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/fedentropy-efficient-device-grouping-for	FedEntropy: Efficient Device Grouping for Federated Learning Using Maximum Entropy Judgment	2205.12038	https://arxiv.org/abs/2205.12038v1	https://arxiv.org/pdf/2205.12038v1.pdf	https://github.com/fedentropy/fedentropy	true	true	false	pytorch
https://paperswithcode.com/paper/learning-transferable-visual-models-from	Learning Transferable Visual Models From Natural Language Supervision	2103.00020	https://arxiv.org/abs/2103.00020v1	https://arxiv.org/pdf/2103.00020v1.pdf	https://github.com/sberbank-ai/ru-clip	false	false	true	pytorch
https://paperswithcode.com/paper/tackling-fake-news-detection-by-continually	Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks	null	https://aclanthology.org/2022.acl-long.97	https://aclanthology.org/2022.acl-long.97.pdf	https://github.com/hockeybro12/fakenews_inference_operators	true	true	false	pytorch
https://paperswithcode.com/paper/bayesian-functional-principal-components-1	Bayesian modeling of nearly mutually orthogonal processes	2205.12361	https://arxiv.org/abs/2205.12361v3	https://arxiv.org/pdf/2205.12361v3.pdf	https://github.com/jamesmatuk/remo-fpca	true	true	false	none
https://paperswithcode.com/paper/bionic-tracking-using-eye-tracking-to-track	Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality	2005.00387	https://arxiv.org/abs/2005.00387v2	https://arxiv.org/pdf/2005.00387v2.pdf	https://github.com/scenerygraphics/bionic-tracking	true	true	false	none
https://paperswithcode.com/paper/the-neuro-symbolic-brain	The Neuro-Symbolic Brain	2205.13440	https://arxiv.org/abs/2205.13440v1	https://arxiv.org/pdf/2205.13440v1.pdf	https://github.com/robertlizee/neuro-symbolic-vm	true	false	true	none
https://paperswithcode.com/paper/flexible-and-fast-estimation-of-binary-merger	Flexible and Fast Estimation of Binary Merger Population Distributions with Adaptive KDE	2112.12659	https://arxiv.org/abs/2112.12659v3	https://arxiv.org/pdf/2112.12659v3.pdf	https://github.com/jamsadiq/peakdetectionalgorithm	true	true	true	none
https://paperswithcode.com/paper/domain-adaptive-faster-r-cnn-for-object	Domain Adaptive Faster R-CNN for Object Detection in the Wild	1803.03243	http://arxiv.org/abs/1803.03243v1	http://arxiv.org/pdf/1803.03243v1.pdf	https://github.com/shreyasrajesh/DA-Object-Detection	false	false	true	pytorch
https://paperswithcode.com/paper/cross-modality-discrepant-interaction-network	Cross-modality Discrepant Interaction Network for RGB-D Salient Object Detection	2108.01971	https://arxiv.org/abs/2108.01971v1	https://arxiv.org/pdf/2108.01971v1.pdf	https://github.com/kingcong/CDINet	false	false	false	mindspore
https://paperswithcode.com/paper/extending-the-design-space-of-graph-neural-1	Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman	2306.03266	https://arxiv.org/abs/2306.03266v3	https://arxiv.org/pdf/2306.03266v3.pdf	https://github.com/jiaruifeng/n2gnn	true	true	true	pytorch
https://paperswithcode.com/paper/transfuser-imitation-with-transformer-based	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving	2205.15997	https://arxiv.org/abs/2205.15997v1	https://arxiv.org/pdf/2205.15997v1.pdf	https://github.com/autonomousvision/transfuser	true	true	true	pytorch
https://paperswithcode.com/paper/a-unified-weight-initialization-paradigm-for	A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks	2205.15307	https://arxiv.org/abs/2205.15307v2	https://arxiv.org/pdf/2205.15307v2.pdf	https://github.com/tnbar/tednet	true	true	false	pytorch
