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/ace-a-generic-constraint-solver	ACE, a generic constraint solver	2302.05405	https://arxiv.org/abs/2302.05405v2	https://arxiv.org/pdf/2302.05405v2.pdf	https://github.com/xcsp3team/ace	true	true	true	none
https://paperswithcode.com/paper/a-unified-framework-for-quantifying-privacy	A Unified Framework for Quantifying Privacy Risk in Synthetic Data	2211.10459	https://arxiv.org/abs/2211.10459v1	https://arxiv.org/pdf/2211.10459v1.pdf	https://github.com/statice/anonymeter	true	true	true	none
https://paperswithcode.com/paper/diffusion-explainer-visual-explanation-for	Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion	2305.03509	https://arxiv.org/abs/2305.03509v3	https://arxiv.org/pdf/2305.03509v3.pdf	https://github.com/poloclub/diffusion-explainer	true	true	true	none
https://paperswithcode.com/paper/intervalmdp-jl-accelerated-value-iteration	IntervalMDP.jl: Accelerated Value Iteration for Interval Markov Decision Processes	2401.04068	https://arxiv.org/abs/2401.04068v2	https://arxiv.org/pdf/2401.04068v2.pdf	https://github.com/zinoex/intervalmdp.jl	true	true	false	none
https://paperswithcode.com/paper/stars-enabled-integrated-sensing-and	STARS Enabled Integrated Sensing and Communications	2207.10748	https://arxiv.org/abs/2207.10748v3	https://arxiv.org/pdf/2207.10748v3.pdf	https://github.com/zhaolin820/stars-enabled-integrated-sensing-and-communications	true	false	true	none
https://paperswithcode.com/paper/learning-to-classify-images-without-labels	SCAN: Learning to Classify Images without Labels	2005.12320	https://arxiv.org/abs/2005.12320v2	https://arxiv.org/pdf/2005.12320v2.pdf	https://github.com/2023-MindSpore-4/Code14/tree/main/simclr	false	false	false	mindspore
https://paperswithcode.com/paper/autoregressive-gan-for-semantic-unconditional	Autoregressive GAN for Semantic Unconditional Head Motion Generation	2211.00987	https://arxiv.org/abs/2211.00987v2	https://arxiv.org/pdf/2211.00987v2.pdf	https://github.com/louisbearing/unconditionalheadmotion	true	true	true	pytorch
https://paperswithcode.com/paper/solving-elliptic-problems-with-singular	Solving Elliptic Problems with Singular Sources using Singularity Splitting Deep Ritz Method	2209.02931	https://arxiv.org/abs/2209.02931v2	https://arxiv.org/pdf/2209.02931v2.pdf	https://github.com/hhjc-web/ssdrm	true	true	false	none
https://paperswithcode.com/paper/memguard-defending-against-black-box	MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples	1909.10594	https://arxiv.org/abs/1909.10594v3	https://arxiv.org/pdf/1909.10594v3.pdf	https://github.com/jinyuan-jia/memguard	false	false	true	tf
https://paperswithcode.com/paper/learning-navigational-visual-representations	Learning Navigational Visual Representations with Semantic Map Supervision	2307.12335	https://arxiv.org/abs/2307.12335v1	https://arxiv.org/pdf/2307.12335v1.pdf	https://github.com/yiconghong/ego2map-navit	true	true	true	none
https://paperswithcode.com/paper/baryonic-features-in-the-matter-transfer	Baryonic Features in the Matter Transfer Function	astro-ph/9709112	https://arxiv.org/abs/astro-ph/9709112v1	https://arxiv.org/pdf/astro-ph/9709112v1.pdf	https://github.com/cosmodesi/cosmoprimo	false	false	true	jax
https://paperswithcode.com/paper/2pcnet-two-phase-consistency-training-for-day	2PCNet: Two-Phase Consistency Training for Day-to-Night Unsupervised Domain Adaptive Object Detection	2303.13853	https://arxiv.org/abs/2303.13853v1	https://arxiv.org/pdf/2303.13853v1.pdf	https://github.com/mecarill/2pcnet	true	true	true	pytorch
