https://github.com/ebalti/Malaga-Distribution	true	false	false	none
https://paperswithcode.com/paper/conditional-generative-adversarial-nets	Conditional Generative Adversarial Nets	1411.1784	https://arxiv.org/abs/1411.1784v1	https://arxiv.org/pdf/1411.1784v1.pdf	https://github.com/bhiziroglu/Conditional-Generative-Adversarial-Network	false	false	true	pytorch
https://paperswithcode.com/paper/inverse-kinematics-for-serial-kinematic	Inverse Kinematics for Serial Kinematic Chains via Sum of Squares Optimization	1909.09318	https://arxiv.org/abs/1909.09318v2	https://arxiv.org/pdf/1909.09318v2.pdf	https://github.com/utiasSTARS/sos-ik	true	true	true	none
https://paperswithcode.com/paper/how-low-is-too-low-a-computational	How Low is Too Low? A Computational Perspective on Extremely Low-Resource Languages	2105.14515	https://arxiv.org/abs/2105.14515v1	https://arxiv.org/pdf/2105.14515v1.pdf	https://github.com/cdli-gh/Semi-Supervised-NMT-for-Sumerian-English	true	false	false	pytorch
https://paperswithcode.com/paper/voxlingua107-a-dataset-for-spoken-language-1	VoxLingua107: a Dataset for Spoken Language Recognition	2011.12998	https://arxiv.org/abs/2011.12998v1	https://arxiv.org/pdf/2011.12998v1.pdf	https://github.com/rush-d/spoken-language-identification	false	false	true	none
https://paperswithcode.com/paper/warpgan-automatic-caricature-generation	WarpGAN: Automatic Caricature Generation	1811.10100	http://arxiv.org/abs/1811.10100v3	http://arxiv.org/pdf/1811.10100v3.pdf	https://github.com/ronny3050/AdvFaces	false	false	true	tf
https://paperswithcode.com/paper/advfaces-adversarial-face-synthesis	AdvFaces: Adversarial Face Synthesis	1908.05008	https://arxiv.org/abs/1908.05008v1	https://arxiv.org/pdf/1908.05008v1.pdf	https://github.com/ronny3050/AdvFaces	false	false	true	tf
https://paperswithcode.com/paper/segan-speech-enhancement-generative	SEGAN: Speech Enhancement Generative Adversarial Network	1703.09452	http://arxiv.org/abs/1703.09452v3	http://arxiv.org/pdf/1703.09452v3.pdf	https://github.com/usimarit/TiramisuASR	false	false	true	tf
https://paperswithcode.com/paper/simple-scalable-and-stable-variational-deep	Simple, Scalable, and Stable Variational Deep Clustering	2005.08047	https://arxiv.org/abs/2005.08047v2	https://arxiv.org/pdf/2005.08047v2.pdf	https://github.com/king/s3vdc	true	true	true	tf
https://paperswithcode.com/paper/a-neural-algorithm-of-artistic-style	A Neural Algorithm of Artistic Style	1508.06576	http://arxiv.org/abs/1508.06576v2	http://arxiv.org/pdf/1508.06576v2.pdf	https://github.com/kanishk16/Image-Style-Transfer	false	false	true	pytorch
https://paperswithcode.com/paper/a-mathematical-formalization-of-hierarchical	A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler	1601.06116	http://arxiv.org/abs/1601.06116v3	http://arxiv.org/pdf/1601.06116v3.pdf	https://github.com/mrkrynmdsco/htm-python	false	false	true	none
https://paperswithcode.com/paper/density-encoding-enables-resource-efficient	Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks	1909.09153	https://arxiv.org/abs/1909.09153v2	https://arxiv.org/pdf/1909.09153v2.pdf	https://github.com/sweetwenwen/Stochastic-computing-based-neural-network-accelerator	false	false	true	none
https://paperswithcode.com/paper/a-distance-preserving-matrix-sketch	A Distance-preserving Matrix Sketch	2009.03979	https://arxiv.org/abs/2009.03979v3	https://arxiv.org/pdf/2009.03979v3.pdf	https://github.com/hrluo/DistancePreservingMatrixSketch	true	true	true	none
