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/x-modaler-a-versatile-and-high-performance	X-modaler: A Versatile and High-performance Codebase for Cross-modal Analytics	2108.08217	https://arxiv.org/abs/2108.08217v1	https://arxiv.org/pdf/2108.08217v1.pdf	https://github.com/yehli/xmodaler	true	true	true	pytorch
https://paperswithcode.com/paper/enhancing-cryptoguards-deployability-for	Enhancing CryptoGuards Deployability for Continuous Software Security Scanning	2201.07651	https://arxiv.org/abs/2201.07651v1	https://arxiv.org/pdf/2201.07651v1.pdf	https://github.com/CryptoGuardOSS/cryptoguard	true	true	false	none
https://paperswithcode.com/paper/pixelsnail-an-improved-autoregressive	PixelSNAIL: An Improved Autoregressive Generative Model	1712.09763	http://arxiv.org/abs/1712.09763v1	http://arxiv.org/pdf/1712.09763v1.pdf	https://github.com/neocxi/pixelsnail-public	true	true	false	tf
https://paperswithcode.com/paper/weakly-supervised-fingerspelling-recognition	Weakly-supervised Fingerspelling Recognition in British Sign Language Videos	2211.08954	https://arxiv.org/abs/2211.08954v1	https://arxiv.org/pdf/2211.08954v1.pdf	https://github.com/prajwalkr/transpeller	true	false	false	pytorch
https://paperswithcode.com/paper/a-neural-conversation-generation-model-via	A Neural Conversation Generation Model via Equivalent Shared Memory Investigation	2108.09164	https://arxiv.org/abs/2108.09164v1	https://arxiv.org/pdf/2108.09164v1.pdf	https://github.com/jichangzhen/drmn	true	true	false	tf
https://paperswithcode.com/paper/machine-learning-based-multiscale	Machine learning-based multiscale constitutive modelling: Development and application to dual-porosity mass transfer	2108.08847	https://arxiv.org/abs/2108.08847v1	https://arxiv.org/pdf/2108.08847v1.pdf	https://github.com/mashworth11/ml-mm	true	true	false	none
https://paperswithcode.com/paper/rethinking-coarse-to-fine-approach-in-single	Rethinking Coarse-to-Fine Approach in Single Image Deblurring	2108.05054	https://arxiv.org/abs/2108.05054v2	https://arxiv.org/pdf/2108.05054v2.pdf	https://github.com/chosj95/mimo-unet	true	true	true	pytorch
https://paperswithcode.com/paper/robust-scene-text-recognition-with-automatic	Robust Scene Text Recognition with Automatic Rectification	1603.03915	http://arxiv.org/abs/1603.03915v2	http://arxiv.org/pdf/1603.03915v2.pdf	https://github.com/Media-Smart/vedastr	false	false	true	pytorch
https://paperswithcode.com/paper/an-efficient-2d-method-for-training-super	An Efficient 2D Method for Training Super-Large Deep Learning Models	2104.05343	https://arxiv.org/abs/2104.05343v1	https://arxiv.org/pdf/2104.05343v1.pdf	https://github.com/xuqifan897/Optimus	true	true	true	pytorch
https://paperswithcode.com/paper/a-remote-sensing-image-dataset-for-cloud	A Remote Sensing Image Dataset for Cloud Removal	1901.00600	http://arxiv.org/abs/1901.00600v1	http://arxiv.org/pdf/1901.00600v1.pdf	https://github.com/BUPTLdy/RICE_DATASET	true	true	false	none
https://paperswithcode.com/paper/fitsmap-a-simple-lightweight-tool-for	FitsMap: A Simple, Lightweight Tool For Displaying Interactive Astronomical Image and Catalog Data	2201.12308	https://arxiv.org/abs/2201.12308v1	https://arxiv.org/pdf/2201.12308v1.pdf	https://github.com/ryanhausen/fitsmap	true	true	false	none
https://paperswithcode.com/paper/dynamic-slate-recommendation-with-gated	Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling	2104.15046	https://arxiv.org/abs/2104.15046v1	https://arxiv.org/pdf/2104.15046v1.pdf	https://github.com/finn-no/recsys_slates_dataset	false	false	true	pytorch
