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/recommendations-for-item-set-completion-on	Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities	2105.04376	https://arxiv.org/abs/2105.04376v1	https://arxiv.org/pdf/2105.04376v1.pdf	https://github.com/lgalke/aae-recommender	true	true	false	pytorch
https://paperswithcode.com/paper/active-fire-detection-in-landsat-8-imagery-a	Active Fire Detection in Landsat-8 Imagery: a Large-Scale Dataset and a Deep-Learning Study	2101.03409	https://arxiv.org/abs/2101.03409v2	https://arxiv.org/pdf/2101.03409v2.pdf	https://github.com/pereira-gha/activefire	true	true	true	tf
https://paperswithcode.com/paper/gift-learning-transformation-invariant-dense-1	GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs	1911.05932	https://arxiv.org/abs/1911.05932v1	https://arxiv.org/pdf/1911.05932v1.pdf	https://github.com/zju3dv/GIFT	false	false	true	pytorch
https://paperswithcode.com/paper/trtr-visual-tracking-with-transformer	TrTr: Visual Tracking with Transformer	2105.03817	https://arxiv.org/abs/2105.03817v1	https://arxiv.org/pdf/2105.03817v1.pdf	https://github.com/tongtybj/TrTr	true	true	false	pytorch
https://paperswithcode.com/paper/copula-based-normalizing-flows	Copula-Based Normalizing Flows	2107.07352	https://arxiv.org/abs/2107.07352v1	https://arxiv.org/pdf/2107.07352v1.pdf	https://github.com/MikeLasz/Copula-Based-Normalizing-Flows	true	true	false	pytorch
https://paperswithcode.com/paper/maximum-likelihood-minimum-effort	Maximum Likelihood, Minimum Effort	1106.5458	https://arxiv.org/abs/1106.5458v2	https://arxiv.org/pdf/1106.5458v2.pdf	https://github.com/fbm2718/QREM	false	false	true	none
https://paperswithcode.com/paper/quantum-overlapping-tomography	Quantum Overlapping Tomography	1908.02754	https://arxiv.org/abs/1908.02754v2	https://arxiv.org/pdf/1908.02754v2.pdf	https://github.com/fbm2718/QREM	false	false	true	none
https://paperswithcode.com/paper/assortativity-in-cognition	Assortativity in cognition	2205.15114	https://arxiv.org/abs/2205.15114v1	https://arxiv.org/pdf/2205.15114v1.pdf	https://github.com/eugeniovicario/assortativity_in_cognition	true	true	false	none
https://paperswithcode.com/paper/training-time-friendly-network-for-real-time	Training-Time-Friendly Network for Real-Time Object Detection	1909.00700	https://arxiv.org/abs/1909.00700v3	https://arxiv.org/pdf/1909.00700v3.pdf	https://github.com/ximilar-com/xcenternet	false	false	true	tf
https://paperswithcode.com/paper/objects-as-points	Objects as Points	1904.07850	http://arxiv.org/abs/1904.07850v2	http://arxiv.org/pdf/1904.07850v2.pdf	https://github.com/ximilar-com/xcenternet	false	false	true	tf
https://paperswithcode.com/paper/deformable-convolutional-networks	Deformable Convolutional Networks	1703.06211	http://arxiv.org/abs/1703.06211v3	http://arxiv.org/pdf/1703.06211v3.pdf	https://github.com/ximilar-com/xcenternet	false	false	true	tf
https://paperswithcode.com/paper/barbershop-gan-based-image-compositing-using	Barbershop: GAN-based Image Compositing using Segmentation Masks	2106.01505	https://arxiv.org/abs/2106.01505v2	https://arxiv.org/pdf/2106.01505v2.pdf	https://github.com/ZPdesu/Barbershop	false	false	true	pytorch
https://paperswithcode.com/paper/knowledge-distillation-from-bert-transformer	Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification	2108.02598	https://arxiv.org/abs/2108.02598v1	https://arxiv.org/pdf/2108.02598v1.pdf	https://github.com/Jiang-Yidi/TransformerDistillation-SLU	true	true	false	pytorch
https://paperswithcode.com/paper/doremi-first-glance-at-a-universal-omr	DoReMi: First glance at a universal OMR dataset	2107.07786	https://arxiv.org/abs/2107.07786v1	https://arxiv.org/pdf/2107.07786v1.pdf	https://github.com/apacha/OMR-Datasets	false	false	true	none
