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/efficient-learning-of-generative-models-via	Efficient Learning of Generative Models via Finite-Difference Score Matching	2007.03317	https://arxiv.org/abs/2007.03317v2	https://arxiv.org/pdf/2007.03317v2.pdf	https://github.com/taufikxu/FD-ScoreMatching	true	true	false	pytorch
https://paperswithcode.com/paper/learning-individualized-treatment-rules-with	Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score	2007.01083	https://arxiv.org/abs/2007.01083v1	https://arxiv.org/pdf/2007.01083v1.pdf	https://github.com/ZhiliangWu/etips	true	true	true	tf
https://paperswithcode.com/paper/gradient-temporal-difference-learning-with	Gradient Temporal-Difference Learning with Regularized Corrections	2007.00611	https://arxiv.org/abs/2007.00611v4	https://arxiv.org/pdf/2007.00611v4.pdf	https://github.com/rlai-lab/Regularized-GradientTD	true	true	true	pytorch
https://paperswithcode.com/paper/deep-bayesian-quadrature-policy-optimization	Deep Bayesian Quadrature Policy Optimization	2006.15637	https://arxiv.org/abs/2006.15637v3	https://arxiv.org/pdf/2006.15637v3.pdf	https://github.com/Akella17/Deep-Bayesian-Quadrature-Policy-Optimization	true	true	true	pytorch
https://paperswithcode.com/paper/gnn3dmot-graph-neural-network-for-3d-multi-1	GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning	2006.07327	https://arxiv.org/abs/2006.07327v1	https://arxiv.org/pdf/2006.07327v1.pdf	https://github.com/xinshuoweng/GNN3DMOT	true	true	false	pytorch
https://paperswithcode.com/paper/rethinking-the-truly-unsupervised-image-to	Rethinking the Truly Unsupervised Image-to-Image Translation	2006.06500	https://arxiv.org/abs/2006.06500v2	https://arxiv.org/pdf/2006.06500v2.pdf	https://github.com/clovaai/tunit	true	true	true	pytorch
https://paperswithcode.com/paper/compositional-convolutional-neural-networks-a	Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion	2003.04490	https://arxiv.org/abs/2003.04490v3	https://arxiv.org/pdf/2003.04490v3.pdf	https://github.com/AdamKortylewski/CompositionalNets	true	true	false	pytorch
https://paperswithcode.com/paper/intra-3d-intracranial-aneurysm-dataset-for	IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning	2003.02920	https://arxiv.org/abs/2003.02920v2	https://arxiv.org/pdf/2003.02920v2.pdf	https://github.com/intra3d2019/IntrA	true	true	true	none
https://paperswithcode.com/paper/few-shot-learning-on-graphs-via-super-classes-1	Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures	2002.12815	https://arxiv.org/abs/2002.12815v1	https://arxiv.org/pdf/2002.12815v1.pdf	https://github.com/chauhanjatin10/GraphsFewShot	true	true	false	pytorch
https://paperswithcode.com/paper/roto-translation-equivariant-convolutional	Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis	2002.08725	https://arxiv.org/abs/2002.08725v1	https://arxiv.org/pdf/2002.08725v1.pdf	https://github.com/tueimage/se2cnn	true	true	false	tf
https://paperswithcode.com/paper/efficient-policy-learning-from-surrogate-loss	Efficient Policy Learning from Surrogate-Loss Classification Reductions	2002.05153	https://arxiv.org/abs/2002.05153v1	https://arxiv.org/pdf/2002.05153v1.pdf	https://github.com/CausalML/ESPRM	true	true	true	pytorch
https://paperswithcode.com/paper/detecting-stable-communities-in-link-streams	Detecting Stable Communities in Link Streams at Multiple Temporal Scales	1907.10453	https://arxiv.org/abs/1907.10453v1	https://arxiv.org/pdf/1907.10453v1.pdf	https://github.com/Yquetzal/ECML_PKDD_2019	true	true	false	none