https://paperswithcode.com/paper/models-of-rotating-coronae	Models of rotating coronae	1809.03437	http://arxiv.org/abs/1809.03437v1	http://arxiv.org/pdf/1809.03437v1.pdf	https://github.com/sormani/coropy	true	true	true	none
https://paperswithcode.com/paper/an-artificial-immune-system-for-adaptive-test	An Artificial Immune System for Adaptive Test Selection	null	https://ieeexplore.ieee.org/document/9308528	https://ieeexplore.ieee.org/document/9308528	https://github.com/LagLukas/adaptiveTestSelection	false	false	false	none
https://paperswithcode.com/paper/ensemble-of-heterogeneous-flexible-neural	Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming	1705.05592	http://arxiv.org/abs/1705.05592v1	http://arxiv.org/pdf/1705.05592v1.pdf	https://github.com/vojha-code/Neural-Tree-Software	true	false	false	none
https://paperswithcode.com/paper/deep-anomaly-detection-on-attributed-networks	Deep Anomaly Detection on Attributed Networks	null	https://epubs.siam.org/doi/abs/10.1137/1.9781611975673.67	https://www.public.asu.edu/~kding9/pdf/SDM2019_Deep.pdf	https://github.com/pygod-team/pygod	false	false	false	pytorch
https://paperswithcode.com/paper/anomalydae-dual-autoencoder-for-anomaly	AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks	2002.03665	https://arxiv.org/abs/2002.03665v2	https://arxiv.org/pdf/2002.03665v2.pdf	https://github.com/pygod-team/pygod	false	false	false	pytorch
https://paperswithcode.com/paper/on-modality-bias-recognition-and-reduction	On Modality Bias Recognition and Reduction	2202.12690	https://arxiv.org/abs/2202.12690v2	https://arxiv.org/pdf/2202.12690v2.pdf	https://github.com/guoyang9/AdaVQA	true	true	false	pytorch
https://paperswithcode.com/paper/comparing-classes-of-estimators-when-does	Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?	2108.11872	https://arxiv.org/abs/2108.11872v2	https://arxiv.org/pdf/2108.11872v2.pdf	https://github.com/dominicrichards/comparinggradientdescentridge	true	true	false	none
https://paperswithcode.com/paper/interpretable-click-through-rate-prediction	Interpretable Click-Through Rate Prediction through Hierarchical Attention	null	https://dl.acm.org/doi/10.1145/3336191.3371785	https://dl.acm.org/doi/pdf/10.1145/3336191.3371785	https://github.com/zyli93/InterHAt	false	false	false	tf
https://paperswithcode.com/paper/photospheric-prompt-emission-from-long-gamma-1	Photospheric Prompt Emission From Long Gamma Ray Burst Simulations -- II. Spectropolarimetry	2108.11412	https://arxiv.org/abs/2108.11412v2	https://arxiv.org/pdf/2108.11412v2.pdf	https://github.com/lazzati-astro/MCRaT	true	true	false	none
https://paperswithcode.com/paper/photospheric-prompt-emission-from-long-gamma-1	Photospheric Prompt Emission From Long Gamma Ray Burst Simulations -- II. Spectropolarimetry	2108.11412	https://arxiv.org/abs/2108.11412v2	https://arxiv.org/pdf/2108.11412v2.pdf	https://github.com/parsotat/ProcessMCRaT	true	true	false	none
https://paperswithcode.com/paper/electra-pre-training-text-encoders-as-1	ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators	2003.10555	https://arxiv.org/abs/2003.10555v1	https://arxiv.org/pdf/2003.10555v1.pdf	https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/electra	false	false	false	paddle
https://paperswithcode.com/paper/nonlinear-state-space-identification-using	Nonlinear state-space identification using deep encoder networks	2012.07697	https://arxiv.org/abs/2012.07697v2	https://arxiv.org/pdf/2012.07697v2.pdf	https://github.com/GerbenBeintema/SS-encoder-WH-Silver	true	true	true	pytorch