https://paperswithcode.com/paper/neural-collaborative-filtering	Neural Collaborative Filtering	1708.05031	http://arxiv.org/abs/1708.05031v2	http://arxiv.org/pdf/1708.05031v2.pdf	https://github.com/EdoardoPona/Neural-Collaborative-Filtering	false	false	true	pytorch
https://paperswithcode.com/paper/jobskape-a-framework-for-generating-synthetic	JOBSKAPE: A Framework for Generating Synthetic Job Postings to Enhance Skill Matching	2402.03242	https://arxiv.org/abs/2402.03242v1	https://arxiv.org/pdf/2402.03242v1.pdf	https://github.com/magantoine/jobskape	true	true	true	pytorch
https://paperswithcode.com/paper/practical-graph-isomorphism-ii	Practical graph isomorphism, II	1301.1493	http://arxiv.org/abs/1301.1493v1	http://arxiv.org/pdf/1301.1493v1.pdf	https://github.com/Mith13/Graphs-isomorphism	false	false	true	none
https://paperswithcode.com/paper/line-large-scale-information-network	LINE: Large-scale Information Network Embedding	1503.03578	http://arxiv.org/abs/1503.03578v1	http://arxiv.org/pdf/1503.03578v1.pdf	https://github.com/2myeonggyu/Graph-Embedding	false	false	true	none
https://paperswithcode.com/paper/imagenet-classification-with-deep	ImageNet Classification with Deep Convolutional Neural Networks	null	http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks	http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf	https://github.com/mindspore-courses/heads-on-mindspore/blob/main/1-best-practice/models/alexnet.py	false	false	false	mindspore
https://paperswithcode.com/paper/fully-convolutional-networks-for-semantic-1	Fully Convolutional Networks for Semantic Segmentation	1411.4038	http://arxiv.org/abs/1411.4038v2	http://arxiv.org/pdf/1411.4038v2.pdf	https://github.com/muramasa8191/DeepLearning	false	false	true	tf
https://paperswithcode.com/paper/instance-based-counterfactual-explanations	Instance-based Counterfactual Explanations for Time Series Classification	2009.13211	https://arxiv.org/abs/2009.13211v2	https://arxiv.org/pdf/2009.13211v2.pdf	https://github.com/e-delaney/Instance-Based_CFE_TSC	true	true	false	tf
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	1810.04805	https://arxiv.org/abs/1810.04805v2	https://arxiv.org/pdf/1810.04805v2.pdf	https://github.com/Holldean/BERT-Pruning	false	false	true	tf
https://paperswithcode.com/paper/structured-pruning-of-large-language-models	Structured Pruning of Large Language Models	1910.04732	https://arxiv.org/abs/1910.04732v2	https://arxiv.org/pdf/1910.04732v2.pdf	https://github.com/Holldean/BERT-Pruning	false	false	true	tf
https://paperswithcode.com/paper/pretraining-based-natural-language-generation	Pretraining-Based Natural Language Generation for Text Summarization	1902.09243	http://arxiv.org/abs/1902.09243v2	http://arxiv.org/pdf/1902.09243v2.pdf	https://github.com/praveenjune17/BERT_text_summarisation	false	false	true	tf
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	1810.04805	https://arxiv.org/abs/1810.04805v2	https://arxiv.org/pdf/1810.04805v2.pdf	https://github.com/Zehui127/SQUAD_BERT	false	false	true	tf
https://paperswithcode.com/paper/sdf-srn-learning-signed-distance-3d-object	SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images	2010.10505	https://arxiv.org/abs/2010.10505v1	https://arxiv.org/pdf/2010.10505v1.pdf	https://github.com/chenhsuanlin/signed-distance-SRN	true	false	true	pytorch