https://paperswithcode.com/paper/reinforcement-learning-enhanced-quantum	Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial Optimization	2002.04676	https://arxiv.org/abs/2002.04676v2	https://arxiv.org/pdf/2002.04676v2.pdf	https://github.com/BeloborodovDS/SIMCIM-RL	true	true	true	pytorch
https://paperswithcode.com/paper/a-probabilistic-formulation-of-unsupervised-1	A Probabilistic Formulation of Unsupervised Text Style Transfer	2002.03912	https://arxiv.org/abs/2002.03912v3	https://arxiv.org/pdf/2002.03912v3.pdf	https://github.com/cindyxinyiwang/deep-latent-sequence-model	true	true	true	pytorch
https://paperswithcode.com/paper/correcting-knowledge-base-assertions	Correcting Knowledge Base Assertions	2001.06917	https://arxiv.org/abs/2001.06917v1	https://arxiv.org/pdf/2001.06917v1.pdf	https://github.com/ChenJiaoyan/KG_Curation	true	true	false	tf
https://paperswithcode.com/paper/nonparametric-estimation-of-population	Nonparametric Estimation of Population Average Dose-Response Curves using Entropy Balancing Weights for Continuous Exposures	2003.02938	https://arxiv.org/abs/2003.02938v1	https://arxiv.org/pdf/2003.02938v1.pdf	https://github.com/EddieYang211/ebal-python	false	false	true	none
https://paperswithcode.com/paper/learning-fairness-in-multi-agent-systems	Learning Fairness in Multi-Agent Systems	1910.14472	https://arxiv.org/abs/1910.14472v1	https://arxiv.org/pdf/1910.14472v1.pdf	https://github.com/PKU-AI-Edge/FEN	true	true	false	tf
https://paperswithcode.com/paper/a-holistic-approach-to-polyphonic-music	A holistic approach to polyphonic music transcription with neural networks	1910.12086	https://arxiv.org/abs/1910.12086v1	https://arxiv.org/pdf/1910.12086v1.pdf	https://github.com/mangelroman/audio2score	true	true	false	pytorch
https://paperswithcode.com/paper/inherent-weight-normalization-in-stochastic	Inherent Weight Normalization in Stochastic Neural Networks	1910.12316	https://arxiv.org/abs/1910.12316v1	https://arxiv.org/pdf/1910.12316v1.pdf	https://github.com/nmi-lab/neural_sampling_machines	true	true	false	pytorch
https://paperswithcode.com/paper/bottom-up-meta-policy-search	Bottom-Up Meta-Policy Search	1910.10232	https://arxiv.org/abs/1910.10232v2	https://arxiv.org/pdf/1910.10232v2.pdf	https://github.com/luckeciano/bumps	true	true	false	tf
https://paperswithcode.com/paper/meme-generating-rnn-model-explanations-via-1	MEME: Generating RNN Model Explanations via Model Extraction	null	https://openreview.net/forum?id=0beaSUVK_n4	https://openreview.net/pdf?id=0beaSUVK_n4	https://github.com/dmitrykazhdan/MEME-RNN-XAI	true	true	false	tf
https://paperswithcode.com/paper/compacting-picking-and-growing-for	Compacting, Picking and Growing for Unforgetting Continual Learning	1910.06562	https://arxiv.org/abs/1910.06562v3	https://arxiv.org/pdf/1910.06562v3.pdf	https://github.com/ivclab/CPG	true	true	false	pytorch
https://paperswithcode.com/paper/how-does-language-influence-documentation	How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages	1910.05154	https://arxiv.org/abs/1910.05154v1	https://arxiv.org/pdf/1910.05154v1.pdf	https://github.com/mzboito/mmboshi	true	true	true	none
https://paperswithcode.com/paper/smoothfool-an-efficient-framework-for	SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations	1910.03624	https://arxiv.org/abs/1910.03624v1	https://arxiv.org/pdf/1910.03624v1.pdf	https://github.com/alldbi/SmoothFool	true	true	true	pytorch
https://paperswithcode.com/paper/epca-high-dimensional-exponential-family-pca	$e$PCA: High Dimensional Exponential Family PCA	1611.05550	https://arxiv.org/abs/1611.05550v2	https://arxiv.org/pdf/1611.05550v2.pdf	https://github.com/lydiatliu/epca	true	true	true	none
