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/a-multi-modal-geographic-pre-training-method	MGeo: Multi-Modal Geographic Pre-Training Method	2301.04283	https://arxiv.org/abs/2301.04283v2	https://arxiv.org/pdf/2301.04283v2.pdf	https://github.com/phantomgrapes/mgeo	true	true	true	pytorch
https://paperswithcode.com/paper/temos-generating-diverse-human-motions-from	TEMOS: Generating diverse human motions from textual descriptions	2204.14109	https://arxiv.org/abs/2204.14109v2	https://arxiv.org/pdf/2204.14109v2.pdf	https://github.com/Mathux/TEMOS	true	false	true	pytorch
https://paperswithcode.com/paper/contrastive-learning-for-improving-asr	Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding	2205.00693	https://arxiv.org/abs/2205.00693v2	https://arxiv.org/pdf/2205.00693v2.pdf	https://github.com/miulab/spokencse	true	true	true	pytorch
https://paperswithcode.com/paper/mnist-c-a-robustness-benchmark-for-computer	MNIST-C: A Robustness Benchmark for Computer Vision	1906.02337	https://arxiv.org/abs/1906.02337v1	https://arxiv.org/pdf/1906.02337v1.pdf	https://github.com/testingautomated-usi/fashion-mnist-c	false	false	true	none
https://paperswithcode.com/paper/prefix-tuning-optimizing-continuous-prompts	Prefix-Tuning: Optimizing Continuous Prompts for Generation	2101.00190	https://arxiv.org/abs/2101.00190v1	https://arxiv.org/pdf/2101.00190v1.pdf	https://github.com/ga642381/SpeechPrompt	false	false	true	pytorch
https://paperswithcode.com/paper/generative-spoken-language-modeling-from-raw	Generative Spoken Language Modeling from Raw Audio	2102.01192	https://arxiv.org/abs/2102.01192v2	https://arxiv.org/pdf/2102.01192v2.pdf	https://github.com/ga642381/SpeechPrompt	false	false	true	pytorch
https://paperswithcode.com/paper/towards-theoretical-analysis-of	Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs	2205.01940	https://arxiv.org/abs/2205.01940v2	https://arxiv.org/pdf/2205.01940v2.pdf	https://github.com/sjtu-xai-lab/transformation-complexity	true	true	true	pytorch
https://paperswithcode.com/paper/mad-self-supervised-masked-anomaly-detection	MAD: Self-Supervised Masked Anomaly Detection Task for Multivariate Time Series	2205.02100	https://arxiv.org/abs/2205.02100v1	https://arxiv.org/pdf/2205.02100v1.pdf	https://github.com/icsdataset/hai	true	true	false	none
https://paperswithcode.com/paper/emospeech-guiding-fastspeech2-towards	EmoSpeech: Guiding FastSpeech2 Towards Emotional Text to Speech	2307.00024	https://arxiv.org/abs/2307.00024v1	https://arxiv.org/pdf/2307.00024v1.pdf	https://github.com/deepvk/emospeech	true	true	true	pytorch
https://paperswithcode.com/paper/learning-to-disambiguate-strongly-interacting	Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentation	2107.00434	https://arxiv.org/abs/2107.00434v2	https://arxiv.org/pdf/2107.00434v2.pdf	https://github.com/zc-alexfan/digit-interacting	true	false	true	pytorch
https://paperswithcode.com/paper/graph-topology-invariant-gradient-and	Graph topology invariant gradient and sampling complexity for decentralized and stochastic optimization	2101.00143	https://arxiv.org/abs/2101.00143v2	https://arxiv.org/pdf/2101.00143v2.pdf	https://github.com/Libensemble/libensemble	false	false	true	none
https://paperswithcode.com/paper/gradient-sliding-for-composite-optimization	Gradient Sliding for Composite Optimization	1406.0919	http://arxiv.org/abs/1406.0919v2	http://arxiv.org/pdf/1406.0919v2.pdf	https://github.com/Libensemble/libensemble	false	false	true	none
https://paperswithcode.com/paper/inferring-density-dependent-population	Inferring Density-Dependent Population Dynamics Mechanisms through Rate Disambiguation for Logistic Birth-Death Processes	2205.05189	https://arxiv.org/abs/2205.05189v1	https://arxiv.org/pdf/2205.05189v1.pdf	https://github.com/lhuynhm/birthdeathdisambiguation	true	true	false	none