https://paperswithcode.com/paper/multifit-efficient-multi-lingual-language	MultiFiT: Efficient Multi-lingual Language Model Fine-tuning	1909.04761	https://arxiv.org/abs/1909.04761v2	https://arxiv.org/pdf/1909.04761v2.pdf	https://github.com/n-waves/multifit	false	false	true	none
https://paperswithcode.com/paper/rtfm-generalising-to-novel-environment	RTFM: Generalising to Novel Environment Dynamics via Reading	1910.08210	https://arxiv.org/abs/1910.08210v6	https://arxiv.org/pdf/1910.08210v6.pdf	https://github.com/facebookresearch/RTFM	false	false	true	none
https://paperswithcode.com/paper/what-are-people-asking-about-covid-19-a	What Are People Asking About COVID-19? A Question Classification Dataset	2005.12522	https://arxiv.org/abs/2005.12522v3	https://arxiv.org/pdf/2005.12522v3.pdf	https://github.com/JerryWei03/COVID-Q	true	true	true	none
https://paperswithcode.com/paper/gnn3dmot-graph-neural-network-for-3d-multi	GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking With 2D-3D Multi-Feature Learning	null	http://openaccess.thecvf.com/content_CVPR_2020/html/Weng_GNN3DMOT_Graph_Neural_Network_for_3D_Multi-Object_Tracking_With_2D-3D_CVPR_2020_paper.html	http://openaccess.thecvf.com/content_CVPR_2020/papers/Weng_GNN3DMOT_Graph_Neural_Network_for_3D_Multi-Object_Tracking_With_2D-3D_CVPR_2020_paper.pdf	https://github.com/xinshuoweng/GNN3DMOT	true	true	false	pytorch
https://paperswithcode.com/paper/mpnet-masked-and-permuted-pre-training-for	MPNet: Masked and Permuted Pre-training for Language Understanding	2004.09297	https://arxiv.org/abs/2004.09297v2	https://arxiv.org/pdf/2004.09297v2.pdf	https://github.com/JunnYu/paddle-mpnet	false	false	false	paddle
https://paperswithcode.com/paper/logical-inference-for-counting-on-semi	Logical Inference for Counting on Semi-structured Tables	2204.07803	https://arxiv.org/abs/2204.07803v2	https://arxiv.org/pdf/2204.07803v2.pdf	https://github.com/ynklab/sst_count	true	true	false	none
https://paperswithcode.com/paper/contrastive-learning-with-hard-negative	Contrastive Learning with Hard Negative Entities for Entity Set Expansion	2204.07789	https://arxiv.org/abs/2204.07789v2	https://arxiv.org/pdf/2204.07789v2.pdf	https://github.com/geekjuruo/probexpan	true	true	false	pytorch
https://paperswithcode.com/paper/reordering-examples-helps-during-priming	Reordering Examples Helps during Priming-based Few-Shot Learning	2106.01751	https://arxiv.org/abs/2106.01751v1	https://arxiv.org/pdf/2106.01751v1.pdf	https://github.com/SawanKumar28/pero	true	true	false	pytorch
https://paperswithcode.com/paper/conversational-neuro-symbolic-commonsense	Conversational Neuro-Symbolic Commonsense Reasoning	2006.10022	https://arxiv.org/abs/2006.10022v3	https://arxiv.org/pdf/2006.10022v3.pdf	https://github.com/ForoughA/CORGI	true	true	true	pytorch
https://paperswithcode.com/paper/depth-aware-video-frame-interpolation	Depth-Aware Video Frame Interpolation	1904.00830	http://arxiv.org/abs/1904.00830v1	http://arxiv.org/pdf/1904.00830v1.pdf	https://github.com/BurguerJohn/Dain-App	false	false	false	pytorch
https://paperswithcode.com/paper/planning-to-explore-via-self-supervised-world	Planning to Explore via Self-Supervised World Models	2005.05960	https://arxiv.org/abs/2005.05960v2	https://arxiv.org/pdf/2005.05960v2.pdf	https://github.com/ramanans1/plan2explore	true	false	false	tf