https://paperswithcode.com/paper/hierarchical-inference-with-bayesian-neural	Hierarchical Inference With Bayesian Neural Networks: An Application to Strong Gravitational Lensing	2010.13787	https://arxiv.org/abs/2010.13787v3	https://arxiv.org/pdf/2010.13787v3.pdf	https://github.com/swagnercarena/ovejero	true	true	true	tf
https://paperswithcode.com/paper/180309746	Lenstronomy: multi-purpose gravitational lens modelling software package	1803.09746	http://arxiv.org/abs/1803.09746v2	http://arxiv.org/pdf/1803.09746v2.pdf	https://github.com/swagnercarena/ovejero	false	false	true	tf
https://paperswithcode.com/paper/structure-aware-hierarchical-graph-pooling	Structure-Aware Hierarchical Graph Pooling using Information Bottleneck	2104.13012	https://arxiv.org/abs/2104.13012v1	https://arxiv.org/pdf/2104.13012v1.pdf	https://github.com/forkkr/HIBPool	true	true	true	pytorch
https://paperswithcode.com/paper/a-functional-skeleton-transfer	A functional skeleton transfer	2108.12041	https://arxiv.org/abs/2108.12041v1	https://arxiv.org/pdf/2108.12041v1.pdf	https://github.com/pietromsn/functional-skeleton-transfer	true	true	false	none
https://paperswithcode.com/paper/baryon-acoustic-oscillations-in-thin-redshift	Baryon acoustic oscillations in thin redshift shells from BOSS DR12 and eBOSS DR16 galaxies	2112.10000	https://arxiv.org/abs/2112.10000v2	https://arxiv.org/pdf/2112.10000v2.pdf	https://github.com/ranier137/angularbao	true	true	false	none
https://paperswithcode.com/paper/metadata-shaping-natural-language-annotations	Metadata Shaping: Natural Language Annotations for the Tail	2110.08430	https://arxiv.org/abs/2110.08430v1	https://arxiv.org/pdf/2110.08430v1.pdf	https://github.com/simran-arora/metadatashaping	false	false	true	pytorch
https://paperswithcode.com/paper/self-distilled-self-supervised-representation	Self-Distilled Self-Supervised Representation Learning	2111.12958	https://arxiv.org/abs/2111.12958v3	https://arxiv.org/pdf/2111.12958v3.pdf	https://github.com/hagiss/sdssl	true	true	false	pytorch
https://paperswithcode.com/paper/an-unsupervised-method-for-building-sentence	An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages	2109.00165	https://arxiv.org/abs/2109.00165v1	https://arxiv.org/pdf/2109.00165v1.pdf	https://github.com/luxinyu1/trans-ss	true	true	false	pytorch
https://paperswithcode.com/paper/pits-variational-pitch-inference-without	PITS: Variational Pitch Inference without Fundamental Frequency for End-to-End Pitch-controllable TTS	2302.12391	https://arxiv.org/abs/2302.12391v3	https://arxiv.org/pdf/2302.12391v3.pdf	https://github.com/anonymous-pits/pits	true	true	false	pytorch
https://paperswithcode.com/paper/modeling-state-transition-dynamics-in-brain	Modeling state-transition dynamics in resting-state brain signals by the hidden Markov and Gaussian mixture models	2001.08369	https://arxiv.org/abs/2001.08369v3	https://arxiv.org/pdf/2001.08369v3.pdf	https://github.com/tkEzaki/gmm_hmm_comparison	true	true	false	none
https://paperswithcode.com/paper/simplot-a-python-application-for-representing	SimPlot++: a Python application for representing sequence similarity and detecting recombination	2112.09755	https://arxiv.org/abs/2112.09755v2	https://arxiv.org/pdf/2112.09755v2.pdf	https://github.com/stephane-s/simplot_plusplus	true	true	true	none
https://paperswithcode.com/paper/arpist-provably-accurate-and-stable-numerical	ARPIST: Provably Accurate and Stable Numerical Integration over Spherical Triangles	2201.00261	https://arxiv.org/abs/2201.00261v2	https://arxiv.org/pdf/2201.00261v2.pdf	https://github.com/numgeom/arpist	true	true	false	none