https://paperswithcode.com/paper/cic-bart-ssa-controllable-image-captioning	CIC-BART-SSA: Controllable Image Captioning with Structured Semantic Augmentation	2407.11393	https://arxiv.org/abs/2407.11393v2	https://arxiv.org/pdf/2407.11393v2.pdf	https://github.com/SamsungLabs/CIC-BART-SSA	true	true	false	pytorch
https://paperswithcode.com/paper/jax-md-end-to-end-differentiable-hardware-1	JAX, M.D.: A Framework for Differentiable Physics	1912.04232	https://arxiv.org/abs/1912.04232v2	https://arxiv.org/pdf/1912.04232v2.pdf	https://github.com/google/jax-md	true	true	true	jax
https://paperswithcode.com/paper/deep-learning-based-channel-estimation-for-4	Deep Learning-based Channel Estimation for Wideband Hybrid MmWave Massive MIMO	2205.05202	https://arxiv.org/abs/2205.05202v1	https://arxiv.org/pdf/2205.05202v1.pdf	https://github.com/ericgjb/sbl_unfolding_based_had_mimo_channel_estimation	true	true	false	tf
https://paperswithcode.com/paper/partial-class-activation-attention-for	Partial Class Activation Attention for Semantic Segmentation	null	http://openaccess.thecvf.com//content/CVPR2022/html/Liu_Partial_Class_Activation_Attention_for_Semantic_Segmentation_CVPR_2022_paper.html	http://openaccess.thecvf.com//content/CVPR2022/papers/Liu_Partial_Class_Activation_Attention_for_Semantic_Segmentation_CVPR_2022_paper.pdf	https://github.com/lsa1997/pcaa	true	true	false	pytorch
https://paperswithcode.com/paper/multi-scale-memory-based-video-deblurring	Multi-Scale Memory-Based Video Deblurring	2204.02977	https://arxiv.org/abs/2204.02977v1	https://arxiv.org/pdf/2204.02977v1.pdf	https://github.com/jibo27/memdeblur	true	true	true	pytorch
https://paperswithcode.com/paper/far-from-asymptopia	Far from Asymptopia	2205.03343	https://arxiv.org/abs/2205.03343v2	https://arxiv.org/pdf/2205.03343v2.pdf	https://github.com/mcabbott/atomicpriors.jl	true	true	true	none
https://paperswithcode.com/paper/llm-based-multi-agent-generation-of-semi	LLM Based Multi-Agent Generation of Semi-structured Documents from Semantic Templates in the Public Administration Domain	2402.14871	https://arxiv.org/abs/2402.14871v1	https://arxiv.org/pdf/2402.14871v1.pdf	https://github.com/michelebri/multi_agent_document_generation	true	false	true	none
https://paperswithcode.com/paper/two-metrics-on-rooted-unordered-trees-with	Two Metrics on Rooted Unordered Trees with Labels	2103.11553	https://arxiv.org/abs/2103.11553v3	https://arxiv.org/pdf/2103.11553v3.pdf	https://github.com/yuewangmathbio/treemetric	true	true	true	none
https://paperswithcode.com/paper/pointdistiller-structured-knowledge	PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection	2205.11098	https://arxiv.org/abs/2205.11098v1	https://arxiv.org/pdf/2205.11098v1.pdf	https://github.com/runpeidong/pointdistiller	true	true	true	pytorch
https://paperswithcode.com/paper/pre-trained-vision-language-models-learn	Pre-trained Vision-Language Models Learn Discoverable Visual Concepts	2404.12652	https://arxiv.org/abs/2404.12652v2	https://arxiv.org/pdf/2404.12652v2.pdf	https://github.com/brown-palm/concept-discovery-and-learning	true	true	false	pytorch
https://paperswithcode.com/paper/teaching-programming-to-novices-using-the	Teaching Programming to Novices Using the codeBoot Online Environment	2207.12702	https://arxiv.org/abs/2207.12702v1	https://arxiv.org/pdf/2207.12702v1.pdf	https://github.com/udem-dlteam/codeboot	true	true	false	none