https://paperswithcode.com/paper/quota-based-debiasing-can-decrease	Quota-based debiasing can decrease representation of already underrepresented groups	2006.07647	https://arxiv.org/abs/2006.07647v1	https://arxiv.org/pdf/2006.07647v1.pdf	https://github.com/ibsmirnov/debiasing	true	true	true	none
https://paperswithcode.com/paper/efficientdet-scalable-and-efficient-object	EfficientDet: Scalable and Efficient Object Detection	1911.09070	https://arxiv.org/abs/1911.09070v7	https://arxiv.org/pdf/1911.09070v7.pdf	https://github.com/JensSettelmeier/EfficientDet-DeepSORT-Tracker	false	false	true	pytorch
https://paperswithcode.com/paper/selection-bias-tracking-and-detailed-subset	Selection Bias Tracking and Detailed Subset Comparison for High-Dimensional Data	1906.07625	https://arxiv.org/abs/1906.07625v2	https://arxiv.org/pdf/1906.07625v2.pdf	https://github.com/VACLab/CadenceEVA	false	false	true	none
https://paperswithcode.com/paper/simple-online-and-realtime-tracking-with-a	Simple Online and Realtime Tracking with a Deep Association Metric	1703.07402	http://arxiv.org/abs/1703.07402v1	http://arxiv.org/pdf/1703.07402v1.pdf	https://github.com/JensSettelmeier/EfficientDet-DeepSORT-Tracker	false	false	true	pytorch
https://paperswithcode.com/paper/pseudo-labeling-and-confirmation-bias-in-deep	Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning	1908.02983	https://arxiv.org/abs/1908.02983v5	https://arxiv.org/pdf/1908.02983v5.pdf	https://github.com/EricArazo/PseudoLabeling	false	false	true	pytorch
https://paperswithcode.com/paper/selective-kernel-networks	Selective Kernel Networks	1903.06586	http://arxiv.org/abs/1903.06586v2	http://arxiv.org/pdf/1903.06586v2.pdf	https://github.com/implus/PytorchInsight	false	false	true	pytorch
https://paperswithcode.com/paper/post-hoc-methods-for-debiasing-neural	Intra-Processing Methods for Debiasing Neural Networks	2006.08564	https://arxiv.org/abs/2006.08564v2	https://arxiv.org/pdf/2006.08564v2.pdf	https://github.com/realityengines/post_hoc_debiasing	true	true	true	pytorch
https://paperswithcode.com/paper/deep-packet-a-novel-approach-for-encrypted	Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning	1709.02656	http://arxiv.org/abs/1709.02656v3	http://arxiv.org/pdf/1709.02656v3.pdf	https://github.com/mhwong2007/Deep-Packet	false	false	false	pytorch
https://paperswithcode.com/paper/robust-differentially-private-training-of	On the effect of normalization layers on Differentially Private training of deep Neural networks	2006.10919	https://arxiv.org/abs/2006.10919v2	https://arxiv.org/pdf/2006.10919v2.pdf	https://github.com/uds-lsv/SIDP	true	true	true	pytorch
https://paperswithcode.com/paper/neural-combinatorial-optimization-with	Neural Combinatorial Optimization with Reinforcement Learning	1611.09940	http://arxiv.org/abs/1611.09940v3	http://arxiv.org/pdf/1611.09940v3.pdf	https://github.com/Rintarooo/TSP_DRL_PointerNet	false	false	true	pytorch
https://paperswithcode.com/paper/pointer-networks	Pointer Networks	1506.03134	http://arxiv.org/abs/1506.03134v2	http://arxiv.org/pdf/1506.03134v2.pdf	https://github.com/Rintarooo/TSP_DRL_PointerNet	false	false	true	pytorch
https://paperswithcode.com/paper/oops-predicting-unintentional-action-in-video	Oops! Predicting Unintentional Action in Video	1911.11206	https://arxiv.org/abs/1911.11206v1	https://arxiv.org/pdf/1911.11206v1.pdf	https://github.com/cvlab-columbia/oops	false	false	false	pytorch