https://paperswithcode.com/paper/preparing-an-endangered-language-for-the	Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish	2205.15599	https://arxiv.org/abs/2205.15599v1	https://arxiv.org/pdf/2205.15599v1.pdf	https://github.com/collectivat-dev/espanyol-ladino-translation	true	true	false	none
https://paperswithcode.com/paper/aggregated-residual-transformations-for-deep	Aggregated Residual Transformations for Deep Neural Networks	1611.05431	http://arxiv.org/abs/1611.05431v2	http://arxiv.org/pdf/1611.05431v2.pdf	https://github.com/2023-MindSpore-1/ms-code-13	false	false	false	mindspore
https://paperswithcode.com/paper/a-theoretical-study-on-solving-continual	A Theoretical Study on Solving Continual Learning	2211.02633	https://arxiv.org/abs/2211.02633v1	https://arxiv.org/pdf/2211.02633v1.pdf	https://github.com/k-gyuhak/wptp	true	true	false	pytorch
https://paperswithcode.com/paper/an-image-is-worth-16x16-words-transformers-1	An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	2010.11929	https://arxiv.org/abs/2010.11929v2	https://arxiv.org/pdf/2010.11929v2.pdf	https://github.com/OML-Team/open-metric-learning	false	false	false	pytorch
https://paperswithcode.com/paper/constrained-variational-policy-optimization	Constrained Variational Policy Optimization for Safe Reinforcement Learning	2201.11927	https://arxiv.org/abs/2201.11927v3	https://arxiv.org/pdf/2201.11927v3.pdf	https://github.com/liuzuxin/cvpo-safe-rl	true	true	true	pytorch
https://paperswithcode.com/paper/pgmpy-a-python-toolkit-for-bayesian-networks	pgmpy: A Python Toolkit for Bayesian Networks	2304.08639	https://arxiv.org/abs/2304.08639v1	https://arxiv.org/pdf/2304.08639v1.pdf	https://github.com/pgmpy/pgmpy	true	true	false	pytorch
https://paperswithcode.com/paper/cyclemix-a-holistic-strategy-for-medical	CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision	2203.01475	https://arxiv.org/abs/2203.01475v2	https://arxiv.org/pdf/2203.01475v2.pdf	https://github.com/bwgzk/cyclemix	true	true	true	pytorch
https://paperswithcode.com/paper/recbole-2-0-towards-a-more-up-to-date	RecBole 2.0: Towards a More Up-to-Date Recommendation Library	2206.07351	https://arxiv.org/abs/2206.07351v2	https://arxiv.org/pdf/2206.07351v2.pdf	https://github.com/rucaibox/recbole2.0	true	true	true	pytorch
https://paperswithcode.com/paper/emerging-properties-in-self-supervised-vision	Emerging Properties in Self-Supervised Vision Transformers	2104.14294	https://arxiv.org/abs/2104.14294v2	https://arxiv.org/pdf/2104.14294v2.pdf	https://github.com/OML-Team/open-metric-learning	false	false	false	pytorch
https://paperswithcode.com/paper/bevdet-high-performance-multi-camera-3d	BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View	2112.11790	https://arxiv.org/abs/2112.11790v3	https://arxiv.org/pdf/2112.11790v3.pdf	https://github.com/HuangJunJie2017/BEVDet	true	true	true	pytorch
https://paperswithcode.com/paper/on-the-surprising-behaviour-of-node2vec	On the Surprising Behaviour of node2vec	2206.08252	https://arxiv.org/abs/2206.08252v2	https://arxiv.org/pdf/2206.08252v2.pdf	https://github.com/aidos-lab/node2vec-surprises	true	true	false	pytorch
https://paperswithcode.com/paper/distributionally-robust-losses-for-latent	Distributionally Robust Losses for Latent Covariate Mixtures	2007.13982	https://arxiv.org/abs/2007.13982v2	https://arxiv.org/pdf/2007.13982v2.pdf	https://github.com/hsnamkoong/marginal-dro	true	true	false	pytorch
https://paperswithcode.com/paper/projection-scrubbing-a-more-effective-data	Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing	2108.00319	https://arxiv.org/abs/2108.00319v4	https://arxiv.org/pdf/2108.00319v4.pdf	https://github.com/cran/fMRIscrub	false	false	true	none