https://paperswithcode.com/paper/what-causes-optical-flow-networks-to-be	Towards Understanding Adversarial Robustness of Optical Flow Networks	2103.16255	https://arxiv.org/abs/2103.16255v3	https://arxiv.org/pdf/2103.16255v3.pdf	https://github.com/lmb-freiburg/understanding_flow_robustness	true	true	true	pytorch
https://paperswithcode.com/paper/hierarchical-consistency-regularized-mean	Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation	2105.10369	https://arxiv.org/abs/2105.10369v2	https://arxiv.org/pdf/2105.10369v2.pdf	https://github.com/jacobzhaoziyuan/HCR-MT	true	false	true	pytorch
https://paperswithcode.com/paper/fully-steerable-3d-spherical-neurons	Steerable 3D Spherical Neurons	2106.13863	https://arxiv.org/abs/2106.13863v7	https://arxiv.org/pdf/2106.13863v7.pdf	https://github.com/pavlo-melnyk/steerable-3d-neurons	true	true	true	pytorch
https://paperswithcode.com/paper/boxdiff-text-to-image-synthesis-with-training	BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion	2307.10816	https://arxiv.org/abs/2307.10816v4	https://arxiv.org/pdf/2307.10816v4.pdf	https://github.com/showlab/boxdiff	true	true	true	pytorch
https://paperswithcode.com/paper/supracentrality-analysis-of-temporal-networks	Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling	1906.06366	http://arxiv.org/abs/1906.06366v2	http://arxiv.org/pdf/1906.06366v2.pdf	https://github.com/taylordr/supracentrality	false	false	true	none
https://paperswithcode.com/paper/190402059	Tunable Eigenvector-Based Centralities for Multiplex and Temporal Networks	1904.02059	http://arxiv.org/abs/1904.02059v1	http://arxiv.org/pdf/1904.02059v1.pdf	https://github.com/taylordr/supracentrality	true	true	true	none
https://paperswithcode.com/paper/mascara-systematically-generating-memorable	MASCARA: Systematically Generating Memorable And Secure Passphrases	2303.09150	https://arxiv.org/abs/2303.09150v1	https://arxiv.org/pdf/2303.09150v1.pdf	https://github.com/mainack/mascara-passphrase-code-data	true	true	false	none
https://paperswithcode.com/paper/representation-learning-with-contrastive	Representation Learning with Contrastive Predictive Coding	1807.03748	http://arxiv.org/abs/1807.03748v2	http://arxiv.org/pdf/1807.03748v2.pdf	https://github.com/chorowski-lab/hcpc	false	false	true	pytorch
https://paperswithcode.com/paper/effective-explanations-for-entity-resolution	Effective Explanations for Entity Resolution Models	2203.12978	https://arxiv.org/abs/2203.12978v2	https://arxiv.org/pdf/2203.12978v2.pdf	https://github.com/tteofili/certa	true	true	true	pytorch
https://paperswithcode.com/paper/voxel-field-fusion-for-3d-object-detection	Voxel Field Fusion for 3D Object Detection	2205.15938	https://arxiv.org/abs/2205.15938v1	https://arxiv.org/pdf/2205.15938v1.pdf	https://github.com/dvlab-research/vff	true	true	true	pytorch
https://paperswithcode.com/paper/libensemble-a-library-to-coordinate-the	libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations	2104.08322	https://arxiv.org/abs/2104.08322v1	https://arxiv.org/pdf/2104.08322v1.pdf	https://github.com/Libensemble/libensemble	false	false	true	none
https://paperswithcode.com/paper/toward-large-kernel-models	Toward Large Kernel Models	2302.02605	https://arxiv.org/abs/2302.02605v3	https://arxiv.org/pdf/2302.02605v3.pdf	https://github.com/eigenpro/eigenpro3	true	true	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/VedantDere0104/Pix2Pix_GAN	false	false	true	none
https://paperswithcode.com/paper/boosting-out-of-distribution-detection-with-1	Boosting Out-of-Distribution Detection with Multiple Pre-trained Models	2212.12720	https://arxiv.org/abs/2212.12720v2	https://arxiv.org/pdf/2212.12720v2.pdf	https://github.com/mapleleaf6/zode	true	false	false	pytorch