https://paperswithcode.com/paper/mining-persistent-activity-in-continually	Mining Persistent Activity in Continually Evolving Networks	2006.15410	https://arxiv.org/abs/2006.15410v1	https://arxiv.org/pdf/2006.15410v1.pdf	https://github.com/GemsLab/PENminer	true	true	false	none
https://paperswithcode.com/paper/attention-is-all-you-need	Attention Is All You Need	1706.03762	https://arxiv.org/abs/1706.03762v7	https://arxiv.org/pdf/1706.03762v7.pdf	https://github.com/AssafSinger94/sigmorphon-2020-inflection	false	false	true	pytorch
https://paperswithcode.com/paper/modeling-relational-data-with-graph	Modeling Relational Data with Graph Convolutional Networks	1703.06103	http://arxiv.org/abs/1703.06103v4	http://arxiv.org/pdf/1703.06103v4.pdf	https://github.com/INK-USC/MHGRN	false	false	true	pytorch
https://paperswithcode.com/paper/kagnet-knowledge-aware-graph-networks-for	KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning	1909.02151	https://arxiv.org/abs/1909.02151v1	https://arxiv.org/pdf/1909.02151v1.pdf	https://github.com/INK-USC/MHGRN	false	false	true	pytorch
https://paperswithcode.com/paper/toward-the-first-quantum-simulation-with	Toward the first quantum simulation with quantum speedup	1711.10980	http://arxiv.org/abs/1711.10980v1	http://arxiv.org/pdf/1711.10980v1.pdf	https://github.com/njross/simcount	true	true	true	none
https://paperswithcode.com/paper/port-hamiltonian-approach-to-neural-network	Port-Hamiltonian Approach to Neural Network Training	1909.02702	https://arxiv.org/abs/1909.02702v1	https://arxiv.org/pdf/1909.02702v1.pdf	https://github.com/esclear/ph-nn	false	false	true	tf
https://paperswithcode.com/paper/the-shapley-value-of-coalition-of-variables	The Shapley Value of coalition of variables provides better explanations	2103.13342	https://arxiv.org/abs/2103.13342v3	https://arxiv.org/pdf/2103.13342v3.pdf	https://github.com/salimamoukou/acv00	true	true	false	none
https://paperswithcode.com/paper/gspn-generative-shape-proposal-network-for-3d	GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud	1812.03320	http://arxiv.org/abs/1812.03320v1	http://arxiv.org/pdf/1812.03320v1.pdf	https://github.com/ericyi/GSPN	true	false	true	tf
https://paperswithcode.com/paper/yolact-better-real-time-instance-segmentation	YOLACT++: Better Real-time Instance Segmentation	1912.06218	https://arxiv.org/abs/1912.06218v2	https://arxiv.org/pdf/1912.06218v2.pdf	https://github.com/2023-MindSpore-1/ms-code-217/tree/main/Yolact%2B%2B	false	false	false	mindspore
https://paperswithcode.com/paper/feature-pyramid-networks-for-object-detection	Feature Pyramid Networks for Object Detection	1612.03144	http://arxiv.org/abs/1612.03144v2	http://arxiv.org/pdf/1612.03144v2.pdf	https://github.com/daxiapazi/faster-rcnn	false	false	true	tf
https://paperswithcode.com/paper/yolo9000-better-faster-stronger	YOLO9000: Better, Faster, Stronger	1612.08242	http://arxiv.org/abs/1612.08242v1	http://arxiv.org/pdf/1612.08242v1.pdf	https://github.com/TheClub4/car-detection-yolov2	false	false	true	tf
https://paperswithcode.com/paper/image-style-transfer-using-convolutional	Image Style Transfer Using Convolutional Neural Networks	null	http://openaccess.thecvf.com/content_cvpr_2016/html/Gatys_Image_Style_Transfer_CVPR_2016_paper.html	http://openaccess.thecvf.com/content_cvpr_2016/papers/Gatys_Image_Style_Transfer_CVPR_2016_paper.pdf	https://github.com/gsurma/style_transfer/blob/master/style-transfer.ipynb	false	false	false	none
