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/edtc-a-corpus-for-discourse-level-topic-chain	EDTC: A Corpus for Discourse-Level Topic Chain Parsing	null	https://aclanthology.org/2021.findings-emnlp.113	https://aclanthology.org/2021.findings-emnlp.113.pdf	https://github.com/nlp-discourse-soochowu/dtcp	true	true	false	pytorch
https://paperswithcode.com/paper/writing-style-author-embedding-evaluation	Writing Style Author Embedding Evaluation	null	https://aclanthology.org/2021.eval4nlp-1.9	https://aclanthology.org/2021.eval4nlp-1.9.pdf	https://github.com/enzofleur/style_embedding_evaluation	true	true	false	none
https://paperswithcode.com/paper/countering-the-influence-of-essay-length-in	Countering the Influence of Essay Length in Neural Essay Scoring	null	https://aclanthology.org/2021.sustainlp-1.4	https://aclanthology.org/2021.sustainlp-1.4.pdf	https://github.com/sdeva14/sustai21-counter-neural-essay-length	true	true	false	pytorch
https://paperswithcode.com/paper/unsupervised-monocular-depth-estimation-with	Unsupervised Monocular Depth Estimation with Left-Right Consistency	1609.03677	http://arxiv.org/abs/1609.03677v3	http://arxiv.org/pdf/1609.03677v3.pdf	https://github.com/xown3197/3D_Pedestrian_Localization_2021ComputerVision	false	false	true	pytorch
https://paperswithcode.com/paper/unsupervised-monocular-depth-learning-in	Unsupervised Monocular Depth Learning in Dynamic Scenes	2010.16404	https://arxiv.org/abs/2010.16404v2	https://arxiv.org/pdf/2010.16404v2.pdf	https://github.com/CarloRadice/depth-and-motion-learning	false	false	true	tf
https://paperswithcode.com/paper/smells-in-system-user-interactive-tests	Smells in System User Interactive Tests	2111.02317	https://arxiv.org/abs/2111.02317v1	https://arxiv.org/pdf/2111.02317v1.pdf	https://github.com/kabinja/suit-smells-replication-package	true	true	false	none
https://paperswithcode.com/paper/improving-sequence-to-sequence-semantic	Improving Sequence-to-Sequence Semantic Parser for Task Oriented Dialog	null	https://aclanthology.org/2020.intexsempar-1.3	https://aclanthology.org/2020.intexsempar-1.3.pdf	https://github.com/cxuan2019/top	true	true	false	pytorch
https://paperswithcode.com/paper/offensive-language-detection-in-nepali-social	Offensive Language Detection in Nepali Social Media	null	https://aclanthology.org/2021.woah-1.7	https://aclanthology.org/2021.woah-1.7.pdf	https://github.com/nowalab/offensive-nepali	true	true	false	none
https://paperswithcode.com/paper/bert4rec-sequential-recommendation-with	BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer	1904.06690	https://arxiv.org/abs/1904.06690v2	https://arxiv.org/pdf/1904.06690v2.pdf	https://github.com/vatsalsaglani/bert4rec	false	false	false	pytorch
https://paperswithcode.com/paper/dual-attention-networks-for-multimodal	Dual Attention Networks for Multimodal Reasoning and Matching	1611.00471	http://arxiv.org/abs/1611.00471v2	http://arxiv.org/pdf/1611.00471v2.pdf	https://github.com/iammrhelo/pytorch-vqa-dan	false	false	true	pytorch
https://paperswithcode.com/paper/cnn-architectures-for-large-scale-audio	CNN Architectures for Large-Scale Audio Classification	1609.09430	http://arxiv.org/abs/1609.09430v2	http://arxiv.org/pdf/1609.09430v2.pdf	https://github.com/stanfordmlgroup/aihc-sum20-lung-sounds	false	false	true	pytorch
https://paperswithcode.com/paper/spread2rml-constructing-knowledge-graphs-by	Spread2RML: Constructing Knowledge Graphs by Predicting RML Mappings on Messy Spreadsheets	2110.12829	https://arxiv.org/abs/2110.12829v1	https://arxiv.org/pdf/2110.12829v1.pdf	https://github.com/mschroeder-github/spread2rml	true	false	false	none