https://paperswithcode.com/paper/multilingual-translation-with-extensible	Multilingual Translation with Extensible Multilingual Pretraining and Finetuning	2008.00401	https://arxiv.org/abs/2008.00401v1	https://arxiv.org/pdf/2008.00401v1.pdf	https://github.com/russiannlp/rucola	false	false	true	pytorch
https://paperswithcode.com/paper/effective-open-intent-classification-with-k	Effective Open Intent Classification with K-center Contrastive Learning and Adjustable Decision Boundary	2304.10220	https://arxiv.org/abs/2304.10220v1	https://arxiv.org/pdf/2304.10220v1.pdf	https://github.com/lxk00/clap	true	true	false	pytorch
https://paperswithcode.com/paper/efficient-reachability-analysis-of-closed	Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers	2101.01815	https://arxiv.org/abs/2101.01815v2	https://arxiv.org/pdf/2101.01815v2.pdf	https://github.com/mit-acl/nn_robustness_analysis	true	true	true	pytorch
https://paperswithcode.com/paper/flair-1-semantic-segmentation-and-domain	FLAIR #1: semantic segmentation and domain adaptation dataset	2211.12979	https://arxiv.org/abs/2211.12979v5	https://arxiv.org/pdf/2211.12979v5.pdf	https://github.com/IGNF/FLAIR-1-AI-Challenge	true	false	true	pytorch
https://paperswithcode.com/paper/learning-representative-trajectories-of	Learning Representative Trajectories of Dynamical Systems via Domain-Adaptive Imitation	2304.10260	https://arxiv.org/abs/2304.10260v1	https://arxiv.org/pdf/2304.10260v1.pdf	https://github.com/dlr-mi/dati	true	true	true	tf
https://paperswithcode.com/paper/a-holistic-approach-to-predicting-top-quark	A Holistic Approach to Predicting Top Quark Kinematic Properties with the Covariant Particle Transformer	2203.05687	https://arxiv.org/abs/2203.05687v3	https://arxiv.org/pdf/2203.05687v3.pdf	https://github.com/hep-lbdl/covariant-particle-transformer	false	false	true	pytorch
https://paperswithcode.com/paper/light-weight-deep-extreme-multilabel	Light-weight Deep Extreme Multilabel Classification	2304.11045	https://arxiv.org/abs/2304.11045v1	https://arxiv.org/pdf/2304.11045v1.pdf	https://github.com/misterpawan/lightdxml	true	true	false	pytorch
https://paperswithcode.com/paper/a-convnet-for-the-2020s	A ConvNet for the 2020s	2201.03545	https://arxiv.org/abs/2201.03545v2	https://arxiv.org/pdf/2201.03545v2.pdf	https://github.com/k-h-ismail/convnext-dcls	false	false	true	pytorch
https://paperswithcode.com/paper/towards-scalable-adaptive-learning-with-graph	Towards Scalable Adaptive Learning with Graph Neural Networks and Reinforcement Learning	2305.06398	https://arxiv.org/abs/2305.06398v1	https://arxiv.org/pdf/2305.06398v1.pdf	https://github.com/jvasso/graph-rl4adaptive-learning	true	true	false	pytorch
https://paperswithcode.com/paper/variational-quantum-simulation-of-the-fokker	Variational Quantum Simulation of the Fokker-Planck Equation applied to Quantum Radiation Reaction	2411.17517	https://arxiv.org/abs/2411.17517v2	https://arxiv.org/pdf/2411.17517v2.pdf	https://github.com/OsAmaro/QuantumFokkerPlanck	true	false	true	none
https://paperswithcode.com/paper/learning-permutation-symmetries-with-gips-in	Learning permutation symmetries with gips in R	2307.00790	https://arxiv.org/abs/2307.00790v3	https://arxiv.org/pdf/2307.00790v3.pdf	https://github.com/przechoj/gips_replication_code	true	true	true	none
https://paperswithcode.com/paper/resolving-the-hubble-tension-with-new-early	Resolving the Hubble Tension with New Early Dark Energy	2006.06686	https://arxiv.org/abs/2006.06686v3	https://arxiv.org/pdf/2006.06686v3.pdf	https://github.com/nede-cosmo/triggerclass	false	false	true	none
https://paperswithcode.com/paper/joint-acoustic-echo-cancellation-and-blind	Joint Acoustic Echo Cancellation and Blind Source Extraction based on Independent Vector Extraction	2205.06473	https://arxiv.org/abs/2205.06473v2	https://arxiv.org/pdf/2205.06473v2.pdf	https://github.com/thomashaubner/joint_aec_bse	true	true	false	none
