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/dynamic-graph-cnn-for-learning-on-point	Dynamic Graph CNN for Learning on Point Clouds	1801.07829	https://arxiv.org/abs/1801.07829v2	https://arxiv.org/pdf/1801.07829v2.pdf	https://gitee.com/gai-shaoyan/mind3d	false	false	false	none
https://paperswithcode.com/paper/analyzing-noise-models-and-advanced-filtering	Analyzing Noise Models and Advanced Filtering Algorithms for Image Enhancement	2410.21946	https://arxiv.org/abs/2410.21946v2	https://arxiv.org/pdf/2410.21946v2.pdf	https://github.com/SahilAliAkbar/Image_Noise_Analysis	true	false	false	none
https://paperswithcode.com/paper/subtractive-aggregation-for-attributed	Subtractive Aggregation for Attributed Network Anomaly Detection	null	https://dl.acm.org/doi/10.1145/3459637.3482195	https://dl.acm.org/doi/10.1145/3459637.3482195	https://github.com/betterzhou/AAGNN	false	false	false	pytorch
https://paperswithcode.com/paper/realtime-person-identification-via-gait	Realtime Person Identification via Gait Analysis	2404.15312	https://arxiv.org/abs/2404.15312v1	https://arxiv.org/pdf/2404.15312v1.pdf	https://github.com/ahmadrida9999/ahmad	false	false	false	none
https://paperswithcode.com/paper/fishdbc-flexible-incremental-scalable	FISHDBC: Flexible, Incremental, Scalable, Hierarchical Density-Based Clustering for Arbitrary Data and Distance	1910.07283	https://arxiv.org/abs/1910.07283v1	https://arxiv.org/pdf/1910.07283v1.pdf	https://github.com/matteodellamico/flexible-clustering	true	true	true	none
https://paperswithcode.com/paper/discontinuous-response-of-the-epidemic-peak	Discontinuous epidemic transition due to limited testing	2006.08005	https://arxiv.org/abs/2006.08005v3	https://arxiv.org/pdf/2006.08005v3.pdf	https://github.com/burakbudanur/gridemic	false	false	true	none
https://paperswithcode.com/paper/heterogeneous-random-forest	Heterogeneous Random Forest	2410.19022	https://arxiv.org/abs/2410.19022v1	https://arxiv.org/pdf/2410.19022v1.pdf	https://github.com/KimYenny/HeterogeneousRF	true	false	false	none
https://paperswithcode.com/paper/probing-the-effects-of-broken-symmetries-in	Probing the effects of broken symmetries in machine learning	2406.17747	https://arxiv.org/abs/2406.17747v1	https://arxiv.org/pdf/2406.17747v1.pdf	https://github.com/spozdn/pet	true	false	false	pytorch
https://paperswithcode.com/paper/example-based-hypernetworks-for-out-of	Example-based Hypernetworks for Out-of-Distribution Generalization	2203.14276	https://arxiv.org/abs/2203.14276v3	https://arxiv.org/pdf/2203.14276v3.pdf	https://github.com/tomervolk/hyper-pada	true	true	true	pytorch
https://paperswithcode.com/paper/conformal-prediction-sets-with-limited-false	Conformal Prediction Sets with Limited False Positives	2202.07650	https://arxiv.org/abs/2202.07650v1	https://arxiv.org/pdf/2202.07650v1.pdf	https://github.com/ajfisch/conformal-fp	true	true	true	pytorch
https://paperswithcode.com/paper/contrast-with-reconstruct-contrastive-3d	Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining	2302.02318	https://arxiv.org/abs/2302.02318v2	https://arxiv.org/pdf/2302.02318v2.pdf	https://github.com/runpeidong/act	false	false	true	pytorch
https://paperswithcode.com/paper/bag-of-words-vs-sequence-vs-graph-vs	Are We Really Making Much Progress in Text Classification? A Comparative Review	2204.03954	https://arxiv.org/abs/2204.03954v6	https://arxiv.org/pdf/2204.03954v6.pdf	https://github.com/drndr/multilabel-text-clf	true	true	false	pytorch
https://paperswithcode.com/paper/model-agnostic-meta-learning-for-fast	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	1703.03400	http://arxiv.org/abs/1703.03400v3	http://arxiv.org/pdf/1703.03400v3.pdf	https://github.com/Mind23-2/MindCode-55	false	false	true	mindspore
https://paperswithcode.com/paper/can-physics-informed-neural-networks-beat-the	Can Physics-Informed Neural Networks beat the Finite Element Method?	2302.04107	https://arxiv.org/abs/2302.04107v1	https://arxiv.org/pdf/2302.04107v1.pdf	https://github.com/tamaragrossmann/fem-vs-pinns	true	true	true	jax