https://paperswithcode.com/paper/learning-stochastic-parametric-differentiable	Learning Stochastic Parametric Differentiable Predictive Control Policies	2203.01447	https://arxiv.org/abs/2203.01447v2	https://arxiv.org/pdf/2203.01447v2.pdf	https://github.com/pnnl/neuromancer	true	true	false	pytorch
https://paperswithcode.com/paper/neural-inverse-kinematics	Neural Inverse Kinematics	2205.10837	https://arxiv.org/abs/2205.10837v1	https://arxiv.org/pdf/2205.10837v1.pdf	https://github.com/RaphaelBensTAU/NeuralInverseKinematics	true	false	true	pytorch
https://paperswithcode.com/paper/instant-neural-graphics-primitives-with-a	Instant Neural Graphics Primitives with a Multiresolution Hash Encoding	2201.05989	https://arxiv.org/abs/2201.05989v2	https://arxiv.org/pdf/2201.05989v2.pdf	https://github.com/kair-bair/nerfacc	false	false	false	pytorch
https://paperswithcode.com/paper/the-sigma-8-tension-is-a-drag	The Sigma-8 Tension is a Drag	2209.06217	https://arxiv.org/abs/2209.06217v2	https://arxiv.org/pdf/2209.06217v2.pdf	https://github.com/brinckmann/montepython_public	true	true	false	none
https://paperswithcode.com/paper/automatic-correction-of-human-translations	Automatic Correction of Human Translations	2206.08593	https://arxiv.org/abs/2206.08593v1	https://arxiv.org/pdf/2206.08593v1.pdf	https://github.com/lilt/tec	true	true	true	none
https://paperswithcode.com/paper/thompson-sampling-for-robust-transfer-in	Thompson Sampling for Robust Transfer in Multi-Task Bandits	2206.08556	https://arxiv.org/abs/2206.08556v1	https://arxiv.org/pdf/2206.08556v1.pdf	https://github.com/zhiwang123/eps-mpmab-ts	true	true	false	none
https://paperswithcode.com/paper/object-structural-points-representation-for	Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping	2206.10263	https://arxiv.org/abs/2206.10263v1	https://arxiv.org/pdf/2206.10263v1.pdf	https://github.com/airlab-polimi/c-slam	true	true	false	none
https://paperswithcode.com/paper/diagnostic-tool-for-out-of-sample-model	Diagnostic Tool for Out-of-Sample Model Evaluation	2206.10982	https://arxiv.org/abs/2206.10982v3	https://arxiv.org/pdf/2206.10982v3.pdf	https://github.com/el-hult/lal	true	true	false	pytorch
https://paperswithcode.com/paper/panoramic-panoptic-segmentation-insights-into	Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive Learning	2206.10711	https://arxiv.org/abs/2206.10711v2	https://arxiv.org/pdf/2206.10711v2.pdf	https://github.com/alexanderjaus/PPS	true	true	true	pytorch
https://paperswithcode.com/paper/a-novel-approach-for-exploring-the-light	A Novel Approach for Exploring the Light Traveling Path in the Medium with a Spherically Symmetric Refractive Index	2212.02642	https://arxiv.org/abs/2212.02642v1	https://arxiv.org/pdf/2212.02642v1.pdf	https://github.com/shengyangzhuang/A-Novel-Approach-for-Exploring-the-Light-Traveling-Path-in-the-Spherically-Symmetric-Medium	true	false	false	none
https://paperswithcode.com/paper/symmetric-network-with-spatial-relationship	Symmetric Network with Spatial Relationship Modeling for Natural Language-based Vehicle Retrieval	2206.10879	https://arxiv.org/abs/2206.10879v1	https://arxiv.org/pdf/2206.10879v1.pdf	https://github.com/hbchen121/aicity2022_track2_ssm	true	true	true	pytorch
https://paperswithcode.com/paper/visfis-visual-feature-importance-supervision	VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives	2206.11212	https://arxiv.org/abs/2206.11212v2	https://arxiv.org/pdf/2206.11212v2.pdf	https://github.com/zfying/visfis	true	true	true	pytorch
https://paperswithcode.com/paper/matrix-completion-and-low-rank-svd-via-fast	Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares	1410.2596	http://arxiv.org/abs/1410.2596v1	http://arxiv.org/pdf/1410.2596v1.pdf	https://github.com/travisbrady/py-soft-impute	false	false	true	none