https://paperswithcode.com/paper/polyhedral-mesh-quality-indicator-for-the	Polyhedral Mesh Quality Indicator for the Virtual Element Method	2112.11365	https://arxiv.org/abs/2112.11365v1	https://arxiv.org/pdf/2112.11365v1.pdf	https://github.com/tommasosorgente/vem-indicator-3d-dataset	true	true	false	none
https://paperswithcode.com/paper/on-the-fly-category-discovery	On-the-Fly Category Discovery	null	http://openaccess.thecvf.com//content/CVPR2023/html/Du_On-the-Fly_Category_Discovery_CVPR_2023_paper.html	http://openaccess.thecvf.com//content/CVPR2023/papers/Du_On-the-Fly_Category_Discovery_CVPR_2023_paper.pdf	https://github.com/pris-cv/on-the-fly-category-discovery	true	true	false	pytorch
https://paperswithcode.com/paper/a-graph-neural-network-based-approach-for	Identifying Possible Rumor Spreaders on Twitter: A Weak Supervised Learning Approach	2010.07647	https://arxiv.org/abs/2010.07647v2	https://arxiv.org/pdf/2010.07647v2.pdf	https://github.com/shakshi12/Rumor-Spreaders-using-GNN-approach-PHEME-dataset-	false	false	true	tf
https://paperswithcode.com/paper/non-intrusive-binaural-speech-intelligibility	Non-Intrusive Binaural Speech Intelligibility Prediction from Discrete Latent Representations	2111.12531	https://arxiv.org/abs/2111.12531v2	https://arxiv.org/pdf/2111.12531v2.pdf	https://github.com/vvvm23/stoi-vqcpc	true	true	true	pytorch
https://paperswithcode.com/paper/revisiting-graph-neural-networks-all-we-have	Revisiting Graph Neural Networks: All We Have is Low-Pass Filters	1905.09550	https://arxiv.org/abs/1905.09550v2	https://arxiv.org/pdf/1905.09550v2.pdf	https://github.com/hazdzz/gfNN	false	false	true	pytorch
https://paperswithcode.com/paper/mesoscopic-insights-orchestrating-multi-scale	Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localization	2412.13753	https://arxiv.org/abs/2412.13753v1	https://arxiv.org/pdf/2412.13753v1.pdf	https://github.com/scu-zjz/Mesorch	true	true	true	pytorch
https://paperswithcode.com/paper/multi-behavior-self-supervised-learning-for	Multi-behavior Self-supervised Learning for Recommendation	2305.18238	https://arxiv.org/abs/2305.18238v1	https://arxiv.org/pdf/2305.18238v1.pdf	https://github.com/scofield666/mbssl	true	true	false	pytorch
https://paperswithcode.com/paper/a-great-model-comparison-against-the	A GREAT model comparison against the cosmological constant	2111.13083	https://arxiv.org/abs/2111.13083v2	https://arxiv.org/pdf/2111.13083v2.pdf	https://github.com/snesseris/great-project	true	true	false	none
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	1810.04805	https://arxiv.org/abs/1810.04805v2	https://arxiv.org/pdf/1810.04805v2.pdf	https://github.com/geondopark/ckd	false	false	true	pytorch
https://paperswithcode.com/paper/texttt-py-irt-a-scalable-item-response-theory	py-irt: A Scalable Item Response Theory Library for Python	2203.01282	https://arxiv.org/abs/2203.01282v2	https://arxiv.org/pdf/2203.01282v2.pdf	https://github.com/nd-ball/py-irt	true	true	false	pytorch
https://paperswithcode.com/paper/deep-predictive-coding-networks-for-video	Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning	1605.08104	http://arxiv.org/abs/1605.08104v5	http://arxiv.org/pdf/1605.08104v5.pdf	https://github.com/Mikkil5112/PredNet	false	false	true	tf
https://paperswithcode.com/paper/active-machine-learning-for-spatio-temporal	Enhanced spatio-temporal electric load forecasts using less data with active deep learning	2012.04407	https://arxiv.org/abs/2012.04407v2	https://arxiv.org/pdf/2012.04407v2.pdf	https://github.com/ArsamAryandoust/DataSelectionMaps	true	true	true	tf
https://paperswithcode.com/paper/video-action-classification-using-prednet	PredNet and Predictive Coding: A Critical Review	1906.11902	https://arxiv.org/abs/1906.11902v3	https://arxiv.org/pdf/1906.11902v3.pdf	https://github.com/Mikkil5112/PredNet	false	false	true	tf