https://paperswithcode.com/paper/flex-unifying-evaluation-for-few-shot-nlp	FLEX: Unifying Evaluation for Few-Shot NLP	2107.07170	https://arxiv.org/abs/2107.07170v2	https://arxiv.org/pdf/2107.07170v2.pdf	https://github.com/allenai/unifew	true	true	true	pytorch
https://paperswithcode.com/paper/few-shot-forecasting-of-time-series-with	Few-Shot Forecasting of Time-Series with Heterogeneous Channels	2204.03456	https://arxiv.org/abs/2204.03456v2	https://arxiv.org/pdf/2204.03456v2.pdf	https://github.com/radrumond/timehetnet	true	true	true	tf
https://paperswithcode.com/paper/speeding-up-bigclam-implementation-on-snap	Speeding Up BigClam Implementation on SNAP	1712.01209	https://arxiv.org/abs/1712.01209v2	https://arxiv.org/pdf/1712.01209v2.pdf	https://github.com/liuchbryan/snap/tree/master/contrib/ICL-bigclam_speedup	true	false	false	none
https://paperswithcode.com/paper/question-generation-for-adaptive-education	Question Generation for Adaptive Education	2106.04262	https://arxiv.org/abs/2106.04262v1	https://arxiv.org/pdf/2106.04262v1.pdf	https://github.com/meghabyte/acl2021-education	true	true	false	pytorch
https://paperswithcode.com/paper/reconfigurable-intelligent-surfaces-a-signal	Reconfigurable Intelligent Surfaces: A Signal Processing Perspective With Wireless Applications	2102.00742	https://arxiv.org/abs/2102.00742v2	https://arxiv.org/pdf/2102.00742v2.pdf	https://github.com/emilbjornson/SP_Cup_2021	false	false	true	none
https://paperswithcode.com/paper/efficient-bitruss-decomposition-for-large	Efficient Bitruss Decomposition for Large-scale Bipartite Graphs	2001.06111	http://arxiv.org/abs/2001.06111v1	http://arxiv.org/pdf/2001.06111v1.pdf	https://github.com/kartiklakhotia/RECEIPT	false	false	true	none
https://paperswithcode.com/paper/scan-flood-fillscaff-an-efficient-automatic	Scan-flood Fill(SCAFF): an Efficient Automatic Precise Region Filling Algorithm for Complicated Regions	1906.03366	https://arxiv.org/abs/1906.03366v1	https://arxiv.org/pdf/1906.03366v1.pdf	https://github.com/SherylHYX/Scan-flood-Fill	true	true	true	none
https://paperswithcode.com/paper/revisiting-contrastive-methods-for	Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations	2106.05967	https://arxiv.org/abs/2106.05967v3	https://arxiv.org/pdf/2106.05967v3.pdf	https://github.com/wvangansbeke/Revisiting-Contrastive-SSL	true	true	true	pytorch
https://paperswithcode.com/paper/learning-manifold-patch-based-representations-1	Learning Manifold Patch-Based Representations of Man-Made Shapes	1906.12337	https://arxiv.org/abs/1906.12337v3	https://arxiv.org/pdf/1906.12337v3.pdf	https://github.com/dmsm/LearningPatches	true	false	false	pytorch
https://paperswithcode.com/paper/modeling-and-control-of-morphing-covers-for	Modeling and Control of Morphing Covers for the Adaptive Morphology of Humanoid Robots	2207.01025	https://arxiv.org/abs/2207.01025v2	https://arxiv.org/pdf/2207.01025v2.pdf	https://github.com/ami-iit/mystica	true	true	false	none
https://paperswithcode.com/paper/yolact-real-time-instance-segmentation	YOLACT: Real-time Instance Segmentation	1904.02689	https://arxiv.org/abs/1904.02689v2	https://arxiv.org/pdf/1904.02689v2.pdf	https://github.com/Abhijeet8901/Instance-Segmentation-using-YOLACT	false	false	true	pytorch
https://paperswithcode.com/paper/computing-multiple-solutions-of-topology	Computing multiple solutions of topology optimization problems	2004.11797	https://arxiv.org/abs/2004.11797v2	https://arxiv.org/pdf/2004.11797v2.pdf	https://bitbucket.org/papadopoulos/deflatedbarrier	true	true	false	none