https://paperswithcode.com/paper/pic-permutation-invariant-critic-for-multi	PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning	1911.00025	https://arxiv.org/abs/1911.00025v1	https://arxiv.org/pdf/1911.00025v1.pdf	https://github.com/IouJenLiu/PIC	true	true	true	pytorch
https://paperswithcode.com/paper/efficient-graph-similarity-computation-with	Efficient Graph Similarity Computation with Alignment Regularization	2406.14929	https://arxiv.org/abs/2406.14929v1	https://arxiv.org/pdf/2406.14929v1.pdf	https://github.com/jhuow/eric	true	true	false	pytorch
https://paperswithcode.com/paper/validations-and-corrections-of-the-sfd-and	Validations and Corrections of the SFD and Planck Reddening Maps Based on LAMOST and Gaia Data	2204.01521	https://arxiv.org/abs/2204.01521v3	https://arxiv.org/pdf/2204.01521v3.pdf	https://github.com/qy-sunyang/extinction-maps-correction	true	true	true	none
https://paperswithcode.com/paper/fake-review-detection-using-behavioral-and	Fake Review Detection Using Behavioral and Contextual Features	2003.00807	https://arxiv.org/abs/2003.00807v1	https://arxiv.org/pdf/2003.00807v1.pdf	https://github.com/JayKumarr/Fake-Review-Detection	false	false	true	none
https://paperswithcode.com/paper/assd-attentive-single-shot-multibox-detector	ASSD: Attentive Single Shot Multibox Detector	1909.12456	https://arxiv.org/abs/1909.12456v1	https://arxiv.org/pdf/1909.12456v1.pdf	https://github.com/yijingru/ASSD-Pytorch	true	true	true	pytorch
https://paperswithcode.com/paper/deep-inside-convolutional-networks	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	1312.6034	http://arxiv.org/abs/1312.6034v2	http://arxiv.org/pdf/1312.6034v2.pdf	https://github.com/RuoyuGuo/Visualising-Image-Classification-Models-and-Saliency-Maps	false	false	true	tf

Subsets and Splits

Framework Repo Connectivity Analysis

Reveals the number of official and unofficial repositories and papers associated with different frameworks, highlighting the most connected ones.

Deduplicated Paper-Code Links

This query provides a detailed and organized list of repositories linked to single papers, highlighting official status and mention sources, which is useful for understanding the relationship between papers and their corresponding repositories.

Paper Repo Counts & Distribution

Provides detailed statistics on the distribution of papers across different numbers of repositories, highlighting the percentage of papers with multiple repositories.

Quantum Papers with Code Links

Lists quantum-related papers with their titles, arXiv IDs, frameworks, and code repository links, providing a valuable resource for researchers interested in quantum computing.

Financial Stock Price Prediction

Finds papers related to stock prices, financial markets, and predictions, providing a focused subset for further analysis.

SQL Console for pwc-archive/links-between-paper-and-code

Retrieves specific details about a single paper by its arXiv ID, providing limited insight into the dataset.

Search for YOLO Links

Retrieves a limited set of records related to YOLO, providing basic information about papers and repositories but without deeper analysis.

Prompt Optimization and Personalization

Retrieves a limited set of papers with titles containing specific keywords related to prompt optimization and personalization, providing basic filtering of the dataset.