https://paperswithcode.com/paper/an-end-to-end-trainable-neural-network-for	An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition	1507.05717	http://arxiv.org/abs/1507.05717v1	http://arxiv.org/pdf/1507.05717v1.pdf	https://github.com/chandan5362/Indian-Number-Plate-Recognition	false	false	true	none
https://paperswithcode.com/paper/discodisco-at-the-disrpt2021-shared-task-a	DisCoDisCo at the DISRPT2021 Shared Task: A System for Discourse Segmentation, Classification, and Connective Detection	2109.09777	https://arxiv.org/abs/2109.09777v1	https://arxiv.org/pdf/2109.09777v1.pdf	https://github.com/gucorpling/discodisco	true	true	true	pytorch
https://paperswithcode.com/paper/nafs-a-simple-yet-tough-to-beat-baseline-for-1	NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning	2206.08583	https://arxiv.org/abs/2206.08583v1	https://arxiv.org/pdf/2206.08583v1.pdf	https://github.com/zwt233/NAFS	true	false	false	pytorch
https://paperswithcode.com/paper/k-2-ie-kernel-method-based-kernel-intensity	K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes	2505.24704	https://arxiv.org/abs/2505.24704v1	https://arxiv.org/pdf/2505.24704v1.pdf	https://github.com/hidkim/k2ie	true	true	false	tf
https://paperswithcode.com/paper/multilingual-controllable-transformer-based	Multilingual Controllable Transformer-Based Lexical Simplification	2307.02120	https://arxiv.org/abs/2307.02120v1	https://arxiv.org/pdf/2307.02120v1.pdf	https://github.com/kimchengsheang/mtls	true	true	false	pytorch
https://paperswithcode.com/paper/strong-instance-segmentation-pipeline-for	Strong Instance Segmentation Pipeline for MMSports Challenge	2209.13899	https://arxiv.org/abs/2209.13899v1	https://arxiv.org/pdf/2209.13899v1.pdf	https://github.com/yjingyu/instanc_segmentation_pro	true	true	true	pytorch
https://paperswithcode.com/paper/a-decentralized-framework-for-kernel-pca-with	A Decentralized Framework for Kernel PCA with Projection Consensus Constraints	2211.15953	https://arxiv.org/abs/2211.15953v1	https://arxiv.org/pdf/2211.15953v1.pdf	https://github.com/yruikk/dkpca-admm	true	true	true	none
https://paperswithcode.com/paper/open-domain-hierarchical-event-schema	Open-Domain Hierarchical Event Schema Induction by Incremental Prompting and Verification	2307.01972	https://arxiv.org/abs/2307.01972v1	https://arxiv.org/pdf/2307.01972v1.pdf	https://github.com/raspberryice/inc-schema	true	true	false	none
https://paperswithcode.com/paper/reverse-image-filtering-using-total	Reverse image filtering using total derivative approximation and accelerated gradient descent	2112.04121	https://arxiv.org/abs/2112.04121v3	https://arxiv.org/pdf/2112.04121v3.pdf	https://github.com/fergaletto/ReverseFilter_TDA	true	false	true	none
https://paperswithcode.com/paper/mipi-2022-challenge-on-rgb-tof-depth	MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and Report	2209.07057	https://arxiv.org/abs/2209.07057v1	https://arxiv.org/pdf/2209.07057v1.pdf	https://github.com/mipi-challenge/mipi2022	true	true	true	none
https://paperswithcode.com/paper/mipi-2022-challenge-on-rgbw-sensor-re-mosaic	MIPI 2022 Challenge on RGBW Sensor Re-mosaic: Dataset and Report	2209.08471	https://arxiv.org/abs/2209.08471v1	https://arxiv.org/pdf/2209.08471v1.pdf	https://github.com/mipi-challenge/mipi2022	true	true	true	none
https://paperswithcode.com/paper/mipi-2022-challenge-on-rgbw-sensor-fusion	MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report	2209.07530	https://arxiv.org/abs/2209.07530v2	https://arxiv.org/pdf/2209.07530v2.pdf	https://github.com/mipi-challenge/mipi2022	true	true	true	none