https://paperswithcode.com/paper/electrical-impedance-tomography-with-deep	Electrical Impedance Tomography with Deep Calderón Method	2304.09074	https://arxiv.org/abs/2304.09074v2	https://arxiv.org/pdf/2304.09074v2.pdf	https://github.com/kwancheolshin/deep-calderon-method	true	true	false	tf
https://paperswithcode.com/paper/supmae-supervised-masked-autoencoders-are	SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners	2205.14540	https://arxiv.org/abs/2205.14540v3	https://arxiv.org/pdf/2205.14540v3.pdf	https://github.com/cmu-enyac/supmae	true	true	true	pytorch
https://paperswithcode.com/paper/the-curious-layperson-fine-grained-image	The Curious Layperson: Fine-Grained Image Recognition without Expert Labels	2111.03651	https://arxiv.org/abs/2111.03651v1	https://arxiv.org/pdf/2111.03651v1.pdf	https://github.com/subhc/clever	true	true	true	pytorch
https://paperswithcode.com/paper/sharp-shielding-aware-robust-planning-for	SHARP: Shielding-Aware Robust Planning for Safe and Efficient Human-Robot Interaction	2110.00843	https://arxiv.org/abs/2110.00843v3	https://arxiv.org/pdf/2110.00843v3.pdf	https://github.com/saferoboticslab/sharp	true	true	true	none
https://paperswithcode.com/paper/unsupervised-cross-lingual-representation-1	Unsupervised Cross-lingual Representation Learning at Scale	1911.02116	https://arxiv.org/abs/1911.02116v2	https://arxiv.org/pdf/1911.02116v2.pdf	https://github.com/deepset-ai/FARM	false	false	true	pytorch
https://paperswithcode.com/paper/semantic-conditional-diffusion-networks-for	Semantic-Conditional Diffusion Networks for Image Captioning	2212.03099	https://arxiv.org/abs/2212.03099v1	https://arxiv.org/pdf/2212.03099v1.pdf	https://github.com/yehli/xmodaler	true	true	false	pytorch
https://paperswithcode.com/paper/active-uncertainty-learning-for-human-robot	Active Uncertainty Reduction for Human-Robot Interaction: An Implicit Dual Control Approach	2202.07720	https://arxiv.org/abs/2202.07720v2	https://arxiv.org/pdf/2202.07720v2.pdf	https://github.com/saferoboticslab/sharp	false	false	true	none
https://paperswithcode.com/paper/tpc-transformation-specific-smoothing-for	TPC: Transformation-Specific Smoothing for Point Cloud Models	2201.12733	https://arxiv.org/abs/2201.12733v5	https://arxiv.org/pdf/2201.12733v5.pdf	https://github.com/qianhewu/point-cloud-smoothing	true	true	true	pytorch
https://paperswithcode.com/paper/activeaed-a-human-in-the-loop-improves	ActiveAED: A Human in the Loop Improves Annotation Error Detection	2305.20045	https://arxiv.org/abs/2305.20045v1	https://arxiv.org/pdf/2305.20045v1.pdf	https://github.com/mainlp/activeaed	true	true	false	pytorch
https://paperswithcode.com/paper/one-step-detection-paradigm-for-hyperspectral	One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning	2303.12342	https://arxiv.org/abs/2303.12342v1	https://arxiv.org/pdf/2303.12342v1.pdf	https://github.com/Jingtao-Li-CVer/TDD	true	false	true	pytorch
https://paperswithcode.com/paper/linearity-grafting-relaxed-neuron-pruning	Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness	2206.07839	https://arxiv.org/abs/2206.07839v1	https://arxiv.org/pdf/2206.07839v1.pdf	https://github.com/vita-group/linearity-grafting	true	true	false	pytorch
https://paperswithcode.com/paper/lightseq-accelerated-training-for-transformer	LightSeq2: Accelerated Training for Transformer-based Models on GPUs	2110.05722	https://arxiv.org/abs/2110.05722v3	https://arxiv.org/pdf/2110.05722v3.pdf	https://github.com/bytedance/lightseq	true	true	false	tf
https://paperswithcode.com/paper/variational-counterdiabatic-driving-of-the	Variational counterdiabatic driving of the Hubbard model for ground-state preparation	2206.07597	https://arxiv.org/abs/2206.07597v2	https://arxiv.org/pdf/2206.07597v2.pdf	https://github.com/qx20211202/hubbardcd	true	true	true	none