https://paperswithcode.com/paper/scaling-up-dynamic-graph-representation	Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks	2208.10364	https://arxiv.org/abs/2208.10364v3	https://arxiv.org/pdf/2208.10364v3.pdf	https://github.com/edisonleeeee/spikenet	true	true	true	pytorch
https://paperswithcode.com/paper/enriching-language-models-with-graph-based	Enriching language models with graph-based context information to better understand textual data	2305.11070	https://arxiv.org/abs/2305.11070v1	https://arxiv.org/pdf/2305.11070v1.pdf	https://github.com/tryptofanik/gc-bert	true	true	false	pytorch
https://paperswithcode.com/paper/assessing-the-predicting-power-of-gps-data	Assessing the predicting power of GPS data for aftershocks forecasting	2305.11183	https://arxiv.org/abs/2305.11183v1	https://arxiv.org/pdf/2305.11183v1.pdf	https://github.com/vicioms/gps_aftershocks_ml	true	true	false	pytorch
https://paperswithcode.com/paper/measuring-intersectional-biases-in-historical	Measuring Intersectional Biases in Historical Documents	2305.12376	https://arxiv.org/abs/2305.12376v1	https://arxiv.org/pdf/2305.12376v1.pdf	https://github.com/copenlu/intersectional-bias-pbw	true	true	false	none
https://paperswithcode.com/paper/zero-shot-end-to-end-spoken-language	Zero-Shot End-to-End Spoken Language Understanding via Cross-Modal Selective Self-Training	2305.12793	https://arxiv.org/abs/2305.12793v2	https://arxiv.org/pdf/2305.12793v2.pdf	https://github.com/amazon-science/zero-shot-e2e-slu	true	true	false	pytorch
https://paperswithcode.com/paper/uncertainty-based-detection-of-adversarial	Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation	2305.12825	https://arxiv.org/abs/2305.12825v2	https://arxiv.org/pdf/2305.12825v2.pdf	https://github.com/kmaag/adversarial-attack-detection-uncertainty	true	true	true	pytorch
https://paperswithcode.com/paper/asynchronous-trajectory-matching-based	Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways	2302.11283	https://arxiv.org/abs/2302.11283v1	https://arxiv.org/pdf/2302.11283v1.pdf	https://github.com/gy65896/DeepSORVF	false	false	true	pytorch
https://paperswithcode.com/paper/generative-data-driven-approaches-for	Generative data-driven approaches for stochastic subgrid parameterizations in an idealized ocean model	2302.07984	https://arxiv.org/abs/2302.07984v1	https://arxiv.org/pdf/2302.07984v1.pdf	https://github.com/m2lines/pyqg_generative	true	false	true	pytorch
https://paperswithcode.com/paper/cl-uzh-at-semeval-2023-task-10-sexism	CL-UZH at SemEval-2023 Task 10: Sexism Detection through Incremental Fine-Tuning and Multi-Task Learning with Label Descriptions	2306.03907	https://arxiv.org/abs/2306.03907v1	https://arxiv.org/pdf/2306.03907v1.pdf	https://github.com/jagol/cl-uzh-edos-2023	true	true	true	none
https://paperswithcode.com/paper/how-poor-is-the-stimulus-evaluating	How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech	2301.11462	https://arxiv.org/abs/2301.11462v2	https://arxiv.org/pdf/2301.11462v2.pdf	https://github.com/adityayedetore/lm-povstim-with-childes	true	true	false	pytorch
https://paperswithcode.com/paper/predicting-gender-of-brazilian-names-using	Predicting Gender by First Name Using Character-level Machine Learning	2106.10156	https://arxiv.org/abs/2106.10156v2	https://arxiv.org/pdf/2106.10156v2.pdf	https://github.com/roscibely/Gender-Classification	true	false	true	tf
https://paperswithcode.com/paper/a-term-based-approach-for-generating-finite	A Term-based Approach for Generating Finite Automata from Interaction Diagrams	2306.02983	https://arxiv.org/abs/2306.02983v2	https://arxiv.org/pdf/2306.02983v2.pdf	https://github.com/erwanm974/hibou_nfa_generation	false	true	false	none