https://paperswithcode.com/paper/cmua-watermark-a-cross-model-universal	CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes	2105.10872	https://arxiv.org/abs/2105.10872v2	https://arxiv.org/pdf/2105.10872v2.pdf	https://github.com/vdigpku/cmua-watermark	true	true	true	pytorch
https://paperswithcode.com/paper/measuring-fairness-with-biased-rulers-a	Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models	2112.07447	https://arxiv.org/abs/2112.07447v1	https://arxiv.org/pdf/2112.07447v1.pdf	https://github.com/ipieter/biased-rulers	true	true	false	pytorch
https://paperswithcode.com/paper/investigation-of-the-dead-time-duration-and	Dead time duration and active reset influence on the afterpulse probability of InGaAs/InP single-photon avalanche diodes	2104.03919	https://arxiv.org/abs/2104.03919v4	https://arxiv.org/pdf/2104.03919v4.pdf	https://github.com/akoziy98/Automated_Stand	false	false	true	none
https://paperswithcode.com/paper/emnist-an-extension-of-mnist-to-handwritten	EMNIST: an extension of MNIST to handwritten letters	1702.05373	http://arxiv.org/abs/1702.05373v2	http://arxiv.org/pdf/1702.05373v2.pdf	https://github.com/chuiyunjun/projectCSC413	false	false	true	none
https://paperswithcode.com/paper/a-variance-reduced-and-stabilized-proximal	A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization	2302.06790	https://arxiv.org/abs/2302.06790v1	https://arxiv.org/pdf/2302.06790v1.pdf	https://github.com/yutong-dai/s-pstorm	true	true	false	none
https://paperswithcode.com/paper/automatic-evaluation-and-moderation-of-open	Automatic Evaluation and Moderation of Open-domain Dialogue Systems	2111.02110	https://arxiv.org/abs/2111.02110v3	https://arxiv.org/pdf/2111.02110v3.pdf	https://github.com/lfdharo/DSTC10_Track5_Toxicity	true	true	false	pytorch
https://paperswithcode.com/paper/automated-grading-of-radiographic-knee	Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance	2203.08914	https://arxiv.org/abs/2203.08914v2	https://arxiv.org/pdf/2203.08914v2.pdf	https://github.com/maciejmazurowski/osteoarthritis-classification	true	true	true	pytorch
https://paperswithcode.com/paper/investigation-of-the-dependence-of-noise	Investigation of the dependence of noise characteristics of SPAD on the gate parameters in sine-wave gated single-photon detectors	2103.07363	https://arxiv.org/abs/2103.07363v3	https://arxiv.org/pdf/2103.07363v3.pdf	https://github.com/akoziy98/Automated_Stand	false	false	true	none
https://paperswithcode.com/paper/investigating-the-coherent-state-detection	Investigating the coherent state detection probability of InGaAs/InP SPAD-based single-photon detectors	2104.07952	https://arxiv.org/abs/2104.07952v1	https://arxiv.org/pdf/2104.07952v1.pdf	https://github.com/akoziy98/Automated_Stand	false	false	true	none
https://paperswithcode.com/paper/tensor-renormalization-of-three-dimensional	Tensor renormalization of three-dimensional Potts model	2201.01789	https://arxiv.org/abs/2201.01789v1	https://arxiv.org/pdf/2201.01789v1.pdf	https://github.com/rgjha/TensorCodes	true	true	false	pytorch
https://paperswithcode.com/paper/neural-discrete-representation-learning	Neural Discrete Representation Learning	1711.00937	http://arxiv.org/abs/1711.00937v2	http://arxiv.org/pdf/1711.00937v2.pdf	https://github.com/yhy258/VariationalAutoEncoders-Pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/kaggledbqa-realistic-evaluation-of-text-to	KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers	2106.11455	https://arxiv.org/abs/2106.11455v1	https://arxiv.org/pdf/2106.11455v1.pdf	https://github.com/chiahsuan156/KaggleDBQA	true	false	false	none