https://paperswithcode.com/paper/block-diffusion-interpolating-between	Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models	2503.09573	https://arxiv.org/abs/2503.09573v3	https://arxiv.org/pdf/2503.09573v3.pdf	https://github.com/MindSpore-scientific/code-12/tree/main/Block_Model	false	false	false	mindspore
https://paperswithcode.com/paper/a-simple-and-efficient-sampling-based	A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis	2112.05745	https://arxiv.org/abs/2112.05745v3	https://arxiv.org/pdf/2112.05745v3.pdf	https://github.com/stanfordasl/stochasticedl	false	false	true	jax
https://paperswithcode.com/paper/a-multi-head-model-for-continual-learning-via	A Multi-Head Model for Continual Learning via Out-of-Distribution Replay	2208.09734	https://arxiv.org/abs/2208.09734v1	https://arxiv.org/pdf/2208.09734v1.pdf	https://github.com/k-gyuhak/wptp	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/udacity/MLND-CN-Capstone-TGSImage	false	false	true	none
https://paperswithcode.com/paper/rethinking-atrous-convolution-for-semantic	Rethinking Atrous Convolution for Semantic Image Segmentation	1706.05587	http://arxiv.org/abs/1706.05587v3	http://arxiv.org/pdf/1706.05587v3.pdf	https://github.com/udacity/MLND-CN-Capstone-TGSImage	false	false	true	none
https://paperswithcode.com/paper/image-aesthetics-assessment-using-graph	Image Aesthetics Assessment Using Graph Attention Network	2206.12869	https://arxiv.org/abs/2206.12869v2	https://arxiv.org/pdf/2206.12869v2.pdf	https://github.com/koustav123/aesthetics_assessment_using_graphs	true	true	false	pytorch
https://paperswithcode.com/paper/rethinking-cnn-models-for-audio	Rethinking CNN Models for Audio Classification	2007.11154	https://arxiv.org/abs/2007.11154v2	https://arxiv.org/pdf/2007.11154v2.pdf	https://github.com/shijing001/unicertainty_calibration_audio_classifiers	false	false	true	pytorch
https://paperswithcode.com/paper/uncertainty-calibration-for-deep-audio	Uncertainty Calibration for Deep Audio Classifiers	2206.13071	https://arxiv.org/abs/2206.13071v1	https://arxiv.org/pdf/2206.13071v1.pdf	https://github.com/shijing001/unicertainty_calibration_audio_classifiers	true	true	true	pytorch
https://paperswithcode.com/paper/enhancing-stochastic-petri-net-based	Enhancing Stochastic Petri Net-based Remaining Time Prediction using k-Nearest Neighbors	2206.13109	https://arxiv.org/abs/2206.13109v1	https://arxiv.org/pdf/2206.13109v1.pdf	https://github.com/jarnevdb/bp-time-prediction-using-knn	true	true	false	none
https://paperswithcode.com/paper/190807919	Deep High-Resolution Representation Learning for Visual Recognition	1908.07919	https://arxiv.org/abs/1908.07919v2	https://arxiv.org/pdf/1908.07919v2.pdf	https://github.com/kingcong/gpu_HRNetW48_cls	false	false	true	mindspore
https://paperswithcode.com/paper/feature-overcorrelation-in-deep-graph-neural	Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective	2206.07743	https://arxiv.org/abs/2206.07743v1	https://arxiv.org/pdf/2206.07743v1.pdf	https://github.com/chandlerbang/decorr	true	true	true	pytorch
https://paperswithcode.com/paper/towards-overcoming-data-scarcity-in-materials	Towards overcoming data scarcity in materials science: unifying models and datasets with a mixture of experts framework	2207.13880	https://arxiv.org/abs/2207.13880v1	https://arxiv.org/pdf/2207.13880v1.pdf	https://github.com/rees-c/moe	true	true	false	pytorch
https://paperswithcode.com/paper/direct-preference-optimization-your-language	Direct Preference Optimization: Your Language Model is Secretly a Reward Model	2305.18290	https://arxiv.org/abs/2305.18290v3	https://arxiv.org/pdf/2305.18290v3.pdf	https://github.com/KomeijiForce/Active_Passive_Constraint_Koishiday_2024	false	false	true	pytorch