https://paperswithcode.com/paper/subgraph2vec-learning-distributed	subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs	1606.08928	http://arxiv.org/abs/1606.08928v1	http://arxiv.org/pdf/1606.08928v1.pdf	https://github.com/mldroid/subgraph2vec_tf	false	false	true	tf
https://paperswithcode.com/paper/sensing-the-pulse-of-the-pandemic	Sensing the Pulse of the Pandemic: Geovisualizing the Demographic Disparities of Public Sentiment toward COVID-19 through Social Media	2304.06120	https://arxiv.org/abs/2304.06120v2	https://arxiv.org/pdf/2304.06120v2.pdf	https://github.com/binbinlingiser/sentiment-adjusted-by-demographics-sad-index	true	true	false	none
https://paperswithcode.com/paper/distributionally-robust-ensemble-of-lottery	Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training	null	https://openreview.net/forum?id=WrRG0C1Vo5	https://openreview.net/pdf?id=WrRG0C1Vo5	https://github.com/ritmininglab/dre	true	true	false	pytorch
https://paperswithcode.com/paper/contrabar-contrastive-bayes-adaptive-deep-rl	ContraBAR: Contrastive Bayes-Adaptive Deep RL	2306.02418	https://arxiv.org/abs/2306.02418v1	https://arxiv.org/pdf/2306.02418v1.pdf	https://github.com/ec2604/contrabar	true	true	false	pytorch
https://paperswithcode.com/paper/nice-slam-with-adaptive-feature-grids	NICE-SLAM with Adaptive Feature Grids	2306.02395	https://arxiv.org/abs/2306.02395v2	https://arxiv.org/pdf/2306.02395v2.pdf	https://github.com/zhangganlin/nice-slam-with-adaptive-feature-grids	true	true	false	pytorch
https://paperswithcode.com/paper/mavd-the-first-open-large-scale-mandarin	MAVD: The First Open Large-Scale Mandarin Audio-Visual Dataset with Depth Information	2306.02263	https://arxiv.org/abs/2306.02263v1	https://arxiv.org/pdf/2306.02263v1.pdf	https://github.com/springhuo/mavd	true	true	false	none
https://paperswithcode.com/paper/balancing-logit-variation-for-long-tailed-1	Balancing Logit Variation for Long-tailed Semantic Segmentation	2306.02061	https://arxiv.org/abs/2306.02061v1	https://arxiv.org/pdf/2306.02061v1.pdf	https://github.com/grantword8/blv	true	true	false	pytorch
https://paperswithcode.com/paper/robust-imaging-sonar-based-place-recognition	Robust Imaging Sonar-based Place Recognition and Localization in Underwater Environments	2305.14773	https://arxiv.org/abs/2305.14773v1	https://arxiv.org/pdf/2305.14773v1.pdf	https://github.com/sparolab/sonar_context	true	true	true	none
https://paperswithcode.com/paper/debiased-pairwise-learning-from-positive	Debiased Pairwise Learning from Positive-Unlabeled Implicit Feedback	2307.15973	https://arxiv.org/abs/2307.15973v1	https://arxiv.org/pdf/2307.15973v1.pdf	https://github.com/liubin06/dpl	true	true	false	pytorch
https://paperswithcode.com/paper/pygwalker-on-the-fly-assistant-for	PyGWalker: On-the-fly Assistant for Exploratory Visual Data Analysis	2406.11637	https://arxiv.org/abs/2406.11637v1	https://arxiv.org/pdf/2406.11637v1.pdf	https://github.com/Kanaries/pygwalker	true	true	true	none
https://paperswithcode.com/paper/computational-methods-for-fast-bayesian-model	Computational methods for fast Bayesian model assessment via calibrated posterior p-values	2306.04866	https://arxiv.org/abs/2306.04866v2	https://arxiv.org/pdf/2306.04866v2.pdf	https://github.com/salleuska/fastcppp	true	true	true	none
https://paperswithcode.com/paper/deepening-gamma-ray-point-source-catalogues	Deepening gamma-ray point-source catalogues with sub-threshold information	2306.16483	https://arxiv.org/abs/2306.16483v2	https://arxiv.org/pdf/2306.16483v2.pdf	https://github.com/aurelio-amerio/gpcs	true	true	true	none