https://paperswithcode.com/paper/joint-entropy-search-for-maximally-informed	Joint Entropy Search for Maximally-Informed Bayesian Optimization	2206.04771	https://arxiv.org/abs/2206.04771v5	https://arxiv.org/pdf/2206.04771v5.pdf	https://github.com/jointentropysearch/jointentropysearch	true	true	false	none
https://paperswithcode.com/paper/signal-strength-and-noise-drive-feature-1	Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers	2201.08893	https://arxiv.org/abs/2201.08893v1	https://arxiv.org/pdf/2201.08893v1.pdf	https://github.com/mwolff31/signal_preference	true	true	false	pytorch
https://paperswithcode.com/paper/a-parallel-corpus-of-python-functions-and	A parallel corpus of Python functions and documentation strings for automated code documentation and code generation	1707.02275	http://arxiv.org/abs/1707.02275v1	http://arxiv.org/pdf/1707.02275v1.pdf	https://github.com/ICSEG/M2TS	false	false	true	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/ICSEG/M2TS	false	false	true	pytorch
https://paperswithcode.com/paper/squeeze-and-excitation-networks	Squeeze-and-Excitation Networks	1709.01507	https://arxiv.org/abs/1709.01507v4	https://arxiv.org/pdf/1709.01507v4.pdf	https://github.com/mehrdad-noori/brain-tumor-segmentation	false	false	true	tf
https://paperswithcode.com/paper/low-rank-constraints-for-fast-inference-in-1	Low-Rank Constraints for Fast Inference in Structured Models	2201.02715	https://arxiv.org/abs/2201.02715v1	https://arxiv.org/pdf/2201.02715v1.pdf	https://github.com/justinchiu/low-rank-models	true	true	false	pytorch
https://paperswithcode.com/paper/spikecv-open-a-continuous-computer-vision-era	SpikeCV: Open a Continuous Computer Vision Era	2303.11684	https://arxiv.org/abs/2303.11684v2	https://arxiv.org/pdf/2303.11684v2.pdf	https://github.com/zyj061/spikecv	true	true	false	pytorch
https://paperswithcode.com/paper/dissipativity-based-decentralized-co-design	Dissipativity-Based Decentralized Co-Design of Distributed Controllers and Communication Topologies for Vehicular Platoons	2312.06472	https://arxiv.org/abs/2312.06472v2	https://arxiv.org/pdf/2312.06472v2.pdf	https://github.com/ndzsong2/longitudinal-vehicular-platoon-simulator	true	true	false	none
https://paperswithcode.com/paper/online-multi-object-tracking-framework-with	Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management	1907.13347	https://arxiv.org/abs/1907.13347v1	https://arxiv.org/pdf/1907.13347v1.pdf	https://github.com/SonginCV/GMPHD-OGM_Tracker	true	false	true	none
https://paperswithcode.com/paper/boost-and-skip-a-simple-guidance-free	Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation	2502.06516	https://arxiv.org/abs/2502.06516v2	https://arxiv.org/pdf/2502.06516v2.pdf	https://github.com/soobin-um/bns	true	true	false	pytorch
https://paperswithcode.com/paper/projection-of-functionals-and-fast-pricing-of	Projection of Functionals and Fast Pricing of Exotic Options	2111.03713	https://arxiv.org/abs/2111.03713v3	https://arxiv.org/pdf/2111.03713v3.pdf	https://github.com/valentintissot/klmc	true	true	true	none
https://paperswithcode.com/paper/parallel-longest-common-subsequence-analysis	Parallel Longest Common SubSequence Analysis In Chapel	2309.09072	https://arxiv.org/abs/2309.09072v1	https://arxiv.org/pdf/2309.09072v1.pdf	https://github.com/soroushvahidi/parallel-longest-common-subsequence	true	true	false	none
https://paperswithcode.com/paper/sum-a-benchmark-dataset-of-semantic-urban	SUM: A Benchmark Dataset of Semantic Urban Meshes	2103.00355	https://arxiv.org/abs/2103.00355v2	https://arxiv.org/pdf/2103.00355v2.pdf	https://github.com/tudelft3d/SUMS-Semantic-Urban-Mesh-Segmentation-public	true	false	false	none