https://paperswithcode.com/paper/self-supervised-learning-for-contextualized	Self-Supervised Learning for Contextualized Extractive Summarization	1906.04466	https://arxiv.org/abs/1906.04466v1	https://arxiv.org/pdf/1906.04466v1.pdf	https://github.com/minsoo9506/NLP-study	false	false	true	pytorch
https://paperswithcode.com/paper/sequence-to-sequence-learning-with-neural	Sequence to Sequence Learning with Neural Networks	1409.3215	http://arxiv.org/abs/1409.3215v3	http://arxiv.org/pdf/1409.3215v3.pdf	https://github.com/minsoo9506/NLP-study	false	false	true	pytorch
https://paperswithcode.com/paper/efficient-estimation-of-word-representations	Efficient Estimation of Word Representations in Vector Space	1301.3781	http://arxiv.org/abs/1301.3781v3	http://arxiv.org/pdf/1301.3781v3.pdf	https://github.com/minsoo9506/NLP-study	false	false	true	pytorch
https://paperswithcode.com/paper/quantum-circuit-autoencoder	Quantum Circuit AutoEncoder	2307.08446	https://arxiv.org/abs/2307.08446v2	https://arxiv.org/pdf/2307.08446v2.pdf	https://github.com/linke-quantum/qcae-master	true	true	false	mindspore
https://paperswithcode.com/paper/soft-actor-critic-off-policy-maximum-entropy	Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor	1801.01290	http://arxiv.org/abs/1801.01290v2	http://arxiv.org/pdf/1801.01290v2.pdf	https://github.com/facebookresearch/rl/blob/main/examples/sac/sac.py	false	false	false	jax
https://paperswithcode.com/paper/label-and-distribution-discriminative-dual	Dual Representation Learning for Out-of-Distribution Detection	2206.09387	https://arxiv.org/abs/2206.09387v2	https://arxiv.org/pdf/2206.09387v2.pdf	https://github.com/lawliet-zzl/drl	true	true	false	pytorch
https://paperswithcode.com/paper/efficient-and-robust-approximate-nearest	Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs	1603.09320	http://arxiv.org/abs/1603.09320v4	http://arxiv.org/pdf/1603.09320v4.pdf	https://github.com/evan176/hnswgo	false	false	true	none
https://paperswithcode.com/paper/agent-based-graph-neural-networks	Agent-based Graph Neural Networks	2206.11010	https://arxiv.org/abs/2206.11010v2	https://arxiv.org/pdf/2206.11010v2.pdf	https://github.com/karolismart/agentnet	true	true	true	pytorch
https://paperswithcode.com/paper/parametrization-of-gamma-ray-production-cross	Parametrization of gamma-ray production cross-sections for pp interactions in a broad proton energy range from the kinematic threshold to PeV energies	1406.7369	https://arxiv.org/abs/1406.7369v2	https://arxiv.org/pdf/1406.7369v2.pdf	https://github.com/ervinkafex/LibppGam	false	false	true	none
https://paperswithcode.com/paper/application-of-a-hybrid-bi-lstm-crf-model-to	Application of a Hybrid Bi-LSTM-CRF model to the task of Russian Named Entity Recognition	1709.09686	http://arxiv.org/abs/1709.09686v2	http://arxiv.org/pdf/1709.09686v2.pdf	https://github.com/deepmipt/ner	false	false	true	tf
https://paperswithcode.com/paper/a-context-integrated-transformer-based-neural	A Context-Integrated Transformer-Based Neural Network for Auction Design	2201.12489	https://arxiv.org/abs/2201.12489v3	https://arxiv.org/pdf/2201.12489v3.pdf	https://github.com/zjduan/CITransNet	true	true	true	pytorch
https://paperswithcode.com/paper/dataperf-benchmarks-for-data-centric-ai-1	DataPerf: Benchmarks for Data-Centric AI Development	2207.10062	https://arxiv.org/abs/2207.10062v4	https://arxiv.org/pdf/2207.10062v4.pdf	https://github.com/mlcommons/dataperf	true	true	false	tf