https://paperswithcode.com/paper/modality-aware-mutual-learning-for-multi	Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation	2107.09842	https://arxiv.org/abs/2107.09842v1	https://arxiv.org/pdf/2107.09842v1.pdf	https://github.com/YaoZhang93/MAML	true	true	true	pytorch
https://paperswithcode.com/paper/mask-r-cnn	Mask R-CNN	1703.06870	http://arxiv.org/abs/1703.06870v3	http://arxiv.org/pdf/1703.06870v3.pdf	https://github.com/George-Ogden/Mask-RCNN	false	false	true	pytorch
https://paperswithcode.com/paper/symmetrygan-symmetry-discovery-with-deep	SymmetryGAN: Symmetry Discovery with Deep Learning	2112.05722	https://arxiv.org/abs/2112.05722v2	https://arxiv.org/pdf/2112.05722v2.pdf	https://github.com/hep-lbdl/symmetrydiscovery	true	true	false	tf
https://paperswithcode.com/paper/emerging-jets-displaced-into-the-future	Emerging Jets Displaced into the Future	2112.05690	https://arxiv.org/abs/2112.05690v1	https://arxiv.org/pdf/2112.05690v1.pdf	https://github.com/DLinthorne/LLP-Experiments	true	true	false	none
https://paperswithcode.com/paper/multi-objective-loss-balancing-for-physics	Multi-Objective Loss Balancing for Physics-Informed Deep Learning	2110.09813	https://arxiv.org/abs/2110.09813v2	https://arxiv.org/pdf/2110.09813v2.pdf	https://github.com/rbischof/relative_balancing	true	true	false	tf
https://paperswithcode.com/paper/mask-r-cnn	Mask R-CNN	1703.06870	http://arxiv.org/abs/1703.06870v3	http://arxiv.org/pdf/1703.06870v3.pdf	https://github.com/jasjeetIM/Mask-RCNN	false	false	true	none
https://paperswithcode.com/paper/gtg-shapley-efficient-and-accurate	GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning	2109.02053	https://arxiv.org/abs/2109.02053v1	https://arxiv.org/pdf/2109.02053v1.pdf	https://github.com/liuzelei13/gtg-shapley	true	true	false	none
https://paperswithcode.com/paper/improving-joint-learning-of-chest-x-ray-and	Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment	2109.01949	https://arxiv.org/abs/2109.01949v1	https://arxiv.org/pdf/2109.01949v1.pdf	https://github.com/mshaikh2/joimter_mlmi_2021	true	true	false	pytorch
https://paperswithcode.com/paper/pu-flow-a-point-cloud-upsampling-networkwith	PU-Flow: a Point Cloud Upsampling Network with Normalizing Flows	2107.05893	https://arxiv.org/abs/2107.05893v4	https://arxiv.org/pdf/2107.05893v4.pdf	https://github.com/unknownue/pu-flow	true	true	true	pytorch
https://paperswithcode.com/paper/data-augmentation-for-cross-domain-named	Data Augmentation for Cross-Domain Named Entity Recognition	2109.01758	https://arxiv.org/abs/2109.01758v1	https://arxiv.org/pdf/2109.01758v1.pdf	https://github.com/ritual-uh/style_ner	true	true	false	pytorch
https://paperswithcode.com/paper/recurrent-back-projection-network-for-video	Recurrent Back-Projection Network for Video Super-Resolution	1903.10128	http://arxiv.org/abs/1903.10128v1	http://arxiv.org/pdf/1903.10128v1.pdf	https://github.com/xiuyu0000/new_papers_codes/tree/main/rbpn	false	false	false	mindspore
https://paperswithcode.com/paper/learning-from-the-memory-of-atari-2600	Learning from the memory of Atari 2600	1605.01335	http://arxiv.org/abs/1605.01335v1	http://arxiv.org/pdf/1605.01335v1.pdf	https://github.com/ulstu/ml	false	false	true	none
https://paperswithcode.com/paper/deepdiva-a-highly-functional-python-framework	DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments	1805.00329	http://arxiv.org/abs/1805.00329v1	http://arxiv.org/pdf/1805.00329v1.pdf	https://github.com/ajoino/ADL-Jacob-Pedro-Tosin	false	false	true	pytorch
https://paperswithcode.com/paper/federated-learning-with-randomized-douglas	FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization	2103.03452	https://arxiv.org/abs/2103.03452v3	https://arxiv.org/pdf/2103.03452v3.pdf	https://github.com/unc-optimization/FedDR	true	false	true	pytorch