https://paperswithcode.com/paper/maxvit-unet-multi-axis-attention-for-medical	MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation	2305.08396	https://arxiv.org/abs/2305.08396v5	https://arxiv.org/pdf/2305.08396v5.pdf	https://github.com/abdul2706/MaxViT-UNet	true	false	true	pytorch
https://paperswithcode.com/paper/safe-deep-policy-adaptation	Safe Deep Policy Adaptation	2310.08602	https://arxiv.org/abs/2310.08602v3	https://arxiv.org/pdf/2310.08602v3.pdf	https://github.com/LeCAR-Lab/SafeDPA	true	false	false	none
https://paperswithcode.com/paper/on-pre-training-for-federated-learning	On the Importance and Applicability of Pre-Training for Federated Learning	2206.11488	https://arxiv.org/abs/2206.11488v3	https://arxiv.org/pdf/2206.11488v3.pdf	https://github.com/andytu28/fps_pre-training	true	true	true	pytorch
https://paperswithcode.com/paper/calibrated-out-of-distribution-detection-with	Calibrated Out-of-Distribution Detection with a Generic Representation	2303.13148	https://arxiv.org/abs/2303.13148v2	https://arxiv.org/pdf/2303.13148v2.pdf	https://github.com/vojirt/grood	true	true	true	pytorch
https://paperswithcode.com/paper/3d-dda-3d-dual-domain-attention-for-brain	3D-DDA: 3D Dual-Domain Attention for Brain Tumor Segmentation	null	https://ieeexplore.ieee.org/document/10222602	https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10222602	https://github.com/sowwnn/3DDualDomainAttention	false	false	false	pytorch
https://paperswithcode.com/paper/fingerprinting-web-servers-through	Fingerprinting web servers through Transformer-encoded HTTP response headers	2404.00056	https://arxiv.org/abs/2404.00056v1	https://arxiv.org/pdf/2404.00056v1.pdf	https://github.com/Darwinkel/bachelor-thesis-information-science	true	true	false	none
https://paperswithcode.com/paper/udapter-efficient-domain-adaptation-using	UDApter -- Efficient Domain Adaptation Using Adapters	2302.03194	https://arxiv.org/abs/2302.03194v2	https://arxiv.org/pdf/2302.03194v2.pdf	https://github.com/declare-lab/domadapter	true	true	true	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/lucidrains/vector-quantize-pytorch	false	false	false	pytorch
https://paperswithcode.com/paper/co-active-subspace-methods-for-the-joint	Co-Active Subspace Methods for the Joint Analysis of Adjacent Computer Models	2311.18146	https://arxiv.org/abs/2311.18146v2	https://arxiv.org/pdf/2311.18146v2.pdf	https://github.com/knrumsey/concordance	true	true	false	none
https://paperswithcode.com/paper/cam-a-fast-and-efficient-network-for-speaker	CAM++: A Fast and Efficient Network for Speaker Verification Using Context-Aware Masking	2303.00332	https://arxiv.org/abs/2303.00332v3	https://arxiv.org/pdf/2303.00332v3.pdf	https://github.com/yuyq96/d-tdnn	false	false	true	pytorch
https://paperswithcode.com/paper/splitnerf-split-sum-approximation-neural	SplitNeRF: Split Sum Approximation Neural Field for Joint Geometry, Illumination, and Material Estimation	2311.16671	https://arxiv.org/abs/2311.16671v1	https://arxiv.org/pdf/2311.16671v1.pdf	https://github.com/zarzarj/SplitNeRF	true	false	true	pytorch
https://paperswithcode.com/paper/bayesian-nonparametric-inference-in-pde	Bayesian Nonparametric Inference in Elliptic PDEs: Convergence Rates and Implementation	2311.18322	https://arxiv.org/abs/2311.18322v2	https://arxiv.org/pdf/2311.18322v2.pdf	https://github.com/mattgiord/bayesian-inverse-problems	true	true	false	none
https://paperswithcode.com/paper/a-database-for-perceived-quality-assessment	Perceptual Quality Assessment of Virtual Reality Videos in the Wild	2206.08751	https://arxiv.org/abs/2206.08751v3	https://arxiv.org/pdf/2206.08751v3.pdf	https://github.com/limuhit/vr-video-quality-in-the-wild	true	true	false	pytorch
https://paperswithcode.com/paper/the-extended-hoa-format-for-synthesis	The Extended HOA Format for Synthesis	1912.05793	https://arxiv.org/abs/1912.05793v2	https://arxiv.org/pdf/1912.05793v2.pdf	https://github.com/SYNTCOMP/hoa-tools	false	false	true	none
https://paperswithcode.com/paper/structure-adaptive-elastic-net	Structure Adaptive Elastic-Net	2006.02041	https://arxiv.org/abs/2006.02041v3	https://arxiv.org/pdf/2006.02041v3.pdf	https://github.com/sandy-pramanik/saenet	true	true	false	none