https://paperswithcode.com/paper/biobert-a-pre-trained-biomedical-language	BioBERT: a pre-trained biomedical language representation model for biomedical text mining	1901.08746	https://arxiv.org/abs/1901.08746v4	https://arxiv.org/pdf/1901.08746v4.pdf	https://github.com/jpablou/Matching-The-Blanks-Ths	false	false	true	pytorch
https://paperswithcode.com/paper/generalized-inner-loop-meta-learning	Generalized Inner Loop Meta-Learning	1910.01727	https://arxiv.org/abs/1910.01727v2	https://arxiv.org/pdf/1910.01727v2.pdf	https://github.com/facebookresearch/higher	true	true	false	pytorch
https://paperswithcode.com/paper/albert-a-lite-bert-for-self-supervised	ALBERT: A Lite BERT for Self-supervised Learning of Language Representations	1909.11942	https://arxiv.org/abs/1909.11942v6	https://arxiv.org/pdf/1909.11942v6.pdf	https://github.com/jpablou/Matching-The-Blanks-Ths	false	false	true	pytorch
https://paperswithcode.com/paper/mtab-matching-tabular-data-to-knowledge-graph	MTab: Matching Tabular Data to Knowledge Graph using Probability Models	1910.00246	https://arxiv.org/abs/1910.00246v2	https://arxiv.org/pdf/1910.00246v2.pdf	https://github.com/phucty/MTab	true	true	true	none
https://paperswithcode.com/paper/matching-the-blanks-distributional-similarity	Matching the Blanks: Distributional Similarity for Relation Learning	1906.03158	https://arxiv.org/abs/1906.03158v1	https://arxiv.org/pdf/1906.03158v1.pdf	https://github.com/jpablou/Matching-The-Blanks-Ths	false	false	true	pytorch
https://paperswithcode.com/paper/well-calibrated-model-uncertainty-with	Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference	1909.13550	https://arxiv.org/abs/1909.13550v3	https://arxiv.org/pdf/1909.13550v3.pdf	https://github.com/mlaves/bayesian-temperature-scaling	true	true	true	pytorch
https://paperswithcode.com/paper/social-and-scene-aware-trajectory-prediction	Social and Scene-Aware Trajectory Prediction in Crowded Spaces	1909.08840	https://arxiv.org/abs/1909.08840v1	https://arxiv.org/pdf/1909.08840v1.pdf	https://github.com/Oghma/sns-lstm	true	true	false	tf
https://paperswithcode.com/paper/revealing-the-importance-of-semantic	Revealing the Importance of Semantic Retrieval for Machine Reading at Scale	1909.08041	https://arxiv.org/abs/1909.08041v1	https://arxiv.org/pdf/1909.08041v1.pdf	https://github.com/easonnie/semanticRetrievalMRS	true	true	true	pytorch
https://paperswithcode.com/paper/stacking-models-for-nearly-optimal-link	Stacking Models for Nearly Optimal Link Prediction in Complex Networks	1909.07578	https://arxiv.org/abs/1909.07578v1	https://arxiv.org/pdf/1909.07578v1.pdf	https://github.com/Aghasemian/OptimalLinkPrediction	true	true	true	none
https://paperswithcode.com/paper/say-anything-automatic-semantic-infelicity	Say Anything: Automatic Semantic Infelicity Detection in L2 English Indefinite Pronouns	1909.07928	https://arxiv.org/abs/1909.07928v1	https://arxiv.org/pdf/1909.07928v1.pdf	https://github.com/ellarabi/indefinite-pronouns	true	true	false	none
https://paperswithcode.com/paper/basketballgan-generating-basketball-play	BasketballGAN: Generating Basketball Play Simulation Through Sketching	1909.07088	https://arxiv.org/abs/1909.07088v2	https://arxiv.org/pdf/1909.07088v2.pdf	https://github.com/chychen/BasketballGAN	true	true	true	tf
https://paperswithcode.com/paper/efficient-low-rank-gaussian-variational	Efficient Low Rank Gaussian Variational Inference for Neural Networks	null	http://proceedings.neurips.cc/paper/2020/hash/310cc7ca5a76a446f85c1a0d641ba96d-Abstract.html	http://proceedings.neurips.cc/paper/2020/file/310cc7ca5a76a446f85c1a0d641ba96d-Paper.pdf	https://github.com/marctom/elrgvi	true	true	false	pytorch