https://paperswithcode.com/paper/analysis-of-language-change-in-collaborative	Analysis of Language Change in Collaborative Instruction Following	2109.04452	https://arxiv.org/abs/2109.04452v1	https://arxiv.org/pdf/2109.04452v1.pdf	https://github.com/lil-lab/cb-analysis	true	true	false	none
https://paperswithcode.com/paper/preservational-learning-improves-self	Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contexts	2109.04379	https://arxiv.org/abs/2109.04379v2	https://arxiv.org/pdf/2109.04379v2.pdf	https://github.com/luchixiang/pcrl	true	true	false	pytorch
https://paperswithcode.com/paper/translating-visual-art-into-music	Translating Visual Art into Music	1909.01218	https://arxiv.org/abs/1909.01218v1	https://arxiv.org/pdf/1909.01218v1.pdf	https://github.com/personads/synvae	true	false	false	tf
https://paperswithcode.com/paper/mine-mutual-information-neural-estimation	MINE: Mutual Information Neural Estimation	1801.04062	https://arxiv.org/abs/1801.04062v5	https://arxiv.org/pdf/1801.04062v5.pdf	https://github.com/personads/synvae	false	false	true	tf
https://paperswithcode.com/paper/distributional-reinforcement-learning-with-1	Distributional Reinforcement Learning with Quantile Regression	1710.10044	http://arxiv.org/abs/1710.10044v1	http://arxiv.org/pdf/1710.10044v1.pdf	https://github.com/DLR-RM/stable-baselines3	false	false	false	pytorch
https://paperswithcode.com/paper/how-powerful-are-graph-neural-networks	How Powerful are Graph Neural Networks?	1810.00826	http://arxiv.org/abs/1810.00826v3	http://arxiv.org/pdf/1810.00826v3.pdf	https://github.com/karolismart/dropgnn	false	false	true	pytorch
https://paperswithcode.com/paper/simple-random-search-provides-a-competitive	Simple random search provides a competitive approach to reinforcement learning	1803.07055	http://arxiv.org/abs/1803.07055v1	http://arxiv.org/pdf/1803.07055v1.pdf	https://github.com/DLR-RM/stable-baselines3	false	false	false	pytorch
https://paperswithcode.com/paper/labeling-free-comparison-testing-of-deep	LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing	2204.03994	https://arxiv.org/abs/2204.03994v2	https://arxiv.org/pdf/2204.03994v2.pdf	https://github.com/testing-cs/laf-model-selection	true	true	true	tf
https://paperswithcode.com/paper/personalisation-in-cyber-physical-social	Personalisation in Cyber-Physical-Social Systems: A Multi-stakeholder aware Recommendation and Guidance	null	https://dl.acm.org/doi/abs/10.1145/3450613.3456847	https://dl.acm.org/doi/pdf/10.1145/3450613.3456847	https://github.com/Bekyilma/Multi-Stakeholder_Recommendation	true	false	false	none
https://paperswithcode.com/paper/conditional-deformable-image-registration	Conditional Deformable Image Registration with Convolutional Neural Network	2106.12673	https://arxiv.org/abs/2106.12673v2	https://arxiv.org/pdf/2106.12673v2.pdf	https://github.com/cwmok/LapIRN	true	true	true	pytorch
https://paperswithcode.com/paper/predictable-universally-unique-identification	Predictable universally unique identification of sequential events on complex objects	2109.06028	https://arxiv.org/abs/2109.06028v1	https://arxiv.org/pdf/2109.06028v1.pdf	https://github.com/davips/garoupa	true	true	true	none
https://paperswithcode.com/paper/latent-hatred-a-benchmark-for-understanding	Latent Hatred: A Benchmark for Understanding Implicit Hate Speech	2109.05322	https://arxiv.org/abs/2109.05322v1	https://arxiv.org/pdf/2109.05322v1.pdf	https://github.com/gt-salt/implicit-hate	true	true	false	none