https://paperswithcode.com/paper/deep-learning-models-for-multilingual-hate	Deep Learning Models for Multilingual Hate Speech Detection	2004.06465	https://arxiv.org/abs/2004.06465v3	https://arxiv.org/pdf/2004.06465v3.pdf	https://github.com/hate-alert/DE-LIMIT	false	false	true	pytorch
https://paperswithcode.com/paper/you-only-look-yourself-unsupervised-and	You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network	2006.16829	https://arxiv.org/abs/2006.16829v1	https://arxiv.org/pdf/2006.16829v1.pdf	https://github.com/XLearning-SCU/2021-IJCV-YOLY	true	false	false	pytorch
https://paperswithcode.com/paper/hvsrweb-an-open-source-web-based-application	HVSRweb: An Open-Source, Web-Based Application for Horizontal-to-Vertical Spectral Ratio Processing	2106.06050	https://arxiv.org/abs/2106.06050v1	https://arxiv.org/pdf/2106.06050v1.pdf	https://github.com/jpvantassel/hvsrweb	true	true	false	none
https://paperswithcode.com/paper/an-inexact-augmented-lagrangian-method-for	An inexact augmented Lagrangian method for nonsmooth optimization on Riemannian manifold	1911.09900	http://arxiv.org/abs/1911.09900v2	http://arxiv.org/pdf/1911.09900v2.pdf	https://github.com/KKDeng/mialm_code_share	true	false	true	none
https://paperswithcode.com/paper/benchmarks-for-deep-off-policy-evaluation-1	Benchmarks for Deep Off-Policy Evaluation	2103.16596	https://arxiv.org/abs/2103.16596v1	https://arxiv.org/pdf/2103.16596v1.pdf	https://github.com/tedmoskovitz/TOP	false	false	true	pytorch
https://paperswithcode.com/paper/structured-attention-for-unsupervised	Structured Attention for Unsupervised Dialogue Structure Induction	2009.08552	https://arxiv.org/abs/2009.08552v2	https://arxiv.org/pdf/2009.08552v2.pdf	https://github.com/Liang-Qiu/SVRNN-dialogues	true	true	true	pytorch
https://paperswithcode.com/paper/cascade-cost-volume-for-high-resolution-multi	Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching	1912.06378	https://arxiv.org/abs/1912.06378v3	https://arxiv.org/pdf/1912.06378v3.pdf	https://github.com/apchenstu/mvsnerf	false	false	true	pytorch
https://paperswithcode.com/paper/structure-extraction-in-task-oriented	Structure Extraction in Task-Oriented Dialogues with Slot Clustering	2203.00073	https://arxiv.org/abs/2203.00073v3	https://arxiv.org/pdf/2203.00073v3.pdf	https://github.com/Liang-Qiu/SVRNN-dialogues	false	false	true	pytorch
https://paperswithcode.com/paper/invariance-principle-meets-information	Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization	2106.06607	https://arxiv.org/abs/2106.06607v2	https://arxiv.org/pdf/2106.06607v2.pdf	https://github.com/ahujak/IB-IRM	true	true	false	pytorch
https://paperswithcode.com/paper/defending-against-backdoors-in-federated	Defending against Backdoors in Federated Learning with Robust Learning Rate	2007.03767	https://arxiv.org/abs/2007.03767v4	https://arxiv.org/pdf/2007.03767v4.pdf	https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate	true	true	true	pytorch
https://paperswithcode.com/paper/mimicking-production-behavior-with-generated	Mimicking Production Behavior with Generated Mocks	2208.01321	https://arxiv.org/abs/2208.01321v4	https://arxiv.org/pdf/2208.01321v4.pdf	https://github.com/castor-software/rick-experiments	true	true	false	none
https://paperswithcode.com/paper/structext-structured-text-understanding-with	StrucTexT: Structured Text Understanding with Multi-Modal Transformers	2108.02923	https://arxiv.org/abs/2108.02923v3	https://arxiv.org/pdf/2108.02923v3.pdf	https://github.com/PaddlePaddle/VIMER/tree/main/StrucTexT	true	false	false	paddle