https://paperswithcode.com/paper/neural-abstractive-text-summarization-with	Neural Abstractive Text Summarization with Sequence-to-Sequence Models	1812.02303	https://arxiv.org/abs/1812.02303v4	https://arxiv.org/pdf/1812.02303v4.pdf	https://github.com/freeflyxiaoma/pycorrector	false	false	true	tf
https://paperswithcode.com/paper/distributional-policy-optimization-an	Distributional Policy Optimization: An Alternative Approach for Continuous Control	1905.09855	https://arxiv.org/abs/1905.09855v2	https://arxiv.org/pdf/1905.09855v2.pdf	https://github.com/tesslerc/GAC	true	true	true	pytorch
https://paperswithcode.com/paper/neural-language-correction-with-character	Neural Language Correction with Character-Based Attention	1603.09727	http://arxiv.org/abs/1603.09727v1	http://arxiv.org/pdf/1603.09727v1.pdf	https://github.com/freeflyxiaoma/pycorrector	false	false	true	tf
https://paperswithcode.com/paper/a-zeroth-order-block-coordinate-descent	A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization	2102.10707	https://arxiv.org/abs/2102.10707v2	https://arxiv.org/pdf/2102.10707v2.pdf	https://github.com/YuchenLou/ZO-BCD	true	true	false	none
https://paperswithcode.com/paper/when-a-good-translation-is-wrong-in-context	When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion	1905.05979	https://arxiv.org/abs/1905.05979v2	https://arxiv.org/pdf/1905.05979v2.pdf	https://github.com/lena-voita/good-translation-wrong-in-context	true	true	false	tf
https://paperswithcode.com/paper/190503706	Accurate Visual Localization for Automotive Applications	1905.03706	http://arxiv.org/abs/1905.03706v1	http://arxiv.org/pdf/1905.03706v1.pdf	https://github.com/getnexar/Nexar-Visual-Localization	true	true	true	none
https://paperswithcode.com/paper/lifelong-sequential-modeling-with	Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction	1905.00758	https://arxiv.org/abs/1905.00758v2	https://arxiv.org/pdf/1905.00758v2.pdf	https://github.com/alimamarankgroup/HPMN	true	true	true	tf
https://paperswithcode.com/paper/data-hand-fostering-visual-exploration-of	Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction	2101.06283	https://arxiv.org/abs/2101.06283v1	https://arxiv.org/pdf/2101.06283v1.pdf	https://github.com/umdsquare/data-at-hand-mobile	true	false	false	none
https://paperswithcode.com/paper/190411800	Adaptive Matrix Completion for the Users and the Items in Tail	1904.11800	https://arxiv.org/abs/1904.11800v2	https://arxiv.org/pdf/1904.11800v2.pdf	https://github.com/mohit-shrma/matfac	true	true	false	none
https://paperswithcode.com/paper/190409324	Mask-Predict: Parallel Decoding of Conditional Masked Language Models	1904.09324	https://arxiv.org/abs/1904.09324v2	https://arxiv.org/pdf/1904.09324v2.pdf	https://github.com/facebookresearch/Mask-Predict	true	true	false	pytorch
https://paperswithcode.com/paper/neural-message-passing-for-multi-label-1	Neural Message Passing for Multi-Label Classification	1904.08049	http://arxiv.org/abs/1904.08049v1	http://arxiv.org/pdf/1904.08049v1.pdf	https://github.com/QData/LaMP	true	true	true	pytorch
https://paperswithcode.com/paper/difficulty-aware-image-super-resolution-via	Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network	1904.05802	http://arxiv.org/abs/1904.05802v2	http://arxiv.org/pdf/1904.05802v2.pdf	https://github.com/xzwlx/Difficulty-SR	true	true	false	pytorch
https://paperswithcode.com/paper/remasc-realistic-replay-attack-corpus-for	ReMASC: Realistic Replay Attack Corpus for Voice Controlled Systems	1904.03365	https://arxiv.org/abs/1904.03365v2	https://arxiv.org/pdf/1904.03365v2.pdf	https://github.com/YuanGongND/ReMASC	true	true	true	pytorch