https://paperswithcode.com/paper/a-permutation-equivariant-neural-network	A Permutation-Equivariant Neural Network Architecture For Auction Design	2003.01497	https://arxiv.org/abs/2003.01497v4	https://arxiv.org/pdf/2003.01497v4.pdf	https://github.com/zjduan/CITransNet	false	false	true	pytorch
https://paperswithcode.com/paper/plingo-a-system-for-probabilistic-reasoning	plingo: A system for probabilistic reasoning in clingo based on lpmln	2206.11515	https://arxiv.org/abs/2206.11515v4	https://arxiv.org/pdf/2206.11515v4.pdf	https://github.com/potassco/plingo	true	true	false	none
https://paperswithcode.com/paper/objective-robustness-in-deep-reinforcement	Goal Misgeneralization in Deep Reinforcement Learning	2105.14111	https://arxiv.org/abs/2105.14111v7	https://arxiv.org/pdf/2105.14111v7.pdf	https://github.com/JacobPfau/procgenAISC	true	true	true	pytorch
https://paperswithcode.com/paper/keras-gpt-copilot-integrating-the-power-of	Keras GPT Copilot: Integrating the Power of Large Language Models in Deep Learning Model Development	null	https://doi.org/10.5281/zenodo.7935183	https://doi.org/10.5281/zenodo.7935183	https://github.com/fabprezja/keras-gpt-copilot	true	false	false	tf
https://paperswithcode.com/paper/diffusion-deformable-model-for-4d-temporal	Diffusion Deformable Model for 4D Temporal Medical Image Generation	2206.13295	https://arxiv.org/abs/2206.13295v1	https://arxiv.org/pdf/2206.13295v1.pdf	https://github.com/torchddm/ddm	true	true	false	pytorch
https://paperswithcode.com/paper/tracer-extreme-attention-guided-salient	TRACER: Extreme Attention Guided Salient Object Tracing Network	2112.07380	https://arxiv.org/abs/2112.07380v2	https://arxiv.org/pdf/2112.07380v2.pdf	https://github.com/Karel911/TRACER	true	true	true	pytorch
https://paperswithcode.com/paper/optimizing-task-waiting-times-in-dynamic	Optimizing Task Waiting Times in Dynamic Vehicle Routing	2307.03984	https://arxiv.org/abs/2307.03984v1	https://arxiv.org/pdf/2307.03984v1.pdf	https://github.com/arminsadeghi/mdvrp-optimal-policy	true	true	false	none
https://paperswithcode.com/paper/tico-transformation-invariance-and-covariance	TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning	2206.10698	https://arxiv.org/abs/2206.10698v2	https://arxiv.org/pdf/2206.10698v2.pdf	https://github.com/sayannag/TiCo-pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/refined-semantic-enhancement-towards	Refined Semantic Enhancement towards Frequency Diffusion for Video Captioning	2211.15076	https://arxiv.org/abs/2211.15076v2	https://arxiv.org/pdf/2211.15076v2.pdf	https://github.com/lzp870/rsfd	true	true	true	pytorch
https://paperswithcode.com/paper/self-supervised-semantic-segmentation-1	Self-supervised Semantic Segmentation: Consistency over Transformation	2309.00143	https://arxiv.org/abs/2309.00143v1	https://arxiv.org/pdf/2309.00143v1.pdf	https://github.com/mindflow-institue/ssct	true	true	true	pytorch
https://paperswithcode.com/paper/machine-learning-the-trilinear-and-light	Machine learning the trilinear and light-quark Yukawa couplings from Higgs pair kinematic shapes	2207.04157	https://arxiv.org/abs/2207.04157v2	https://arxiv.org/pdf/2207.04157v2.pdf	https://github.com/talismanbrandi/IML-diHiggs	true	true	true	none
https://paperswithcode.com/paper/normalizing-flows-on-tori-and-spheres	Normalizing Flows on Tori and Spheres	2002.02428	https://arxiv.org/abs/2002.02428v2	https://arxiv.org/pdf/2002.02428v2.pdf	https://github.com/ryushinn/flows-on-sphere	false	false	true	pytorch
https://paperswithcode.com/paper/adapterhub-a-framework-for-adapting	AdapterHub: A Framework for Adapting Transformers	2007.07779	https://arxiv.org/abs/2007.07779v3	https://arxiv.org/pdf/2007.07779v3.pdf	https://github.com/parovicm/badx	false	false	true	jax