https://paperswithcode.com/paper/pair-diffusion-a-comprehensive-multimodal	PAIR Diffusion: A Comprehensive Multimodal Object-Level Image Editor	null	http://openaccess.thecvf.com//content/CVPR2024/html/Goel_PAIR_Diffusion_A_Comprehensive_Multimodal_Object-Level_Image_Editor_CVPR_2024_paper.html	http://openaccess.thecvf.com//content/CVPR2024/papers/Goel_PAIR_Diffusion_A_Comprehensive_Multimodal_Object-Level_Image_Editor_CVPR_2024_paper.pdf	https://github.com/picsart-ai-research/pair-diffusion	true	true	false	pytorch
https://paperswithcode.com/paper/faster-ltn-a-neuro-symbolic-end-to-end-object	Faster-LTN: a neuro-symbolic, end-to-end object detection architecture	2107.01877	https://arxiv.org/abs/2107.01877v1	https://arxiv.org/pdf/2107.01877v1.pdf	https://gitlab.com/grains2/Faster-LTN	true	true	false	tf
https://paperswithcode.com/paper/optimizing-graphical-procedures-for	Optimizing Graphical Procedures for Multiplicity Control in a Confirmatory Clinical Trial via Deep Learning	1908.10262	https://arxiv.org/abs/1908.10262v2	https://arxiv.org/pdf/1908.10262v2.pdf	https://github.com/tian-yu-zhan/dnn_optimization	true	true	false	none
https://paperswithcode.com/paper/a-large-scale-study-on-research-code-quality	A large-scale study on research code quality and execution	2103.12793	https://arxiv.org/abs/2103.12793v1	https://arxiv.org/pdf/2103.12793v1.pdf	https://github.com/atrisovic/dataverse-r-study	true	true	true	none
https://paperswithcode.com/paper/fine-grained-continual-learning	Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches	1907.03799	https://arxiv.org/abs/1907.03799v3	https://arxiv.org/pdf/1907.03799v3.pdf	https://github.com/vlomonaco/core50	false	false	true	none
https://paperswithcode.com/paper/hdr-environment-map-estimation-for-real-time	HDR Environment Map Estimation for Real-Time Augmented Reality	2011.10687	https://arxiv.org/abs/2011.10687v5	https://arxiv.org/pdf/2011.10687v5.pdf	https://github.com/apple/ml-envmapnet	true	false	true	none
https://paperswithcode.com/paper/potential-gap-using-reactive-policies-to	Potential Gap: Using Reactive Policies to Guarantee Safe Navigation	2103.11491	https://arxiv.org/abs/2103.11491v1	https://arxiv.org/pdf/2103.11491v1.pdf	https://github.com/ivaROS/PotentialGap	false	false	true	none
https://paperswithcode.com/paper/wkb-based-scheme-with-adaptive-step-size	WKB-based scheme with adaptive step size control for the Schrödinger equation in the highly oscillatory regime	2102.03107	https://arxiv.org/abs/2102.03107v2	https://arxiv.org/pdf/2102.03107v2.pdf	https://github.com/JannisKoerner/adaptive-WKB-marching-method	true	true	true	none
https://paperswithcode.com/paper/frustum-pointnets-for-3d-object-detection	Frustum PointNets for 3D Object Detection from RGB-D Data	1711.08488	http://arxiv.org/abs/1711.08488v2	http://arxiv.org/pdf/1711.08488v2.pdf	https://github.com/charlesq34/frustum-pointnets	true	false	true	tf
https://paperswithcode.com/paper/trajformer-trajectory-prediction-with-local	Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving	2011.14910	https://arxiv.org/abs/2011.14910v1	https://arxiv.org/pdf/2011.14910v1.pdf	https://github.com/Manojbhat09/Trajformer	true	true	true	pytorch
https://paperswithcode.com/paper/transition-based-bubble-parsing-improvements	Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction	2107.06905	https://arxiv.org/abs/2107.06905v1	https://arxiv.org/pdf/2107.06905v1.pdf	https://github.com/tzshi/bubble-parser-acl21	true	true	false	pytorch
https://paperswithcode.com/paper/terapipe-token-level-pipeline-parallelism-for	TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models	2102.07988	https://arxiv.org/abs/2102.07988v2	https://arxiv.org/pdf/2102.07988v2.pdf	https://github.com/zhuohan123/terapipe	true	true	false	pytorch