https://paperswithcode.com/paper/an-open-source-toolkit-for-the-tracking	An open source toolkit for the tracking, termination and recovery of high altitude balloon flights and payloads	1904.04321	http://arxiv.org/abs/1904.04321v1	http://arxiv.org/pdf/1904.04321v1.pdf	https://github.com/PaulZC/Balloon_Cut-Down_Device	true	true	true	none
https://paperswithcode.com/paper/vest-very-sparse-tucker-factorization-of	VeST: Very Sparse Tucker Factorization of Large-Scale Tensors	1904.02603	http://arxiv.org/abs/1904.02603v1	http://arxiv.org/pdf/1904.02603v1.pdf	https://github.com/leesael/VeST	true	true	true	none
https://paperswithcode.com/paper/et-bert-a-contextualized-datagram	ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification	2202.06335	https://arxiv.org/abs/2202.06335v2	https://arxiv.org/pdf/2202.06335v2.pdf	https://github.com/linwhitehat/et-bert	true	true	true	pytorch
https://paperswithcode.com/paper/robust-graph-learning-from-noisy-data	Robust Graph Learning from Noisy Data	1812.06673	http://arxiv.org/abs/1812.06673v1	http://arxiv.org/pdf/1812.06673v1.pdf	https://github.com/sckangz/RGC	true	true	false	none
https://paperswithcode.com/paper/lsicc-a-large-scale-informal-chinese-corpus	LSICC: A Large Scale Informal Chinese Corpus	1811.10167	http://arxiv.org/abs/1811.10167v1	http://arxiv.org/pdf/1811.10167v1.pdf	https://github.com/JaniceZhao/Chinese-Forum-Corpus	true	true	false	none
https://paperswithcode.com/paper/using-sentiment-induction-to-understand	Using Sentiment Induction to Understand Variation in Gendered Online Communities	1811.07061	http://arxiv.org/abs/1811.07061v1	http://arxiv.org/pdf/1811.07061v1.pdf	https://github.com/lucy3/reddit-sent	true	true	false	none
https://paperswithcode.com/paper/on-pruning-for-score-based-bayesian-network	On Pruning for Score-Based Bayesian Network Structure Learning	1905.09943	https://arxiv.org/abs/1905.09943v2	https://arxiv.org/pdf/1905.09943v2.pdf	https://github.com/AlCorreia/BDeu-Structure-Learning	true	false	false	none
https://paperswithcode.com/paper/derpn-taking-a-further-step-toward-more	DeRPN: Taking a further step toward more general object detection	1811.06700	http://arxiv.org/abs/1811.06700v1	http://arxiv.org/pdf/1811.06700v1.pdf	https://github.com/HCIILAB/DeRPN	true	true	true	none
https://paperswithcode.com/paper/counterfactual-learning-from-human	Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing	1811.12239	http://arxiv.org/abs/1811.12239v1	http://arxiv.org/pdf/1811.12239v1.pdf	https://github.com/carolinlawrence/nematus	true	false	false	none
https://paperswithcode.com/paper/gated-hierarchical-attention-for-image	Gated Hierarchical Attention for Image Captioning	1810.12535	http://arxiv.org/abs/1810.12535v2	http://arxiv.org/pdf/1810.12535v2.pdf	https://github.com/qingzwang/GHA-ImageCaptioning	true	true	true	pytorch
https://paperswithcode.com/paper/global-deep-learning-methods-for	Non-local U-Net for Biomedical Image Segmentation	1812.04103	https://arxiv.org/abs/1812.04103v2	https://arxiv.org/pdf/1812.04103v2.pdf	https://github.com/divelab/Non-local-U-Nets	true	true	false	tf
https://paperswithcode.com/paper/context-dependent-word-representation-for	Context-Dependent Word Representation for Neural Machine Translation	1607.00578	http://arxiv.org/abs/1607.00578v1	http://arxiv.org/pdf/1607.00578v1.pdf	https://github.com/kyunghyuncho/WordVectorManifold	true	true	false	none
https://paperswithcode.com/paper/interactive-language-learning-by-question	Interactive Language Learning by Question Answering	1908.10909	https://arxiv.org/abs/1908.10909v1	https://arxiv.org/pdf/1908.10909v1.pdf	https://github.com/xingdi-eric-yuan/qait_public	true	true	false	pytorch