https://paperswithcode.com/paper/automatic-instrument-recognition-in	Automatic Instrument Recognition in Polyphonic Music Using Convolutional Neural Networks	1511.05520	http://arxiv.org/abs/1511.05520v1	http://arxiv.org/pdf/1511.05520v1.pdf	https://github.com/glennq/instrument-recognition	true	true	false	none
https://paperswithcode.com/paper/generative-adversarial-nets-for-multiple-text	Generative Adversarial Nets for Multiple Text Corpora	1712.09127	http://arxiv.org/abs/1712.09127v1	http://arxiv.org/pdf/1712.09127v1.pdf	https://github.com/baiyangwang/emgan	true	true	false	none
https://paperswithcode.com/paper/learning-to-play-othello-with-deep-neural	Learning to Play Othello with Deep Neural Networks	1711.06583	http://arxiv.org/abs/1711.06583v1	http://arxiv.org/pdf/1711.06583v1.pdf	https://github.com/wjaskowski/dnnothello	true	false	true	none
https://paperswithcode.com/paper/deep-mimo-detection	Deep MIMO Detection	1706.01151	http://arxiv.org/abs/1706.01151v1	http://arxiv.org/pdf/1706.01151v1.pdf	https://github.com/Deeksha96/Deep-MIMO-Detection	false	false	true	tf
https://paperswithcode.com/paper/deep-learning-for-optimal-energy-efficient	A Globally Optimal Energy-Efficient Power Control Framework and its Efficient Implementation in Wireless Interference Networks	1812.06920	https://arxiv.org/abs/1812.06920v2	https://arxiv.org/pdf/1812.06920v2.pdf	https://github.com/bmatthiesen/deep-EE-opt	true	true	true	tf
https://paperswithcode.com/paper/the-case-for-learned-index-structures	The Case for Learned Index Structures	1712.01208	http://arxiv.org/abs/1712.01208v3	http://arxiv.org/pdf/1712.01208v3.pdf	https://github.com/ArnabRaxit/learned_indexes	false	false	true	pytorch
https://paperswithcode.com/paper/spanning-tree-auxiliary-graphs	Spanning Tree Auxiliary Graphs	1705.00119	http://arxiv.org/abs/1705.00119v1	http://arxiv.org/pdf/1705.00119v1.pdf	https://github.com/abhishekgarg2009/Spanning-Tree-Auxiliary-Graphs	false	false	true	none
https://paperswithcode.com/paper/infinite-size-density-matrix-renormalization	Infinite size density matrix renormalization group, revisited	0804.2509	http://arxiv.org/abs/0804.2509v1	http://arxiv.org/pdf/0804.2509v1.pdf	https://github.com/empter/DMRGwithMPSandMPO	false	false	true	none
https://paperswithcode.com/paper/multi-modal-factorized-bilinear-pooling-with	Multi-modal Factorized Bilinear Pooling with Co-Attention Learning for Visual Question Answering	1708.01471	http://arxiv.org/abs/1708.01471v1	http://arxiv.org/pdf/1708.01471v1.pdf	https://github.com/yuzcccc/mfb	true	true	true	caffe2
https://paperswithcode.com/paper/beyond-bilinear-generalized-multi-modal	Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question Answering	1708.03619	https://arxiv.org/abs/1708.03619v2	https://arxiv.org/pdf/1708.03619v2.pdf	https://github.com/yuzcccc/mfb	true	true	true	caffe2
https://paperswithcode.com/paper/self-diagnosing-gan-diagnosing	Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks	2102.12033	https://arxiv.org/abs/2102.12033v3	https://arxiv.org/pdf/2102.12033v3.pdf	https://github.com/grayhong/self-diagnosing-gan	true	true	true	pytorch
https://paperswithcode.com/paper/explaining-and-harnessing-adversarial	Explaining and Harnessing Adversarial Examples	1412.6572	http://arxiv.org/abs/1412.6572v3	http://arxiv.org/pdf/1412.6572v3.pdf	https://github.com/henry8527/GCE	false	false	true	pytorch
https://paperswithcode.com/paper/provable-defenses-against-adversarial	Provable defenses against adversarial examples via the convex outer adversarial polytope	1711.00851	http://arxiv.org/abs/1711.00851v3	http://arxiv.org/pdf/1711.00851v3.pdf	https://github.com/huanzhang12/CROWN-Robustness-Certification	false	false	true	tf