https://paperswithcode.com/paper/global-context-enhanced-social-recommendation	Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks	2110.04039	https://arxiv.org/abs/2110.04039v1	https://arxiv.org/pdf/2110.04039v1.pdf	https://github.com/xhcdream/sr-hgnn	true	true	false	pytorch
https://paperswithcode.com/paper/recommendations-for-datasets-for-source-code	Recommendations for Datasets for Source Code Summarization	1904.02660	http://arxiv.org/abs/1904.02660v1	http://arxiv.org/pdf/1904.02660v1.pdf	https://github.com/sjj0403/Datasets-for-code-summarization-evaluation	false	false	true	pytorch
https://paperswithcode.com/paper/star-sparse-transformer-based-action	STAR: Sparse Transformer-based Action Recognition	2107.07089	https://arxiv.org/abs/2107.07089v1	https://arxiv.org/pdf/2107.07089v1.pdf	https://github.com/imj2185/STAR	true	false	true	pytorch
https://paperswithcode.com/paper/word-recognition-with-deep-conditional-random	Word Recognition with Deep Conditional Random Fields	1612.01072	http://arxiv.org/abs/1612.01072v1	http://arxiv.org/pdf/1612.01072v1.pdf	https://github.com/ganggit/deepCRFs	true	true	false	none
https://paperswithcode.com/paper/towards-end-to-end-semi-supervised-learning	Towards End-to-end Semi-supervised Learning for One-stage Object Detection	2302.11299	https://arxiv.org/abs/2302.11299v1	https://arxiv.org/pdf/2302.11299v1.pdf	https://github.com/luogen1996/oneteacher	true	true	false	pytorch
https://paperswithcode.com/paper/addressing-function-approximation-error-in	Addressing Function Approximation Error in Actor-Critic Methods	1802.09477	http://arxiv.org/abs/1802.09477v3	http://arxiv.org/pdf/1802.09477v3.pdf	https://github.com/pkasala/ContinuesControl	false	false	true	pytorch
https://paperswithcode.com/paper/machine-learning-kondo-physics-using	Machine learning of Kondo physics using variational autoencoders and symbolic regression	2107.08013	https://arxiv.org/abs/2107.08013v2	https://arxiv.org/pdf/2107.08013v2.pdf	https://github.com/ColeMiles/SpectralVAE	true	true	false	pytorch
https://paperswithcode.com/paper/ms-mda-multisource-marginal-distribution	MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition	2107.07740	https://arxiv.org/abs/2107.07740v1	https://arxiv.org/pdf/2107.07740v1.pdf	https://github.com/VoiceBeer/MS-MDA	true	true	false	pytorch
https://paperswithcode.com/paper/approaches-to-constrained-quantum-approximate	Approaches to Constrained Quantum Approximate Optimization	2010.06660	https://arxiv.org/abs/2010.06660v3	https://arxiv.org/pdf/2010.06660v3.pdf	https://github.com/Quantum-Software-Tools/dqva-and-circuit-cutting	false	false	true	none
https://paperswithcode.com/paper/latentkeypointgan-controlling-gans-via-latent	LatentKeypointGAN: Controlling Images via Latent Keypoints	2103.15812	https://arxiv.org/abs/2103.15812v5	https://arxiv.org/pdf/2103.15812v5.pdf	https://github.com/DELTA37/LatentKeypointGAN	false	false	false	pytorch
https://paperswithcode.com/paper/r-drop-regularized-dropout-for-neural	R-Drop: Regularized Dropout for Neural Networks	2106.14448	https://arxiv.org/abs/2106.14448v2	https://arxiv.org/pdf/2106.14448v2.pdf	https://github.com/zbp-xxxp/R-Drop-Paddle	false	false	false	paddle
https://paperswithcode.com/paper/generalized-variational-inference-in-function	Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning	2205.06342	https://arxiv.org/abs/2205.06342v2	https://arxiv.org/pdf/2205.06342v2.pdf	https://github.com/MrHuff/GWI	true	true	false	pytorch
https://paperswithcode.com/paper/autoscore-survival-developing-interpretable	AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data	2106.06957	https://arxiv.org/abs/2106.06957v1	https://arxiv.org/pdf/2106.06957v1.pdf	https://github.com/nliulab/AutoScore-Survival	true	true	true	none