https://paperswithcode.com/paper/building-a-hebrew-semantic-role-labeling	Building a Hebrew Semantic Role Labeling Lexical Resource from Parallel Movie Subtitles	2005.08206	https://arxiv.org/abs/2005.08206v1	https://arxiv.org/pdf/2005.08206v1.pdf	https://github.com/bgunlp/hebrew_srl	true	true	false	none
https://paperswithcode.com/paper/data-driven-meta-set-based-fine-grained	Data-driven Meta-set Based Fine-Grained Visual Classification	2008.02438	https://arxiv.org/abs/2008.02438v1	https://arxiv.org/pdf/2008.02438v1.pdf	https://github.com/NUST-Machine-Intelligence-Laboratory/dmbfgvr	true	true	false	pytorch
https://paperswithcode.com/paper/survae-flows-surjections-to-bridge-the-gap	SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows	2007.02731	https://arxiv.org/abs/2007.02731v2	https://arxiv.org/pdf/2007.02731v2.pdf	https://github.com/didriknielsen/survae_flows	true	true	true	pytorch
https://paperswithcode.com/paper/foreground-segmentation-using-a-triplet	Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding	1801.02225	http://arxiv.org/abs/1801.02225v1	http://arxiv.org/pdf/1801.02225v1.pdf	https://github.com/lim-anggun/FgSegNet	true	true	true	tf
https://paperswithcode.com/paper/morphological-analyzer-and-generator-for	Morphological Analyzer and Generator for Russian and Ukrainian Languages	1503.07283	http://arxiv.org/abs/1503.07283v1	http://arxiv.org/pdf/1503.07283v1.pdf	https://github.com/kmike/pymorphy2	true	true	true	none
https://paperswithcode.com/paper/how-to-find-a-unicorn-a-novel-model-free	How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series	2004.11468	https://arxiv.org/abs/2004.11468v3	https://arxiv.org/pdf/2004.11468v3.pdf	https://github.com/phrenico/uniqed	true	true	true	none
https://paperswithcode.com/paper/image-to-image-translation-via-group-wise	Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation	1812.09912	https://arxiv.org/abs/1812.09912v2	https://arxiv.org/pdf/1812.09912v2.pdf	https://github.com/WonwoongCho/GDWCT	true	true	true	pytorch
https://paperswithcode.com/paper/modular-representation-underlies-systematic	Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation	2004.14623	https://arxiv.org/abs/2004.14623v4	https://arxiv.org/pdf/2004.14623v4.pdf	https://github.com/atticusg/MoNLI	true	true	false	none
https://paperswithcode.com/paper/modelicagym-applying-reinforcement-learning	ModelicaGym: Applying Reinforcement Learning to Modelica Models	1909.08604	https://arxiv.org/abs/1909.08604v1	https://arxiv.org/pdf/1909.08604v1.pdf	https://github.com/ucuapps/modelicagym	true	true	true	none
https://paperswithcode.com/paper/finding-temporal-patterns-using-algebraic	Finding path motifs in large temporal graphs using algebraic fingerprints	2001.07158	https://arxiv.org/abs/2001.07158v4	https://arxiv.org/pdf/2001.07158v4.pdf	https://github.com/suhastheju/temporal-patterns-mk2	true	true	false	none
https://paperswithcode.com/paper/towards-precise-completion-of-deformable	Towards Precise Completion of Deformable Shapes	null	https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4619_ECCV_2020_paper.php	https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690358.pdf	https://github.com/OshriHalimi/precise_shape_completion	true	true	false	none
https://paperswithcode.com/paper/towards-compact-single-image-super-resolution	Towards Compact Single Image Super-Resolution via Contrastive Self-distillation	2105.11683	https://arxiv.org/abs/2105.11683v1	https://arxiv.org/pdf/2105.11683v1.pdf	https://github.com/mindspore-ai/contrib/tree/master/papers/CSD	false	false	false	mindspore
https://paperswithcode.com/paper/eigendecompositions-of-transfer-operators-in	Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces	1712.01572	https://arxiv.org/abs/1712.01572v3	https://arxiv.org/pdf/1712.01572v3.pdf	https://github.com/sklus/d3s	true	true	false	none