https://paperswithcode.com/paper/ego-planner-an-esdf-free-gradient-based-local	EGO-Planner: An ESDF-free Gradient-based Local Planner for Quadrotors	2008.08835	https://arxiv.org/abs/2008.08835v1	https://arxiv.org/pdf/2008.08835v1.pdf	https://github.com/j-marple-dev/ego-planner	false	false	true	none
https://paperswithcode.com/paper/learning-maritime-obstacle-detection-from	Learning Maritime Obstacle Detection from Weak Annotations by Scaffolding	2108.00564	https://arxiv.org/abs/2108.00564v1	https://arxiv.org/pdf/2108.00564v1.pdf	https://github.com/lojzezust/slr	false	false	true	pytorch
https://paperswithcode.com/paper/sparse-distillation-speeding-up-text	Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models	2110.08536	https://arxiv.org/abs/2110.08536v2	https://arxiv.org/pdf/2110.08536v2.pdf	https://github.com/ink-usc/sparse-distillation	true	true	true	pytorch
https://paperswithcode.com/paper/in-defense-of-the-triplet-loss-for-person-re	In Defense of the Triplet Loss for Person Re-Identification	1703.07737	http://arxiv.org/abs/1703.07737v4	http://arxiv.org/pdf/1703.07737v4.pdf	https://github.com/OML-Team/open-metric-learning	false	false	false	pytorch
https://paperswithcode.com/paper/non-gaussianity-in-cmb-lensing-from-full-sky	Non-Gaussianity in CMB lensing from full-sky simulations	2411.02774	https://arxiv.org/abs/2411.02774v3	https://arxiv.org/pdf/2411.02774v3.pdf	https://github.com/Kang-Yuqi/FLAReS	true	false	false	none
https://paperswithcode.com/paper/serendipity-in-dark-photon-searches	Serendipity in dark photon searches	1801.04847	https://arxiv.org/abs/1801.04847v2	https://arxiv.org/pdf/1801.04847v2.pdf	https://gitlab.com/philten/darkcast	true	true	true	none
https://paperswithcode.com/paper/transformcode-a-contrastive-learning	TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation	2311.08157	https://arxiv.org/abs/2311.08157v2	https://arxiv.org/pdf/2311.08157v2.pdf	https://github.com/iamfaith/transformcode	true	true	false	pytorch
https://paperswithcode.com/paper/technical-report-large-language-models-can	Large Language Models can Strategically Deceive their Users when Put Under Pressure	2311.07590	https://arxiv.org/abs/2311.07590v4	https://arxiv.org/pdf/2311.07590v4.pdf	https://github.com/apolloresearch/insider-trading	true	true	false	none
https://paperswithcode.com/paper/detecting-covariate-drift-in-text-data-using	Detecting covariate drift in text data using document embeddings and dimensionality reduction	2309.10000	https://arxiv.org/abs/2309.10000v1	https://arxiv.org/pdf/2309.10000v1.pdf	https://github.com/vinayaksodar/nlp_drift_paper_code	true	true	false	none
https://paperswithcode.com/paper/adaptive-measurement-strategy-for-quantum	Adaptive measurement strategy for quantum subspace methods	2311.07893	https://arxiv.org/abs/2311.07893v2	https://arxiv.org/pdf/2311.07893v2.pdf	https://github.com/quantum-programming/adaptive-subspace	true	false	false	none
https://paperswithcode.com/paper/coatnet-marrying-convolution-and-attention	CoAtNet: Marrying Convolution and Attention for All Data Sizes	2106.04803	https://arxiv.org/abs/2106.04803v2	https://arxiv.org/pdf/2106.04803v2.pdf	https://github.com/MS-Mind/MS-Code-02/tree/main/configs/coat	false	false	false	mindspore
https://paperswithcode.com/paper/a-study-of-slang-representation-methods	A Study of Slang Representation Methods	2212.05613	https://arxiv.org/abs/2212.05613v3	https://arxiv.org/pdf/2212.05613v3.pdf	https://github.com/usc-isi-i2/slang-representation-learning	true	false	false	pytorch