https://paperswithcode.com/paper/atspy-automated-time-series-forecasting-in	AtsPy: Automated Time Series Forecasting in Python	null	https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3580631	https://poseidon01.ssrn.com/delivery.php?ID=707091125114113026107095123106012077118020024084061089000004119106020064002075106096026057102032006102108123122117114083097012038034045078021105097124103065089098001069030017007065001016083087005002028016069112115112083121104114122001107118013017105025&EXT=pdf&INDEX=TRUE	https://github.com/firmai/atspy	false	false	false	tf
https://paperswithcode.com/paper/explanations-based-on-the-missing-towards	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives	1802.07623	http://arxiv.org/abs/1802.07623v2	http://arxiv.org/pdf/1802.07623v2.pdf	https://github.com/IBM/Contrastive-Explanation-Method	true	true	true	tf
https://paperswithcode.com/paper/scalability-in-perception-for-autonomous	Scalability in Perception for Autonomous Driving: Waymo Open Dataset	1912.04838	https://arxiv.org/abs/1912.04838v7	https://arxiv.org/pdf/1912.04838v7.pdf	https://github.com/p-mc-grath/DMMFODS	false	false	true	pytorch
https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical	U-Net: Convolutional Networks for Biomedical Image Segmentation	1505.04597	http://arxiv.org/abs/1505.04597v1	http://arxiv.org/pdf/1505.04597v1.pdf	https://github.com/p-mc-grath/DMMFODS	false	false	true	pytorch
https://paperswithcode.com/paper/densely-connected-convolutional-networks	Densely Connected Convolutional Networks	1608.06993	http://arxiv.org/abs/1608.06993v5	http://arxiv.org/pdf/1608.06993v5.pdf	https://github.com/p-mc-grath/DMMFODS	false	false	true	pytorch
https://paperswithcode.com/paper/lale-consistent-automated-machine-learning	Lale: Consistent Automated Machine Learning	2007.01977	https://arxiv.org/abs/2007.01977v1	https://arxiv.org/pdf/2007.01977v1.pdf	https://github.com/IBM/Lale.jl	false	false	true	none
https://paperswithcode.com/paper/iranis-a-large-scale-dataset-of-farsi-license	Iranis: A Large-scale Dataset of Farsi License Plate Characters	2101.00295	https://arxiv.org/abs/2101.00295v1	https://arxiv.org/pdf/2101.00295v1.pdf	https://github.com/alitourani/Iranis-dataset	true	false	true	none
https://paperswithcode.com/paper/modeling-natural-language-emergence-with	Modeling natural language emergence with integral transform theory and reinforcement learning	1812.01431	http://arxiv.org/abs/1812.01431v1	http://arxiv.org/pdf/1812.01431v1.pdf	https://github.com/Quiltomics/NLERL	true	true	false	tf
https://paperswithcode.com/paper/accurate-liability-estimation-improves-power	Accurate Liability Estimation Improves Power in Ascertained Case Control Studies	1409.2448	http://arxiv.org/abs/1409.2448v3	http://arxiv.org/pdf/1409.2448v3.pdf	https://github.com/omerwe/LEAP	true	true	false	none
https://paperswithcode.com/paper/bag-tag-em-a-new-dutch-stemmer	Bag \& Tag'em - A New Dutch Stemmer	null	https://aclanthology.org/2020.lrec-1.477	https://aclanthology.org/2020.lrec-1.477.pdf	https://github.com/Anne-Jonker/Bag-Tag-em	true	true	false	none
https://paperswithcode.com/paper/guided-search-for-desired-functional	Guided search for desired functional responses via Bayesian optimization of generative model: hysteresis loop shape engineering in ferroelectrics	2004.12512	https://arxiv.org/abs/2004.12512v1	https://arxiv.org/pdf/2004.12512v1.pdf	https://github.com/ramav87/Ferrosim	true	true	false	none