https://paperswithcode.com/paper/a-genre-aware-attention-model-to-improve-the	A Genre-Aware Attention Model to Improve the Likability Prediction of Books	null	https://aclanthology.org/D18-1375	https://aclanthology.org/D18-1375.pdf	https://github.com/sjmaharjan/genre_aware_attention	true	true	false	none
https://paperswithcode.com/paper/prema-principled-tensor-data-recovery-from	PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views	1910.12001	https://arxiv.org/abs/1910.12001v2	https://arxiv.org/pdf/1910.12001v2.pdf	https://github.com/FaisalAlmutairi/Prema	true	true	true	none
https://paperswithcode.com/paper/learning-to-generate-move-by-move-commentary	Learning to Generate Move-by-Move Commentary for Chess Games from Large-Scale Social Forum Data	null	https://aclanthology.org/P18-1154	https://aclanthology.org/P18-1154.pdf	https://github.com/harsh19/ChessCommentaryGeneration	true	true	false	pytorch
https://paperswithcode.com/paper/interactive-text-ranking-with-bayesian	Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation	1911.10183	https://arxiv.org/abs/1911.10183v3	https://arxiv.org/pdf/1911.10183v3.pdf	https://github.com/UKPLab/tacl2020-interactive-ranking	true	true	false	pytorch
https://paperswithcode.com/paper/wavelet-integrated-cnns-for-noise-robust	Wavelet Integrated CNNs for Noise-Robust Image Classification	2005.03337	https://arxiv.org/abs/2005.03337v2	https://arxiv.org/pdf/2005.03337v2.pdf	https://github.com/LiQiufu/WaveCNet	true	true	false	pytorch
https://paperswithcode.com/paper/generating-market-comments-referring-to	Generating Market Comments Referring to External Resources	null	https://aclanthology.org/W18-6515	https://aclanthology.org/W18-6515.pdf	https://github.com/aistairc/market-reporter	true	true	false	pytorch
https://paperswithcode.com/paper/comment-on-androdet-an-adaptive-android	Comment on "AndrODet: An adaptive Android obfuscation detector"	1910.06192	https://arxiv.org/abs/1910.06192v2	https://arxiv.org/pdf/1910.06192v2.pdf	https://github.com/alirezamohammadinodooshan/androdet-se-eval	true	true	false	none
https://paperswithcode.com/paper/real-world-multiobject-multigrasp-detection	Real-world multiobject, multigrasp detection	null	https://arxiv.org/abs/1802.00520	https://arxiv.org/pdf/1802.00520.pdf	https://github.com/ivalab/grasp_multiObject	true	true	false	none
https://paperswithcode.com/paper/unsupervised-feature-learning-via-non-1	Unsupervised Feature Learning via Non-Parametric Instance Discrimination	null	http://openaccess.thecvf.com/content_cvpr_2018/html/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.html	http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Unsupervised_Feature_Learning_CVPR_2018_paper.pdf	https://github.com/zhirongw/lemniscate.pytorch	true	true	false	pytorch
https://paperswithcode.com/paper/zipper-logic	Zipper logic	1405.6095	https://arxiv.org/abs/1405.6095v1	https://arxiv.org/pdf/1405.6095v1.pdf	https://github.com/mbuliga/zss	false	false	true	none
https://paperswithcode.com/paper/mobilenets-efficient-convolutional-neural	MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications	1704.04861	http://arxiv.org/abs/1704.04861v1	http://arxiv.org/pdf/1704.04861v1.pdf	https://github.com/sivaole/Face_Detection	false	false	true	tf
https://paperswithcode.com/paper/reinforcement-learning-with-prototypical-1	Reinforcement Learning with Prototypical Representations	null	https://openreview.net/forum?id=NVd9b1sFO0R	https://openreview.net/pdf?id=NVd9b1sFO0R	https://github.com/denisyarats/proto	true	true	false	pytorch