https://paperswithcode.com/paper/the-drunkard-s-odometry-estimating-camera	The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes	2306.16917	https://arxiv.org/abs/2306.16917v1	https://arxiv.org/pdf/2306.16917v1.pdf	https://github.com/UZ-SLAMLab/DrunkardsOdometry	true	false	true	pytorch
https://paperswithcode.com/paper/hierarchical-consistent-contrastive-learning	Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing Augmentations	2211.13466	https://arxiv.org/abs/2211.13466v3	https://arxiv.org/pdf/2211.13466v3.pdf	https://github.com/JHang2020/HiCLR	true	false	true	pytorch
https://paperswithcode.com/paper/end-to-end-differentiable-molecular-mechanics	End-to-End Differentiable Molecular Mechanics Force Field Construction	2010.01196	https://arxiv.org/abs/2010.01196v3	https://arxiv.org/pdf/2010.01196v3.pdf	https://github.com/kntkb/openmmforcefields	false	false	true	none
https://paperswithcode.com/paper/minddiffuser-controlled-image-reconstruction-1	MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion	2308.04249	https://arxiv.org/abs/2308.04249v1	https://arxiv.org/pdf/2308.04249v1.pdf	https://github.com/reedonepeck/minddiffuser	true	true	false	pytorch
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition	Deep Residual Learning for Image Recognition	1512.03385	http://arxiv.org/abs/1512.03385v1	http://arxiv.org/pdf/1512.03385v1.pdf	https://github.com/ljy-hy/mentormix_pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/model-based-offline-reinforcement-learning	Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief	2210.06692	https://arxiv.org/abs/2210.06692v2	https://arxiv.org/pdf/2210.06692v2.pdf	https://github.com/2023-MindSpore-1/ms-code-220/tree/main/pmdb	false	false	false	mindspore
https://paperswithcode.com/paper/conditional-variational-autoencoder-with	Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech	2106.06103	https://arxiv.org/abs/2106.06103v1	https://arxiv.org/pdf/2106.06103v1.pdf	https://github.com/lakahaga/dc-comix-tts	false	false	true	pytorch
https://paperswithcode.com/paper/mixer-tts-non-autoregressive-fast-and-compact	Mixer-TTS: non-autoregressive, fast and compact text-to-speech model conditioned on language model embeddings	2110.03584	https://arxiv.org/abs/2110.03584v2	https://arxiv.org/pdf/2110.03584v2.pdf	https://github.com/lakahaga/dc-comix-tts	false	false	true	pytorch
https://paperswithcode.com/paper/qmix-monotonic-value-function-factorisation	QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning	1803.11485	http://arxiv.org/abs/1803.11485v2	http://arxiv.org/pdf/1803.11485v2.pdf	https://github.com/2023-MindSpore-1/ms-code-221/tree/main/qmix	false	false	false	mindspore
https://paperswithcode.com/paper/fpdm-domain-specific-fast-pre-training	$FastDoc$: Domain-Specific Fast Continual Pre-training Technique using Document-Level Metadata and Taxonomy	2306.06190	https://arxiv.org/abs/2306.06190v3	https://arxiv.org/pdf/2306.06190v3.pdf	https://github.com/manavkapadnis/FPDM-Fast-Pre-training-Technique	true	false	false	pytorch
https://paperswithcode.com/paper/on-a-tropicalization-of-planar-polynomial	On a tropicalization of planar polynomial ODEs with finitely many structurally stable phase portraits	2305.18002	https://arxiv.org/abs/2305.18002v3	https://arxiv.org/pdf/2305.18002v3.pdf	https://github.com/ahsarantaris/tropical-phase-plane	true	true	true	none
https://paperswithcode.com/paper/a-large-scale-empirical-study-on-semantic	A Large-Scale Empirical Study on Semantic Versioning in Golang Ecosystem	2309.02894	https://arxiv.org/abs/2309.02894v2	https://arxiv.org/pdf/2309.02894v2.pdf	https://github.com/liwenke1/GoSVI	true	true	false	none