https://paperswithcode.com/paper/to-vr-or-not-to-vr-is-virtual-reality	To VR or not to VR: Is virtual reality suitable to understand software development metrics?	2109.13768	https://arxiv.org/abs/2109.13768v1	https://arxiv.org/pdf/2109.13768v1.pdf	https://gitlab.com/babiaxr/aframe-babia-components	true	true	false	none
https://paperswithcode.com/paper/image-based-correction-of-continuous-and	Image-Based Correction of Continuous and Discontinuous Non-Planar Axial Distortion in Serial Section Microscopy	1511.01161	http://arxiv.org/abs/1511.01161v2	http://arxiv.org/pdf/1511.01161v2.pdf	https://github.com/saalfeldlab/em-thickness-estimation	true	true	false	none
https://paperswithcode.com/paper/spatial-temporal-transformer-for-dynamic	Spatial-Temporal Transformer for Dynamic Scene Graph Generation	2107.12309	https://arxiv.org/abs/2107.12309v2	https://arxiv.org/pdf/2107.12309v2.pdf	https://github.com/yrcong/sttran	true	true	true	pytorch
https://paperswithcode.com/paper/yolox-exceeding-yolo-series-in-2021	YOLOX: Exceeding YOLO Series in 2021	2107.08430	https://arxiv.org/abs/2107.08430v2	https://arxiv.org/pdf/2107.08430v2.pdf	https://github.com/StephenStorm/YOLOX	false	false	true	pytorch
https://paperswithcode.com/paper/probing-for-labeled-dependency-trees	Probing for Labeled Dependency Trees	2203.12971	https://arxiv.org/abs/2203.12971v1	https://arxiv.org/pdf/2203.12971v1.pdf	https://github.com/personads/depprobe	true	false	false	pytorch
https://paperswithcode.com/paper/dropgnn-random-dropouts-increase-the	DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks	2111.06283	https://arxiv.org/abs/2111.06283v1	https://arxiv.org/pdf/2111.06283v1.pdf	https://github.com/karolismart/dropgnn	true	true	true	pytorch
https://paperswithcode.com/paper/automatic-annotation-and-evaluation-of-error	Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction	null	https://aclanthology.org/P17-1074	https://aclanthology.org/P17-1074.pdf	https://github.com/chrisjbryant/errant	true	true	false	none
https://paperswithcode.com/paper/epidemic-thresholds-of-infectious-diseases-on	Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks	2009.12932	https://arxiv.org/abs/2009.12932v2	https://arxiv.org/pdf/2009.12932v2.pdf	https://github.com/qinyichen/tie-decay-epidemic-threshold	true	true	true	none
https://paperswithcode.com/paper/opinionated-practices-for-teaching	Opinionated practices for teaching reproducibility: motivation, guided instruction and practice	2109.13656	https://arxiv.org/abs/2109.13656v2	https://arxiv.org/pdf/2109.13656v2.pdf	https://github.com/UBC-MDS/opinionated-practices-for-teaching-reproducibility	true	false	false	none
https://paperswithcode.com/paper/parallel-peeling-of-bipartite-networks-for	Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery	2110.12511	https://arxiv.org/abs/2110.12511v1	https://arxiv.org/pdf/2110.12511v1.pdf	https://github.com/kartiklakhotia/RECEIPT	true	true	false	none
https://paperswithcode.com/paper/pseudo-relevance-feedback-for-multiple	Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval	2106.11251	https://arxiv.org/abs/2106.11251v2	https://arxiv.org/pdf/2106.11251v2.pdf	https://github.com/cmacdonald/pyterrier_colbert	true	false	true	pytorch
https://paperswithcode.com/paper/implicit-svd-for-graph-representation	Implicit SVD for Graph Representation Learning	2111.06312	https://arxiv.org/abs/2111.06312v1	https://arxiv.org/pdf/2111.06312v1.pdf	https://github.com/samihaija/isvd	true	true	false	tf
https://paperswithcode.com/paper/a-consolidated-open-knowledge-representation	A Consolidated Open Knowledge Representation for Multiple Texts	null	https://aclanthology.org/W17-0902	https://aclanthology.org/W17-0902.pdf	https://github.com/vered1986/OKR	true	true	false	none