https://paperswithcode.com/paper/automatic-pull-request-title-generation	Automatic Pull Request Title Generation	2206.10430	https://arxiv.org/abs/2206.10430v2	https://arxiv.org/pdf/2206.10430v2.pdf	https://github.com/soarsmu/prtiger	true	true	false	pytorch
https://paperswithcode.com/paper/trajectron-multi-agent-generative-trajectory	Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data	2001.03093	https://arxiv.org/abs/2001.03093v5	https://arxiv.org/pdf/2001.03093v5.pdf	https://github.com/nvr-avg/adaptive-prediction	false	false	true	pytorch
https://paperswithcode.com/paper/neural-networks-on-random-graphs	Analyzing Neural Networks Based on Random Graphs	2002.08104	https://arxiv.org/abs/2002.08104v3	https://arxiv.org/pdf/2002.08104v3.pdf	https://github.com/rmldj/random-graph-nn-paper	true	true	true	pytorch
https://paperswithcode.com/paper/the-problem-of-human-label-variation-on	The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation	2211.02570	https://arxiv.org/abs/2211.02570v1	https://arxiv.org/pdf/2211.02570v1.pdf	https://github.com/mainlp/awesome-human-label-variation	true	true	true	none
https://paperswithcode.com/paper/masked-autoencoders-that-listen	Masked Autoencoders that Listen	2207.06405	https://arxiv.org/abs/2207.06405v3	https://arxiv.org/pdf/2207.06405v3.pdf	https://github.com/facebookresearch/audiomae	true	true	true	pytorch
https://paperswithcode.com/paper/a-tutorial-on-time-dependent-cohort-state	A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example	2108.13552	https://arxiv.org/abs/2108.13552v2	https://arxiv.org/pdf/2108.13552v2.pdf	https://github.com/DARTH-git/cohort-modeling-tutorial-timedep	true	true	true	none
https://paperswithcode.com/paper/pidloc-cross-view-pose-optimization-network	PIDLoc: Cross-View Pose Optimization Network Inspired by PID Controllers	null	http://openaccess.thecvf.com//content/CVPR2025/html/Lee_PIDLoc_Cross-View_Pose_Optimization_Network_Inspired_by_PID_Controllers_CVPR_2025_paper.html	http://openaccess.thecvf.com//content/CVPR2025/papers/Lee_PIDLoc_Cross-View_Pose_Optimization_Network_Inspired_by_PID_Controllers_CVPR_2025_paper.pdf	https://github.com/url-kaist/pidloc	true	true	false	none
https://paperswithcode.com/paper/real-world-image-dehazing-with-improved-joint	Real-world image dehazing with improved joint enhancement and exposure fusion	null	https://www.sciencedirect.com/science/article/pii/S1047320322002401	https://www.sciencedirect.com/science/article/pii/S1047320322002401	https://github.com/nhk21/Real-world-image-dehazing-with-improved-joint-enhancement-and-exposure-fusion	true	false	false	none
https://paperswithcode.com/paper/a-k-cdot-p-effective-hamiltonian-generator	A $k\cdot p$ effective Hamiltonian generator	2104.08493	https://arxiv.org/abs/2104.08493v1	https://arxiv.org/pdf/2104.08493v1.pdf	https://github.com/yjiang-iop/kdotp-generator	true	true	true	none
https://paperswithcode.com/paper/custom-pretrainings-and-adapted-3d-convnext	COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings	2206.15073	https://arxiv.org/abs/2206.15073v2	https://arxiv.org/pdf/2206.15073v2.pdf	https://github.com/kiedani/submission_2nd_covid19_competition	true	true	false	pytorch
https://paperswithcode.com/paper/motion-style-transfer-modular-low-rank	Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting	2211.03165	https://arxiv.org/abs/2211.03165v1	https://arxiv.org/pdf/2211.03165v1.pdf	https://github.com/vita-epfl/motion-style-transfer	true	true	false	pytorch