https://paperswithcode.com/paper/pvg-at-wassa-2021-a-multi-input-multi-task	PVG at WASSA 2021: A Multi-Input, Multi-Task, Transformer-Based Architecture for Empathy and Distress Prediction	2103.03296	https://arxiv.org/abs/2103.03296v1	https://arxiv.org/pdf/2103.03296v1.pdf	https://github.com/mr-atharva-kulkarni/EACL-WASSA-2021-Empathy-Distress	true	false	false	tf
https://paperswithcode.com/paper/cocon-a-data-set-on-combined-contextualized	CoCon: A Data Set on Combined Contextualized Research Artifact Use	2303.15193	https://arxiv.org/abs/2303.15193v1	https://arxiv.org/pdf/2303.15193v1.pdf	https://github.com/illdepence/contextgraph	true	true	false	pytorch
https://paperswithcode.com/paper/deep-generative-framework-for-interactive-3d	Deep Generative Framework for Interactive 3D Terrain Authoring and Manipulation	2201.02369	https://arxiv.org/abs/2201.02369v1	https://arxiv.org/pdf/2201.02369v1.pdf	https://github.com/Shanthika/TerrainAuthoring-Pytorch	true	false	true	pytorch
https://paperswithcode.com/paper/scaled-yolov4-scaling-cross-stage-partial	Scaled-YOLOv4: Scaling Cross Stage Partial Network	2011.08036	https://arxiv.org/abs/2011.08036v2	https://arxiv.org/pdf/2011.08036v2.pdf	https://github.com/xyuan-wyze/darknet	false	false	true	tf
https://paperswithcode.com/paper/cspnet-a-new-backbone-that-can-enhance	CSPNet: A New Backbone that can Enhance Learning Capability of CNN	1911.11929	https://arxiv.org/abs/1911.11929v1	https://arxiv.org/pdf/1911.11929v1.pdf	https://github.com/xyuan-wyze/darknet	false	false	true	tf
https://paperswithcode.com/paper/yolov3-an-incremental-improvement	YOLOv3: An Incremental Improvement	1804.02767	http://arxiv.org/abs/1804.02767v1	http://arxiv.org/pdf/1804.02767v1.pdf	https://github.com/xyuan-wyze/darknet	false	false	true	tf
https://paperswithcode.com/paper/neural-ocr-post-hoc-correction-of-historical	Neural OCR Post-Hoc Correction of Historical Corpora	2102.00583	https://arxiv.org/abs/2102.00583v1	https://arxiv.org/pdf/2102.00583v1.pdf	https://github.com/GarfieldLyu/OCR_POST_DE	true	true	true	pytorch
https://paperswithcode.com/paper/yolov4-optimal-speed-and-accuracy-of-object	YOLOv4: Optimal Speed and Accuracy of Object Detection	2004.10934	https://arxiv.org/abs/2004.10934v1	https://arxiv.org/pdf/2004.10934v1.pdf	https://github.com/xyuan-wyze/darknet	false	false	true	tf
https://paperswithcode.com/paper/detect-influential-points-of-feature-rankings	Detect influential points of feature rankings	2303.10516	https://arxiv.org/abs/2303.10516v1	https://arxiv.org/pdf/2303.10516v1.pdf	https://github.com/shuostat/ips_on_feature_rankings	true	true	false	none
https://paperswithcode.com/paper/probing-pre-trained-language-models-for-cross	Probing Pre-Trained Language Models for Cross-Cultural Differences in Values	2203.13722	https://arxiv.org/abs/2203.13722v2	https://arxiv.org/pdf/2203.13722v2.pdf	https://github.com/copenlu/value-probing	true	true	false	none
https://paperswithcode.com/paper/deep-graph-neural-networks-with-shallow-1	Deep Graph Neural Networks with Shallow Subgraph Samplers	2012.01380	https://arxiv.org/abs/2012.01380v3	https://arxiv.org/pdf/2012.01380v3.pdf	https://github.com/facebookresearch/shaDow_GNN	true	false	true	pytorch
https://paperswithcode.com/paper/vector-based-data-improves-left-right-eye	Vector-Based Data Improves Left-Right Eye-Tracking Classifier Performance After a Covariate Distributional Shift	2208.00465	https://arxiv.org/abs/2208.00465v1	https://arxiv.org/pdf/2208.00465v1.pdf	https://github.com/brianxiang123/eegetcovariatedistributionalshift	true	true	false	none
https://paperswithcode.com/paper/a-state-distribution-matching-approach-to-non	A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning	2205.05212	https://arxiv.org/abs/2205.05212v1	https://arxiv.org/pdf/2205.05212v1.pdf	https://github.com/architsharma97/medal	true	false	false	pytorch