https://paperswithcode.com/paper/post-data-augmentation-to-improve-deep-pose	Post-Data Augmentation to Improve Deep Pose Estimation of Extreme and Wild Motions	1902.04250	http://arxiv.org/abs/1902.04250v1	http://arxiv.org/pdf/1902.04250v1.pdf	https://github.com/ktoyod/rotatedpose	false	false	true	none
https://paperswithcode.com/paper/a-survey-of-motion-planning-and-control	A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles	1604.07446	http://arxiv.org/abs/1604.07446v1	http://arxiv.org/pdf/1604.07446v1.pdf	https://github.com/gtg162y/Resources	false	false	true	none
https://paperswithcode.com/paper/deepwarp-dnn-based-nonlinear-deformation	DeepWarp: DNN-based Nonlinear Deformation	1803.09109	http://arxiv.org/abs/1803.09109v1	http://arxiv.org/pdf/1803.09109v1.pdf	https://github.com/kidyan0000/cloth_simulation	false	false	true	none
https://paperswithcode.com/paper/estimating-sample-specific-regulatory	Estimating sample-specific regulatory networks	1505.06440	http://arxiv.org/abs/1505.06440v2	http://arxiv.org/pdf/1505.06440v2.pdf	https://github.com/twangxxx/netZooR	false	false	true	none
https://paperswithcode.com/paper/propagate-selector-detecting-supporting	Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks	1908.09137	https://arxiv.org/abs/1908.09137v2	https://arxiv.org/pdf/1908.09137v2.pdf	https://github.com/david-yoon/propagate-selector	true	true	true	tf
https://paperswithcode.com/paper/oifits-2-the-2nd-version-of-the-data-exchange	OIFITS 2: the 2nd version of the Data Exchange Standard for Optical (Visible/IR) Interferometry	1510.04556	http://arxiv.org/abs/1510.04556v4	http://arxiv.org/pdf/1510.04556v4.pdf	https://github.com/UnofficialJuliaMirrorSnapshots/OIFITS.jl-53eb397e-dec1-5dcf-8dc9-2db916067267	false	false	true	none
https://paperswithcode.com/paper/enhancing-the-lexvec-distributed-word	Enhancing the LexVec Distributed Word Representation Model Using Positional Contexts and External Memory	1606.01283	http://arxiv.org/abs/1606.01283v1	http://arxiv.org/pdf/1606.01283v1.pdf	https://github.com/alexandres/lexvec	true	false	true	none
https://paperswithcode.com/paper/cost-effective-on-device-continual-learning	Cost-effective On-device Continual Learning over Memory Hierarchy with Miro	2308.06053	https://arxiv.org/abs/2308.06053v4	https://arxiv.org/pdf/2308.06053v4.pdf	https://github.com/omnia-unist/Miro	true	true	false	pytorch
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/nicholasbao/nlp_job	false	false	true	tf
https://paperswithcode.com/paper/product-based-neural-networks-for-user-1	Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data	1807.00311	http://arxiv.org/abs/1807.00311v1	http://arxiv.org/pdf/1807.00311v1.pdf	https://github.com/Atomu2014/product-nets-distributed	true	true	true	tf
https://paperswithcode.com/paper/unpaired-image-to-image-translation-using	Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks	1703.10593	https://arxiv.org/abs/1703.10593v7	https://arxiv.org/pdf/1703.10593v7.pdf	https://github.com/ZC119/Handwritten-CycleGAN	false	false	true	pytorch
https://paperswithcode.com/paper/testing-the-number-of-components-in-finite	Testing the Number of Components in Finite Mixture Normal Regression Model with Panel Data	2210.02824	https://arxiv.org/abs/2210.02824v2	https://arxiv.org/pdf/2210.02824v2.pdf	https://github.com/JasmineHao/NormalRegPanelMixture	true	false	false	none
https://paperswithcode.com/paper/bottom-up-and-top-down-attention-for-image	Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering	1707.07998	http://arxiv.org/abs/1707.07998v3	http://arxiv.org/pdf/1707.07998v3.pdf	https://github.com/Wentong-DST/up-down-captioner	false	false	true	caffe2