https://paperswithcode.com/paper/massformer-tandem-mass-spectrum-prediction	MassFormer: Tandem Mass Spectrum Prediction for Small Molecules using Graph Transformers	2111.04824	https://arxiv.org/abs/2111.04824v3	https://arxiv.org/pdf/2111.04824v3.pdf	https://github.com/samgoldman97/ms-pred	false	false	true	pytorch
https://paperswithcode.com/paper/automatically-polyconvex-strain-energy	Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations	2110.03774	https://arxiv.org/abs/2110.03774v2	https://arxiv.org/pdf/2110.03774v2.pdf	https://github.com/tajtac/node	true	true	false	jax
https://paperswithcode.com/paper/scalable-visual-transformers-with	Scalable Vision Transformers with Hierarchical Pooling	2103.10619	https://arxiv.org/abs/2103.10619v2	https://arxiv.org/pdf/2103.10619v2.pdf	https://github.com/MonashAI/HVT	true	true	true	pytorch
https://paperswithcode.com/paper/window-level-is-a-strong-denoising-surrogate	Window-Level is a Strong Denoising Surrogate	2105.07153	https://arxiv.org/abs/2105.07153v1	https://arxiv.org/pdf/2105.07153v1.pdf	https://github.com/zubaerimran/SSWL-IDN	true	true	true	pytorch
https://paperswithcode.com/paper/galactic-diffuse-gamma-rays-meet-the-pev	Galactic diffuse gamma rays meet the PeV frontier	2203.15759	https://arxiv.org/abs/2203.15759v3	https://arxiv.org/pdf/2203.15759v3.pdf	https://github.com/tospines/gamma-variable_high-resolution	true	true	false	none
https://paperswithcode.com/paper/nifty-web-apps-build-a-web-app-for-any-text	Nifty Web Apps: Build a Web App for Any Text-Based Programming Assignment	2010.04671	https://arxiv.org/abs/2010.04671v1	https://arxiv.org/pdf/2010.04671v1.pdf	https://github.com/kevinlin1/nifty-web-apps	true	false	true	none
https://paperswithcode.com/paper/not-just-a-black-box-learning-important	Not Just a Black Box: Learning Important Features Through Propagating Activation Differences	1605.01713	http://arxiv.org/abs/1605.01713v3	http://arxiv.org/pdf/1605.01713v3.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/vit-cx-causal-explanation-of-vision	ViT-CX: Causal Explanation of Vision Transformers	2211.03064	https://arxiv.org/abs/2211.03064v3	https://arxiv.org/pdf/2211.03064v3.pdf	https://github.com/vaynexie/CausalX-ViT	true	true	true	pytorch
https://paperswithcode.com/paper/mura-large-dataset-for-abnormality-detection	MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs	1712.06957	http://arxiv.org/abs/1712.06957v4	http://arxiv.org/pdf/1712.06957v4.pdf	https://github.com/anirudh2019/MURA-xception-inceptionV2	false	false	true	tf
https://paperswithcode.com/paper/agglomerative-fast-super-paramagnetic	Agglomerative Likelihood Clustering	1908.00951	https://arxiv.org/abs/1908.00951v4	https://arxiv.org/pdf/1908.00951v4.pdf	https://github.com/tehraio/timeseries_gen	false	false	true	none
https://paperswithcode.com/paper/graph2mda-a-multi-modal-variational-graph	Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug associations	2108.06338	https://arxiv.org/abs/2108.06338v1	https://arxiv.org/pdf/2108.06338v1.pdf	https://github.com/moen-hyb/Graph2MDA	true	false	false	tf
https://paperswithcode.com/paper/syntactic-parse-fusion	Syntactic Parse Fusion	null	https://aclanthology.org/D15-1160	https://aclanthology.org/D15-1160.pdf	https://github.com/BLLIP/bllip-parser	true	true	false	none
https://paperswithcode.com/paper/improved-techniques-for-model-inversion-1	Knowledge-Enriched Distributional Model Inversion Attacks	2010.04092	https://arxiv.org/abs/2010.04092v4	https://arxiv.org/pdf/2010.04092v4.pdf	https://github.com/scccc21/knowledge-enriched-dmi	true	true	true	pytorch

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.