https://paperswithcode.com/paper/traffic-state-data-imputation-an-efficient	Traffic state data imputation: An efficient generating method based on the graph aggregator	null	https://ieeexplore.ieee.org/abstract/document/9582618	https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9582618	https://github.com/pihang/GA-GAN	true	false	false	none
https://paperswithcode.com/paper/ask2transformers-zero-shot-domain-labelling-1	Ask2Transformers: Zero-Shot Domain labelling with Pretrained Language Models	null	https://aclanthology.org/2021.gwc-1.6	https://aclanthology.org/2021.gwc-1.6.pdf	https://github.com/osainz59/Ask2Transformers	true	true	false	pytorch
https://paperswithcode.com/paper/a-field-test-of-bandit-algorithms-for	A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits	2304.09088	https://arxiv.org/abs/2304.09088v1	https://arxiv.org/pdf/2304.09088v1.pdf	https://github.com/humainlab/human-bandit-evaluation	true	true	false	none
https://paperswithcode.com/paper/probabilistic-embeddings-for-cross-modal	Probabilistic Embeddings for Cross-Modal Retrieval	2101.05068	https://arxiv.org/abs/2101.05068v2	https://arxiv.org/pdf/2101.05068v2.pdf	https://github.com/naver-ai/pcme	true	true	true	pytorch
https://paperswithcode.com/paper/computing-and-exploiting-document-structure	Computing and Exploiting Document Structure to Improve Unsupervised Extractive Summarization of Legal Case Decisions	2211.03229	https://arxiv.org/abs/2211.03229v1	https://arxiv.org/pdf/2211.03229v1.pdf	https://github.com/cs329yangzhong/documentstructurelegalsum	true	true	false	none
https://paperswithcode.com/paper/meta-networks	Meta Networks	1703.00837	http://arxiv.org/abs/1703.00837v2	http://arxiv.org/pdf/1703.00837v2.pdf	https://bitbucket.org/tsendeemts/metanet	true	true	true	none
https://paperswithcode.com/paper/model-predictive-control-of-nonlinear-latent	Model Predictive Control of Nonlinear Latent Force Models: A Scenario-Based Approach	2207.13872	https://arxiv.org/abs/2207.13872v1	https://arxiv.org/pdf/2207.13872v1.pdf	https://github.com/KU-ISSL/MPC-NLFM-Scenario-ICRA21	true	false	false	none
https://paperswithcode.com/paper/eccv-caption-correcting-false-negatives-by	ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO	2204.03359	https://arxiv.org/abs/2204.03359v5	https://arxiv.org/pdf/2204.03359v5.pdf	https://github.com/naver-ai/pcme	false	false	true	pytorch
https://paperswithcode.com/paper/4k-haze-a-dehazing-benchmark-with-4k	4K-HAZE: A Dehazing Benchmark with 4K Resolution Hazy and Haze-Free Images	2303.15848	https://arxiv.org/abs/2303.15848v1	https://arxiv.org/pdf/2303.15848v1.pdf	https://github.com/zzr-idam/4KDehazing	true	true	false	pytorch
https://paperswithcode.com/paper/foundationpose-unified-6d-pose-estimation-and	FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects	2312.08344	https://arxiv.org/abs/2312.08344v2	https://arxiv.org/pdf/2312.08344v2.pdf	https://github.com/NVlabs/FoundationStereo	true	false	false	pytorch
https://paperswithcode.com/paper/a-generative-approach-for-script-event-1	A Generative Approach for Script Event Prediction via Contrastive Fine-tuning	2212.03496	https://arxiv.org/abs/2212.03496v3	https://arxiv.org/pdf/2212.03496v3.pdf	https://github.com/zhufq00/mcnc	true	true	false	pytorch
https://paperswithcode.com/paper/bootstrap-state-representation-using-style	Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning	2207.07749	https://arxiv.org/abs/2207.07749v1	https://arxiv.org/pdf/2207.07749v1.pdf	https://github.com/masud99r/thinker	true	true	true	pytorch