https://paperswithcode.com/paper/nearest-neighbor-and-kernel-survival-analysis	Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates	1905.05285	https://arxiv.org/abs/1905.05285v2	https://arxiv.org/pdf/1905.05285v2.pdf	https://github.com/georgehc/npsurvival	false	false	true	none
https://paperswithcode.com/paper/revisiting-ensembling-in-one-shot-federated	Revisiting Ensembling in One-Shot Federated Learning	2411.07182	https://arxiv.org/abs/2411.07182v1	https://arxiv.org/pdf/2411.07182v1.pdf	https://github.com/sacs-epfl/fens	true	true	false	pytorch
https://paperswithcode.com/paper/estimating-lexical-complexity-from-document	Estimating Lexical Complexity from Document-Level Distributions	2404.01196	https://arxiv.org/abs/2404.01196v1	https://arxiv.org/pdf/2404.01196v1.pdf	https://github.com/sondrewold/lexical_complexity_estimation	true	true	true	none
https://paperswithcode.com/paper/liquid-structural-state-space-models	Liquid Structural State-Space Models	2209.12951	https://arxiv.org/abs/2209.12951v1	https://arxiv.org/pdf/2209.12951v1.pdf	https://github.com/raminmh/liquid-s4	true	true	true	pytorch
https://paperswithcode.com/paper/towards-effective-ancient-chinese-translation	Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation	2308.00240	https://arxiv.org/abs/2308.00240v1	https://arxiv.org/pdf/2308.00240v1.pdf	https://github.com/rucaibox/erya	true	true	false	none
https://paperswithcode.com/paper/generative-downscaling-of-pde-solvers-with	Generative downscaling of PDE solvers with physics-guided diffusion models	2404.05009	https://arxiv.org/abs/2404.05009v1	https://arxiv.org/pdf/2404.05009v1.pdf	https://github.com/woodssss/generative-downsscaling-pde-solvers	true	true	true	pytorch
https://paperswithcode.com/paper/training-neural-networks-as-recognizers-of	Training Neural Networks as Recognizers of Formal Languages	2411.07107	https://arxiv.org/abs/2411.07107v1	https://arxiv.org/pdf/2411.07107v1.pdf	https://github.com/rycolab/flare	true	true	false	none
https://paperswithcode.com/paper/training-neural-networks-as-recognizers-of	Training Neural Networks as Recognizers of Formal Languages	2411.07107	https://arxiv.org/abs/2411.07107v1	https://arxiv.org/pdf/2411.07107v1.pdf	https://github.com/rycolab/neural-network-recognizers	true	true	false	none
https://paperswithcode.com/paper/xgbd-explanation-guided-graph-backdoor	XGBD: Explanation-Guided Graph Backdoor Detection	2308.04406	https://arxiv.org/abs/2308.04406v1	https://arxiv.org/pdf/2308.04406v1.pdf	https://github.com/guanzihan/gnn_backdoor_detection	true	true	false	pytorch
https://paperswithcode.com/paper/improved-benthic-classification-using	Improved Benthic Classification using Resolution Scaling and SymmNet Unsupervised Domain Adaptation	2303.10960	https://arxiv.org/abs/2303.10960v1	https://arxiv.org/pdf/2303.10960v1.pdf	https://github.com/hdoi5324/benthic-uda	true	true	true	pytorch
https://paperswithcode.com/paper/structural-attention-rethinking-transformer	Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis	2406.18967	https://arxiv.org/abs/2406.18967v2	https://arxiv.org/pdf/2406.18967v2.pdf	https://github.com/hieuphan33/miccai2024-unest	true	true	false	pytorch
https://paperswithcode.com/paper/mamba-linear-time-sequence-modeling-with	Mamba: Linear-Time Sequence Modeling with Selective State Spaces	2312.00752	https://arxiv.org/abs/2312.00752v2	https://arxiv.org/pdf/2312.00752v2.pdf	https://github.com/mzeromiko/vmamba	false	false	true	pytorch
https://paperswithcode.com/paper/tc-gnn-accelerating-sparse-graph-neural	TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs	2112.02052	https://arxiv.org/abs/2112.02052v4	https://arxiv.org/pdf/2112.02052v4.pdf	https://github.com/YukeWang96/TCGNN-Pytorch	true	true	true	pytorch