https://paperswithcode.com/paper/deep-learning-through-the-lens-of-example	Deep Learning Through the Lens of Example Difficulty	2106.09647	https://arxiv.org/abs/2106.09647v2	https://arxiv.org/pdf/2106.09647v2.pdf	https://github.com/pengbohua/AngularGap/tree/12dad1ec18d3c15a41835c3c342f82051d895ccc/standard_curriculum_learning/prediction_depth	false	false	false	pytorch
https://paperswithcode.com/paper/end-to-end-learning-for-self-driving-cars	End to End Learning for Self-Driving Cars	1604.07316	http://arxiv.org/abs/1604.07316v1	http://arxiv.org/pdf/1604.07316v1.pdf	https://github.com/drtupe/Behavioral_Cloning	false	false	true	tf
https://paperswithcode.com/paper/collective-explainable-ai-explaining	Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values	2110.01307	https://arxiv.org/abs/2110.01307v1	https://arxiv.org/pdf/2110.01307v1.pdf	https://github.com/fabien-couthouis/xai-in-rl	true	true	true	none
https://paperswithcode.com/paper/a-multi-agent-reinforcement-learning-model-of	A multi-agent reinforcement learning model of common-pool resource appropriation	1707.06600	http://arxiv.org/abs/1707.06600v2	http://arxiv.org/pdf/1707.06600v2.pdf	https://github.com/fabien-couthouis/xai-in-rl	false	false	true	none
https://paperswithcode.com/paper/msccl-microsoft-collective-communication	GC3: An Optimizing Compiler for GPU Collective Communication	2201.11840	https://arxiv.org/abs/2201.11840v3	https://arxiv.org/pdf/2201.11840v3.pdf	https://github.com/microsoft/msccl-tools	true	true	true	pytorch
https://paperswithcode.com/paper/llama-open-and-efficient-foundation-language-1	LLaMA: Open and Efficient Foundation Language Models	2302.13971	https://arxiv.org/abs/2302.13971v1	https://arxiv.org/pdf/2302.13971v1.pdf	https://github.com/xiaoman-zhang/PMC-VQA	false	false	true	pytorch
https://paperswithcode.com/paper/a-cooperation-graph-approach-for-multiagent	A Cooperation Graph Approach for Multiagent Sparse Reward Reinforcement Learning	2208.03002	https://arxiv.org/abs/2208.03002v1	https://arxiv.org/pdf/2208.03002v1.pdf	https://github.com/binary-husky/hmp2g	true	true	false	pytorch
https://paperswithcode.com/paper/metrics-quantization-and-registration-in	Metrics, quantization and registration in varifold spaces	1903.11196	https://arxiv.org/abs/1903.11196v1	https://arxiv.org/pdf/1903.11196v1.pdf	https://github.com/charoncode/Var_LDDMM	true	false	true	none
https://paperswithcode.com/paper/mastering-visual-continuous-control-improved	Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning	2107.09645	https://arxiv.org/abs/2107.09645v1	https://arxiv.org/pdf/2107.09645v1.pdf	https://github.com/architsharma97/medal	false	false	true	pytorch
https://paperswithcode.com/paper/generative-modeling-with-optimal-transport	Generative Modeling with Optimal Transport Maps	2110.02999	https://arxiv.org/abs/2110.02999v2	https://arxiv.org/pdf/2110.02999v2.pdf	https://github.com/LituRout/OptimalTransportModeling	true	false	false	pytorch
https://paperswithcode.com/paper/structural-temporal-graph-neural-networks-for	Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs	2005.07427	https://arxiv.org/abs/2005.07427v2	https://arxiv.org/pdf/2005.07427v2.pdf	https://github.com/KnowledgeDiscovery/StrGNN	true	false	false	pytorch
https://paperswithcode.com/paper/predrnn-towards-a-resolution-of-the-deep-in	PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning	1804.06300	http://arxiv.org/abs/1804.06300v2	http://arxiv.org/pdf/1804.06300v2.pdf	https://github.com/mindspore-ai/models/tree/master/official/cv/predrnn%2B%2B	false	false	false	mindspore