https://paperswithcode.com/paper/dual-branch-hybrid-learning-network-for	Dual-branch Hybrid Learning Network for Unbiased Scene Graph Generation	2207.07913	https://arxiv.org/abs/2207.07913v1	https://arxiv.org/pdf/2207.07913v1.pdf	https://github.com/aa200647963/sgg-dhl	true	true	true	pytorch
https://paperswithcode.com/paper/facial-expression-and-attributes-recognition-1	Facial expression and attributes recognition based on multi-task learning of lightweight neural networks	2103.17107	https://arxiv.org/abs/2103.17107v3	https://arxiv.org/pdf/2103.17107v3.pdf	https://github.com/tomas-gajarsky/facetorch	false	false	false	pytorch
https://paperswithcode.com/paper/slowly-varying-regression-under-sparsity	Slowly Varying Regression under Sparsity	2102.10773	https://arxiv.org/abs/2102.10773v5	https://arxiv.org/pdf/2102.10773v5.pdf	https://github.com/vvdigalakis/ssvregression	true	true	false	none
https://paperswithcode.com/paper/one-person-one-model-learning-compound-router	One Person, One Model--Learning Compound Router for Sequential Recommendation	2211.02824	https://arxiv.org/abs/2211.02824v2	https://arxiv.org/pdf/2211.02824v2.pdf	https://github.com/icantnamemyself/canet	true	true	false	pytorch
https://paperswithcode.com/paper/networked-federated-multi-task-learning	Clustered Federated Learning via Generalized Total Variation Minimization	2105.12769	https://arxiv.org/abs/2105.12769v4	https://arxiv.org/pdf/2105.12769v4.pdf	https://github.com/sahelyiyi/FederatedLearning	true	true	true	pytorch
https://paperswithcode.com/paper/improving-federated-learning-personalization-1	Improving Federated Learning Personalization via Model Agnostic Meta Learning	1909.12488	https://arxiv.org/abs/1909.12488v2	https://arxiv.org/pdf/1909.12488v2.pdf	https://github.com/xiuyu0000/new_papers_codes/tree/main/FSMAFL	false	false	false	mindspore
https://paperswithcode.com/paper/preconditioned-nonlinear-conjugate-gradient-2	Preconditioned Nonlinear Conjugate Gradient Method for Real-time Interior-point Hyperelasticity	2405.08001	https://arxiv.org/abs/2405.08001v1	https://arxiv.org/pdf/2405.08001v1.pdf	https://github.com/Xingbaji/PNCG_IPC	true	false	false	none
https://paperswithcode.com/paper/mfan-multi-modal-feature-enhanced-attention	MFAN: Multi-modal Feature-enhanced Attention Networks for Rumor Detection	null	https://www.ijcai.org/proceedings/2022/335	https://www.ijcai.org/proceedings/2022/0335.pdf	https://github.com/drivsaf/MFAN	false	false	false	pytorch
https://paperswithcode.com/paper/bit-depth-enhancement-detection-for	Bit-depth enhancement detection for compressed video	2211.04799	https://arxiv.org/abs/2211.04799v1	https://arxiv.org/pdf/2211.04799v1.pdf	https://github.com/msu-video-group/bdedm	true	true	false	none
https://paperswithcode.com/paper/a-hierarchical-semantic-segmentation	A hierarchical semantic segmentation framework for computer vision-based bridge damage detection	2207.08878	https://arxiv.org/abs/2207.08878v2	https://arxiv.org/pdf/2207.08878v2.pdf	https://github.com/jingxiaoliu/bridge-damage-segmentation	true	true	true	pytorch
https://paperswithcode.com/paper/kold-korean-offensive-language-dataset	KOLD: Korean Offensive Language Dataset	2205.11315	https://arxiv.org/abs/2205.11315v2	https://arxiv.org/pdf/2205.11315v2.pdf	https://github.com/boychaboy/kold	true	true	true	none
https://paperswithcode.com/paper/wenet-2-0-more-productive-end-to-end-speech	WeNet 2.0: More Productive End-to-End Speech Recognition Toolkit	2203.15455	https://arxiv.org/abs/2203.15455v2	https://arxiv.org/pdf/2203.15455v2.pdf	https://github.com/wenet-e2e/wenet	true	true	true	pytorch
https://paperswithcode.com/paper/interpretable-semantic-photo-geolocalization	Interpretable Semantic Photo Geolocation	2104.14995	https://arxiv.org/abs/2104.14995v2	https://arxiv.org/pdf/2104.14995v2.pdf	https://github.com/jtheiner/semantic_geo_partitioning	true	true	true	pytorch