https://paperswithcode.com/paper/evaluating-bayesian-deep-learning-methods-for	Evaluating Bayesian Deep Learning Methods for Semantic Segmentation	1811.12709	http://arxiv.org/abs/1811.12709v2	http://arxiv.org/pdf/1811.12709v2.pdf	https://github.com/IntelLabs/AVUC	false	false	true	pytorch
https://paperswithcode.com/paper/your-answer-is-incorrect-would-you-like-to-1	Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset	null	https://aclanthology.org/2022.acl-long.587	https://aclanthology.org/2022.acl-long.587.pdf	https://github.com/sebochs/saf	true	true	false	pytorch
https://paperswithcode.com/paper/online-geolocalized-emotion-across-us-cities	Online geolocalized emotion across US cities during the COVID crisis: Universality, policy response, and connection with local mobility	2009.10461	https://arxiv.org/abs/2009.10461v1	https://arxiv.org/pdf/2009.10461v1.pdf	https://github.com/aleckirkley/US-covid-tweets-with-sentiments-and-geolocations	true	true	true	none
https://paperswithcode.com/paper/pre-training-auto-generated-volumetric-shapes	Pre-Training Auto-Generated Volumetric Shapes for 3D Medical Image Segmentation	null	https://openaccess.thecvf.com/content/CVPR2023W/ECV/html/Tadokoro_Pre-Training_Auto-Generated_Volumetric_Shapes_for_3D_Medical_Image_Segmentation_CVPRW_2023_paper.html	https://openaccess.thecvf.com/content/CVPR2023W/ECV/papers/Tadokoro_Pre-Training_Auto-Generated_Volumetric_Shapes_for_3D_Medical_Image_Segmentation_CVPRW_2023_paper.pdf	https://github.com/super-tadory/primgeoseg	false	false	false	pytorch
https://paperswithcode.com/paper/comparison-by-conversion-reverse-engineering	Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics	2011.00834	https://arxiv.org/abs/2011.00834v1	https://arxiv.org/pdf/2011.00834v1.pdf	https://github.com/danielhers/hit-scir-ucca-parser	true	true	false	pytorch
https://paperswithcode.com/paper/bracketing-encodings-for-2-planar-dependency	Bracketing Encodings for 2-Planar Dependency Parsing	2011.00596	https://arxiv.org/abs/2011.00596v2	https://arxiv.org/pdf/2011.00596v2.pdf	https://github.com/mstrise/dep2label	true	true	false	pytorch
https://paperswithcode.com/paper/a-unifying-theory-of-transition-based-and	A Unifying Theory of Transition-based and Sequence Labeling Parsing	2011.00584	https://arxiv.org/abs/2011.00584v1	https://arxiv.org/pdf/2011.00584v1.pdf	https://github.com/mstrise/dep2label	true	true	false	pytorch
https://paperswithcode.com/paper/transitive-learning-exploring-the	Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolution	2103.15290	https://arxiv.org/abs/2103.15290v2	https://arxiv.org/pdf/2103.15290v2.pdf	https://github.com/YuanfeiHuang/TLSR	true	true	true	pytorch
https://paperswithcode.com/paper/learning-to-play-cup-and-ball-with-noisy	Learning to Play Cup-and-Ball with Noisy Camera Observations	2007.09562	https://arxiv.org/abs/2007.09562v1	https://arxiv.org/pdf/2007.09562v1.pdf	https://github.com/MPC-Berkeley/kendama	true	true	true	none
https://paperswithcode.com/paper/an-implementation-of-faster-rcnn-with-study	An Implementation of Faster RCNN with Study for Region Sampling	1702.02138	http://arxiv.org/abs/1702.02138v2	http://arxiv.org/pdf/1702.02138v2.pdf	https://github.com/tigerofmurder/tf-faster-rcnn	false	false	true	tf
https://paperswithcode.com/paper/faster-r-cnn-towards-real-time-object	Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	1506.01497	http://arxiv.org/abs/1506.01497v3	http://arxiv.org/pdf/1506.01497v3.pdf	https://github.com/tigerofmurder/tf-faster-rcnn	false	false	true	tf
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/tigerofmurder/tf-faster-rcnn	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.