https://paperswithcode.com/paper/attribute-descent-simulating-object-centric	Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond	2202.14034	https://arxiv.org/abs/2202.14034v2	https://arxiv.org/pdf/2202.14034v2.pdf	https://github.com/yorkeyao/VehicleX	true	true	false	pytorch
https://paperswithcode.com/paper/potter-pooling-attention-transformer-for	POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery	2303.13357	https://arxiv.org/abs/2303.13357v1	https://arxiv.org/pdf/2303.13357v1.pdf	https://github.com/zczcwh/potter	false	false	true	pytorch
https://paperswithcode.com/paper/minority-oriented-vicinity-expansion-with	Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition	2211.13471	https://arxiv.org/abs/2211.13471v1	https://arxiv.org/pdf/2211.13471v1.pdf	https://github.com/wjun0830/move	true	true	true	pytorch
https://paperswithcode.com/paper/py-gwbse-a-high-throughput-workflow-package	$py$GWBSE: A high throughput workflow package for GW-BSE calculations	2210.00152	https://arxiv.org/abs/2210.00152v2	https://arxiv.org/pdf/2210.00152v2.pdf	https://github.com/cmdlab/pygwbse	true	true	true	none
https://paperswithcode.com/paper/iterative-graph-alignment	Iterative Graph Alignment	2408.16667	https://arxiv.org/abs/2408.16667v1	https://arxiv.org/pdf/2408.16667v1.pdf	https://github.com/fangyuan-ksgk/ruleeval	true	true	true	none
https://paperswithcode.com/paper/hyperparameter-optimization-for-ast	Hyperparameter Optimization for AST Differencing	2011.10268	https://arxiv.org/abs/2011.10268v3	https://arxiv.org/pdf/2011.10268v3.pdf	https://github.com/GumTreeDiff/gumtree	true	true	false	none
https://paperswithcode.com/paper/improve-long-term-memory-learning-through	Improve Long-term Memory Learning Through Rescaling the Error Temporally	2307.11462	https://arxiv.org/abs/2307.11462v1	https://arxiv.org/pdf/2307.11462v1.pdf	https://github.com/radarFudan/INTEREST	false	false	true	pytorch
https://paperswithcode.com/paper/generative-modeling-helps-weak-supervision	Generative Modeling Helps Weak Supervision (and Vice Versa)	2203.12023	https://arxiv.org/abs/2203.12023v6	https://arxiv.org/pdf/2203.12023v6.pdf	https://github.com/benbo/wsgan-paper	true	true	true	pytorch
https://paperswithcode.com/paper/magic-nerf-lens-interactive-fusion-of-neural	Magic NeRF Lens: Interactive Fusion of Neural Radiance Fields for Virtual Facility Inspection	2307.09860	https://arxiv.org/abs/2307.09860v1	https://arxiv.org/pdf/2307.09860v1.pdf	https://github.com/uhhhci/immersive-ngp	true	true	true	none
https://paperswithcode.com/paper/bayesian-optimized-monte-carlo-planning	Bayesian Optimized Monte Carlo Planning	2010.03597	https://arxiv.org/abs/2010.03597v1	https://arxiv.org/pdf/2010.03597v1.pdf	https://github.com/sisl/BOMCP.jl	false	false	true	none
https://paperswithcode.com/paper/from-sparse-to-soft-mixtures-of-experts	From Sparse to Soft Mixtures of Experts	2308.00951	https://arxiv.org/abs/2308.00951v2	https://arxiv.org/pdf/2308.00951v2.pdf	https://github.com/fkodom/soft-mixture-of-experts	false	false	true	pytorch
https://paperswithcode.com/paper/learning-to-paraphrase-sentences-to-different	Learning to Paraphrase Sentences to Different Complexity Levels	2308.02226	https://arxiv.org/abs/2308.02226v1	https://arxiv.org/pdf/2308.02226v1.pdf	https://github.com/alisonhc/change-complexity	true	true	true	pytorch
https://paperswithcode.com/paper/distilbert-a-distilled-version-of-bert	DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter	1910.01108	https://arxiv.org/abs/1910.01108v4	https://arxiv.org/pdf/1910.01108v4.pdf	https://github.com/philschmid/knowledge-distillation-transformers-pytorch-sagemaker	false	false	true	pytorch