https://paperswithcode.com/paper/high-resolution-image-synthesis-with-latent	High-Resolution Image Synthesis with Latent Diffusion Models	2112.10752	https://arxiv.org/abs/2112.10752v2	https://arxiv.org/pdf/2112.10752v2.pdf	https://github.com/joanrod/ocr-vqgan	false	false	true	pytorch
https://paperswithcode.com/paper/taming-transformers-for-high-resolution-image	Taming Transformers for High-Resolution Image Synthesis	2012.09841	https://arxiv.org/abs/2012.09841v3	https://arxiv.org/pdf/2012.09841v3.pdf	https://github.com/joanrod/ocr-vqgan	false	false	true	pytorch
https://paperswithcode.com/paper/character-region-awareness-for-text-detection	Character Region Awareness for Text Detection	1904.01941	http://arxiv.org/abs/1904.01941v1	http://arxiv.org/pdf/1904.01941v1.pdf	https://github.com/joanrod/ocr-vqgan	false	false	true	pytorch
https://paperswithcode.com/paper/cryptanalyzing-an-image-encryption-algorithm-1	Cryptanalyzing an Image Encryption Algorithm Underpinned by 2D Lag-Complex Logistic Map	2208.06774	https://arxiv.org/abs/2208.06774v1	https://arxiv.org/pdf/2208.06774v1.pdf	https://github.com/chengqingli/mm-iealm	true	true	false	none
https://paperswithcode.com/paper/rethinking-image-mixture-for-unsupervised	Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning	2003.05438	https://arxiv.org/abs/2003.05438v5	https://arxiv.org/pdf/2003.05438v5.pdf	https://github.com/szq0214/Rethinking-Image-Mixture-for-Unsupervised-Learning	true	true	true	pytorch
https://paperswithcode.com/paper/tristereonet-a-trinocular-framework-for-multi	TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation	2111.12502	https://arxiv.org/abs/2111.12502v2	https://arxiv.org/pdf/2111.12502v2.pdf	https://github.com/cogsys-tuebingen/tristereonet	true	true	true	pytorch
https://paperswithcode.com/paper/mid-fusion-octree-based-object-level-multi	MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM	1812.07976	http://arxiv.org/abs/1812.07976v4	http://arxiv.org/pdf/1812.07976v4.pdf	https://github.com/smartroboticslab/mid-fusion	true	false	true	tf
https://paperswithcode.com/paper/deep-graph-library-towards-efficient-and	Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks	1909.01315	https://arxiv.org/abs/1909.01315v2	https://arxiv.org/pdf/1909.01315v2.pdf	https://github.com/OweysMomenzada/Graph-Neural-Networks-for-effecient-Recommender-Systems	false	false	true	pytorch
https://paperswithcode.com/paper/self-guided-contrastive-learning-for-bert	Self-Guided Contrastive Learning for BERT Sentence Representations	2106.07345	https://arxiv.org/abs/2106.07345v1	https://arxiv.org/pdf/2106.07345v1.pdf	https://github.com/galsang/SG-BERT	true	true	false	pytorch
https://paperswithcode.com/paper/xnor-net-imagenet-classification-using-binary	XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks	1603.05279	http://arxiv.org/abs/1603.05279v4	http://arxiv.org/pdf/1603.05279v4.pdf	https://github.com/pminhtam/xnor_conv_pytorch_extension	false	false	false	pytorch
https://paperswithcode.com/paper/fleet-policy-learning-via-weight-merging-and	Robot Fleet Learning via Policy Merging	2310.01362	https://arxiv.org/abs/2310.01362v3	https://arxiv.org/pdf/2310.01362v3.pdf	https://github.com/liruiw/fleet-tools	true	true	true	none
https://paperswithcode.com/paper/multiclass-sgcn-sparse-graph-based-trajectory	Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding	2206.15275	https://arxiv.org/abs/2206.15275v1	https://arxiv.org/pdf/2206.15275v1.pdf	https://github.com/carrotsniper/multiclass-sgcn	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.