https://paperswithcode.com/paper/actor-critic-versus-direct-policy-search-a	Actor-critic versus direct policy search: a comparison based on sample complexity	1606.09152	http://arxiv.org/abs/1606.09152v2	http://arxiv.org/pdf/1606.09152v2.pdf	https://github.com/MOCR/DDPG	true	true	true	tf
https://paperswithcode.com/paper/generating-focussed-molecule-libraries-for	Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks	1701.01329	http://arxiv.org/abs/1701.01329v1	http://arxiv.org/pdf/1701.01329v1.pdf	https://github.com/jaechanglim/molecule-generator	false	false	true	tf
https://paperswithcode.com/paper/deterministic-memory-abstraction-and	Deterministic Memory Abstraction and Supporting Multicore System Architecture	1707.05260	https://arxiv.org/abs/1707.05260v4	https://arxiv.org/pdf/1707.05260v4.pdf	https://github.com/farzadfch/gem5-cache-partitioning	true	true	true	none
https://paperswithcode.com/paper/dynamic-coattention-networks-for-question	Dynamic Coattention Networks For Question Answering	1611.01604	http://arxiv.org/abs/1611.01604v4	http://arxiv.org/pdf/1611.01604v4.pdf	https://github.com/Lou1sM/AML-Project	false	false	true	tf
https://paperswithcode.com/paper/mask-r-cnn	Mask R-CNN	1703.06870	http://arxiv.org/abs/1703.06870v3	http://arxiv.org/pdf/1703.06870v3.pdf	https://github.com/sbetageri/MaskRCNN	false	false	true	pytorch
https://paperswithcode.com/paper/introducing-astrocytes-on-a-neuromorphic	Introducing Astrocytes on a Neuromorphic Processor: Synchronization, Local Plasticity and Edge of Chaos	1907.01620	https://arxiv.org/abs/1907.01620v2	https://arxiv.org/pdf/1907.01620v2.pdf	https://github.com/combra-lab/combra_loihi	true	true	true	none
https://paperswithcode.com/paper/unsupervised-representation-learning-with-1	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	1511.06434	http://arxiv.org/abs/1511.06434v2	http://arxiv.org/pdf/1511.06434v2.pdf	https://github.com/Ksuryateja/DCGAN-CIFAR10-pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/towards-sparse-hierarchical-graph-classifiers	Towards Sparse Hierarchical Graph Classifiers	1811.01287	http://arxiv.org/abs/1811.01287v1	http://arxiv.org/pdf/1811.01287v1.pdf	https://github.com/HeapHop30/hierarchical-pooling	false	false	true	tf
https://paperswithcode.com/paper/a-quantum-approximate-optimization-algorithm-1	A Quantum Approximate Optimization Algorithm	1411.4028	http://arxiv.org/abs/1411.4028v1	http://arxiv.org/pdf/1411.4028v1.pdf	https://github.com/kdalkafoukis/quantum_computing	false	false	true	none
https://paperswithcode.com/paper/swin-transformer-hierarchical-vision	Swin Transformer: Hierarchical Vision Transformer using Shifted Windows	2103.14030	https://arxiv.org/abs/2103.14030v2	https://arxiv.org/pdf/2103.14030v2.pdf	https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/backbone/swin_transformer.py	false	false	false	mindspore
https://paperswithcode.com/paper/scalable-string-reconciliation-by-recursive	Scalable String Reconciliation by Recursive Content-Dependent Shingling	1910.00536	https://arxiv.org/abs/1910.00536v1	https://arxiv.org/pdf/1910.00536v1.pdf	https://github.com/String-Reconciliation-Ditributed-System/RCDS_GO	false	false	true	none
https://paperswithcode.com/paper/forward-modeling-of-large-scale-structure-an	Forward Modeling of Large-Scale Structure: An open-source approach with Halotools	1606.04106	http://arxiv.org/abs/1606.04106v2	http://arxiv.org/pdf/1606.04106v2.pdf	https://github.com/mclaughlin6464/halotools_old	false	false	true	none

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.