https://paperswithcode.com/paper/skeleton-based-action-recognition-via	Skeleton-based Action Recognition via Temporal-Channel Aggregation	2205.15936	https://arxiv.org/abs/2205.15936v2	https://arxiv.org/pdf/2205.15936v2.pdf	https://github.com/OrdinaryQin/TCA-GCN	true	false	true	pytorch
https://paperswithcode.com/paper/building-a-relation-extraction-baseline-for	Building a Relation Extraction Baseline for Gene-Disease Associations: A Reproducibility Study	2207.06226	https://arxiv.org/abs/2207.06226v1	https://arxiv.org/pdf/2207.06226v1.pdf	https://github.com/mntlra/dexter	true	true	false	none
https://paperswithcode.com/paper/voxel-r-cnn-towards-high-performance-voxel	Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection	2012.15712	https://arxiv.org/abs/2012.15712v2	https://arxiv.org/pdf/2012.15712v2.pdf	https://github.com/open-mmlab/OpenPCDet	true	true	true	pytorch
https://paperswithcode.com/paper/mppnet-multi-frame-feature-intertwining-with	MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection	2205.05979	https://arxiv.org/abs/2205.05979v2	https://arxiv.org/pdf/2205.05979v2.pdf	https://github.com/open-mmlab/OpenPCDet	true	true	true	pytorch
https://paperswithcode.com/paper/spatial-aggregation-with-respect-to-a	Spatial Aggregation with Respect to a Population Distribution	2207.06700	https://arxiv.org/abs/2207.06700v1	https://arxiv.org/pdf/2207.06700v1.pdf	https://github.com/paigejo/summer	true	true	false	none
https://paperswithcode.com/paper/a-little-fog-for-a-large-turn	A Little Fog for a Large Turn	2001.05873	https://arxiv.org/abs/2001.05873v1	https://arxiv.org/pdf/2001.05873v1.pdf	https://github.com/SullyChen/Autopilot-TensorFlow	false	false	true	tf
https://paperswithcode.com/paper/tt-ggxy-a-flexible-library-to-compute-gluon	{\tt ggxy}: a flexible library to compute gluon-induced cross sections	2506.04323	https://arxiv.org/abs/2506.04323v1	https://arxiv.org/pdf/2506.04323v1.pdf	https://gitlab.com/ggxy/ggxy-release	true	true	true	none
https://paperswithcode.com/paper/evaluating-coreference-resolvers-on-community	Evaluating Coreference Resolvers on Community-based Question Answering: From Rule-based to State of the Art	null	https://aclanthology.org/2022.crac-1.7	https://aclanthology.org/2022.crac-1.7.pdf	https://github.com/haixiachai/coref_cqa	true	true	false	tf
https://paperswithcode.com/paper/improving-bridging-reference-resolution-using	Improving Bridging Reference Resolution using Continuous Essentiality from Crowdsourcing	null	https://aclanthology.org/2022.crac-1.8	https://aclanthology.org/2022.crac-1.8.pdf	https://github.com/nobu-g/bridging-resolution	true	true	false	pytorch
https://paperswithcode.com/paper/watermark-vaccine-adversarial-attacks-to	Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal	2207.08178	https://arxiv.org/abs/2207.08178v1	https://arxiv.org/pdf/2207.08178v1.pdf	https://github.com/thinwayliu/watermark-vaccine	true	true	true	pytorch
https://paperswithcode.com/paper/learning-to-infer-from-unlabeled-data-a-semi	Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference	2211.02971	https://arxiv.org/abs/2211.02971v1	https://arxiv.org/pdf/2211.02971v1.pdf	https://github.com/msadat3/ssl_for_nli	true	true	false	pytorch
https://paperswithcode.com/paper/semi-supervised-vision-transformers	Semi-Supervised Vision Transformers	2111.11067	https://arxiv.org/abs/2111.11067v2	https://arxiv.org/pdf/2111.11067v2.pdf	https://github.com/wengzejia1/semiformer	true	true	true	pytorch
https://paperswithcode.com/paper/does-thermal-data-make-the-detection-systems	Does Thermal data make the detection systems more reliable?	2111.05191	https://arxiv.org/abs/2111.05191v1	https://arxiv.org/pdf/2111.05191v1.pdf	https://github.com/neurai-lab/mmc	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.