https://paperswithcode.com/paper/comparison-of-spatio-temporal-models-for	Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios	2203.03245	https://arxiv.org/abs/2203.03245v1	https://arxiv.org/pdf/2203.03245v1.pdf	https://github.com/crisie/udiva	true	true	false	none
https://paperswithcode.com/paper/dynamic-mlp-for-fine-grained-image	Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information	2203.03253	https://arxiv.org/abs/2203.03253v1	https://arxiv.org/pdf/2203.03253v1.pdf	https://github.com/ylingfeng/dynamicmlp	true	true	true	pytorch
https://paperswithcode.com/paper/a-unified-framework-for-masked-and-mask-free	A Unified Framework for Masked and Mask-Free Face Recognition via Feature Rectification	2202.07358	https://arxiv.org/abs/2202.07358v1	https://arxiv.org/pdf/2202.07358v1.pdf	https://github.com/haoosz/ffr-net	true	true	true	pytorch
https://paperswithcode.com/paper/bashexplainer-retrieval-augmented-bash-code	BashExplainer: Retrieval-Augmented Bash Code Comment Generation based on Fine-tuned CodeBERT	2206.13325	https://arxiv.org/abs/2206.13325v1	https://arxiv.org/pdf/2206.13325v1.pdf	https://github.com/NTDXYG/BASHEXPLAINER	true	true	false	none
https://paperswithcode.com/paper/generative-invertible-quantum-neural-networks	Generative Invertible Quantum Neural Networks	2302.12906	https://arxiv.org/abs/2302.12906v3	https://arxiv.org/pdf/2302.12906v3.pdf	https://gitlab.com/RussellA/quantumML	true	true	false	pytorch
https://paperswithcode.com/paper/nedmp-neural-enhanced-dynamic-message-passing	NEDMP: Neural Enhanced Dynamic Message Passing	2202.06496	https://arxiv.org/abs/2202.06496v1	https://arxiv.org/pdf/2202.06496v1.pdf	https://github.com/feigsss/nedmp	true	true	false	pytorch
https://paperswithcode.com/paper/distributing-persistent-homology-via-spectral	Distributing Persistent Homology via Spectral Sequences	1907.05228	https://arxiv.org/abs/1907.05228v1	https://arxiv.org/pdf/1907.05228v1.pdf	https://github.com/atorras1618/PerMaViss	false	false	true	none
https://paperswithcode.com/paper/r-local-sensing-improved-algorithm-and	r-local sensing: Improved algorithm and applications	2110.14034	https://arxiv.org/abs/2110.14034v3	https://arxiv.org/pdf/2110.14034v3.pdf	https://github.com/aabbas02/proximal-alt-min-for-uls-udgp	true	true	true	none
https://paperswithcode.com/paper/communication-efficient-zeroth-order	Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applications	2306.05655	https://arxiv.org/abs/2306.05655v1	https://arxiv.org/pdf/2306.05655v1.pdf	https://github.com/sunses-hub/fed-ef-zo-sgd	true	true	false	none
https://paperswithcode.com/paper/denoising-diffusion-probabilistic-models	Denoising Diffusion Probabilistic Models	2006.11239	https://arxiv.org/abs/2006.11239v2	https://arxiv.org/pdf/2006.11239v2.pdf	https://github.com/keonlee9420/DiffGAN-TTS	false	false	true	pytorch
https://paperswithcode.com/paper/tackling-the-generative-learning-trilemma-1	Tackling the Generative Learning Trilemma with Denoising Diffusion GANs	2112.07804	https://arxiv.org/abs/2112.07804v2	https://arxiv.org/pdf/2112.07804v2.pdf	https://github.com/keonlee9420/DiffGAN-TTS	false	false	true	pytorch
https://paperswithcode.com/paper/diffsinger-diffusion-acoustic-model-for	DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism	2105.02446	https://arxiv.org/abs/2105.02446v6	https://arxiv.org/pdf/2105.02446v6.pdf	https://github.com/keonlee9420/DiffGAN-TTS	false	false	true	pytorch
https://paperswithcode.com/paper/divide-and-conquer-text-semantic-matching-1	Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents	2203.02898	https://arxiv.org/abs/2203.02898v1	https://arxiv.org/pdf/2203.02898v1.pdf	https://github.com/rowitzou/dc-match	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.