https://paperswithcode.com/paper/fastformers-highly-efficient-transformer	FastFormers: Highly Efficient Transformer Models for Natural Language Understanding	2010.13382	https://arxiv.org/abs/2010.13382v1	https://arxiv.org/pdf/2010.13382v1.pdf	https://github.com/philschmid/knowledge-distillation-transformers-pytorch-sagemaker	false	false	true	pytorch
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/MindSpore-paper-code-3/code5/tree/main/res2net_yolov3	false	false	false	mindspore
https://paperswithcode.com/paper/adarevd-adaptive-patch-exiting-reversible-1	AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring	2406.09135	https://arxiv.org/abs/2406.09135v1	https://arxiv.org/pdf/2406.09135v1.pdf	https://github.com/INVOKERer/AdaRevD	true	false	false	pytorch
https://paperswithcode.com/paper/rethinking-uncertainly-missing-and-ambiguous	Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment	2307.16210	https://arxiv.org/abs/2307.16210v2	https://arxiv.org/pdf/2307.16210v2.pdf	https://github.com/zjukg/umaea	false	true	true	pytorch
https://paperswithcode.com/paper/better-speech-synthesis-through-scaling	Better speech synthesis through scaling	2305.07243	https://arxiv.org/abs/2305.07243v2	https://arxiv.org/pdf/2305.07243v2.pdf	https://github.com/neonbjb/tortoise-tts	true	true	true	pytorch
https://paperswithcode.com/paper/synthesis-of-separation-processes-with	Synthesis of separation processes with reinforcement learning	2211.04327	https://arxiv.org/abs/2211.04327v1	https://arxiv.org/pdf/2211.04327v1.pdf	https://github.com/lollcat/aspen-rl	true	true	true	jax
https://paperswithcode.com/paper/it5-large-scale-text-to-text-pretraining-for	IT5: Text-to-text Pretraining for Italian Language Understanding and Generation	2203.03759	https://arxiv.org/abs/2203.03759v2	https://arxiv.org/pdf/2203.03759v2.pdf	https://github.com/MrFeelgoood/RealEstateStocksForecasting	false	false	true	none
https://paperswithcode.com/paper/optimal-sample-size-planning-for-the-wilcoxon	Optimal Sample Size Planning for the Wilcoxon-Mann-Whitney-Test	1805.12249	http://arxiv.org/abs/1805.12249v1	http://arxiv.org/pdf/1805.12249v1.pdf	https://github.com/cran/WMWssp	false	false	true	none
https://paperswithcode.com/paper/deformation-equivariant-cross-modality-image	Deformation equivariant cross-modality image synthesis with paired non-aligned training data	2208.12491	https://arxiv.org/abs/2208.12491v2	https://arxiv.org/pdf/2208.12491v2.pdf	https://github.com/honkamj/non-aligned-i2i	true	true	false	pytorch
https://paperswithcode.com/paper/generalized-laplacian-regularized-framelet	Generalized Laplacian Regularized Framelet Graph Neural Networks	2210.15092	https://arxiv.org/abs/2210.15092v2	https://arxiv.org/pdf/2210.15092v2.pdf	https://github.com/superca729/pl-ufg	true	true	false	pytorch
https://paperswithcode.com/paper/a-quantum-of-quic-dissecting-cryptography	A Quantum of QUIC: Dissecting Cryptography with Post-Quantum Insights	2405.09264	https://arxiv.org/abs/2405.09264v1	https://arxiv.org/pdf/2405.09264v1.pdf	https://github.com/tumi8/quic-crypto-paper	true	true	false	none
https://paperswithcode.com/paper/scaling-inference-time-search-with-vision	Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension	2412.03704	https://arxiv.org/abs/2412.03704v2	https://arxiv.org/pdf/2412.03704v2.pdf	https://github.com/si0wang/visvm	true	true	false	pytorch
https://paperswithcode.com/paper/compose-and-conquer-diffusion-based-3d-depth	Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis	2401.09048	https://arxiv.org/abs/2401.09048v1	https://arxiv.org/pdf/2401.09048v1.pdf	https://github.com/tomtom1103/compose-and-conquer	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.