https://paperswithcode.com/paper/predicting-workload-in-virtual-flight	Predicting Workload in Virtual Flight Simulations using EEG Features (Including Post-hoc Analysis in Appendix)	2412.12428	https://arxiv.org/abs/2412.12428v2	https://arxiv.org/pdf/2412.12428v2.pdf	https://github.com/basverkennis/flight-sim-cognitive-workload-eeg-prediction	true	true	false	none
https://paperswithcode.com/paper/bayesian-low-rank-adaptation-for-large	Bayesian Low-rank Adaptation for Large Language Models	2308.13111	https://arxiv.org/abs/2308.13111v5	https://arxiv.org/pdf/2308.13111v5.pdf	https://github.com/maximerobeyns/bayesian_lora	true	true	false	pytorch
https://paperswithcode.com/paper/multi-correlation-siamese-transformer-network	Multi-Correlation Siamese Transformer Network with Dense Connection for 3D Single Object Tracking	2312.11051	https://arxiv.org/abs/2312.11051v1	https://arxiv.org/pdf/2312.11051v1.pdf	https://github.com/liangp/mcstn-3dsot	true	true	false	pytorch
https://paperswithcode.com/paper/organelle-specific-segmentation-spatial	Organelle-specific segmentation, spatial analysis, and visualization of volume electron microscopy datasets	2303.03876	https://arxiv.org/abs/2303.03876v1	https://arxiv.org/pdf/2303.03876v1.pdf	https://gitlab.com/album-app/album	true	true	false	none
https://paperswithcode.com/paper/fft-based-dynamic-token-mixer-for-vision	FFT-based Dynamic Token Mixer for Vision	2303.03932	https://arxiv.org/abs/2303.03932v2	https://arxiv.org/pdf/2303.03932v2.pdf	https://github.com/okojoalg/dfformer	true	true	true	pytorch
https://paperswithcode.com/paper/integrated-image-and-location-analysis-for	Integrated Image and Location Analysis for Wound Classification: A Deep Learning Approach	2308.11877	https://arxiv.org/abs/2308.11877v2	https://arxiv.org/pdf/2308.11877v2.pdf	https://github.com/uwm-bigdata/multi-modal-wound-classification-using-images-and-locations	true	true	false	none
https://paperswithcode.com/paper/rm-e-3-equivariant-actor-critic-methods-for	${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning	2308.11842	https://arxiv.org/abs/2308.11842v3	https://arxiv.org/pdf/2308.11842v3.pdf	https://github.com/dchen48/e3ac	true	true	false	pytorch
https://paperswithcode.com/paper/facediffuser-speech-driven-3d-facial	FaceDiffuser: Speech-Driven 3D Facial Animation Synthesis Using Diffusion	2309.11306	https://arxiv.org/abs/2309.11306v1	https://arxiv.org/pdf/2309.11306v1.pdf	https://github.com/uuembodiedsocialai/FaceDiffuser	true	true	false	jax
https://paperswithcode.com/paper/wdd-weighted-delta-debugging	WDD: Weighted Delta Debugging	2411.19410	https://arxiv.org/abs/2411.19410v2	https://arxiv.org/pdf/2411.19410v2.pdf	https://github.com/uw-pluverse/perses	true	true	false	none
https://paperswithcode.com/paper/the-three-channels-of-many-body-perturbation	The three channels of many-body perturbation theory: $GW$, particle-particle, and electron-hole $T$-matrix self-energies	2309.04167	https://arxiv.org/abs/2309.04167v3	https://arxiv.org/pdf/2309.04167v3.pdf	https://github.com/pfloos/QuAcK	true	true	false	none
https://paperswithcode.com/paper/generative-adversarial-networks	Generative Adversarial Networks	1406.2661	https://arxiv.org/abs/1406.2661v1	https://arxiv.org/pdf/1406.2661v1.pdf	https://github.com/2024-MindSpore-1/Code5/tree/main/APDrawingGAN	false	false	false	mindspore
https://paperswithcode.com/paper/a-simple-baseline-for-batch-active-learning	Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning	2106.12059	https://arxiv.org/abs/2106.12059v3	https://arxiv.org/pdf/2106.12059v3.pdf	https://github.com/baal-org/baal	true	true	true	pytorch
https://paperswithcode.com/paper/head-tail-breaks-a-new-classification-scheme	Head/tail Breaks: A New Classification Scheme for Data with a Heavy-tailed Distribution	1209.2801	https://arxiv.org/abs/1209.2801v1	https://arxiv.org/pdf/1209.2801v1.pdf	https://github.com/r-spatial/classInt	false	false	true	none
https://paperswithcode.com/paper/deep-recurrent-q-learning-for-partially	Deep Recurrent Q-Learning for Partially Observable MDPs	1507.06527	http://arxiv.org/abs/1507.06527v4	http://arxiv.org/pdf/1507.06527v4.pdf	https://github.com/kevslinger/dtqn	false	false	true	pytorch
https://paperswithcode.com/paper/star-tracking-using-an-event-camera	Star Tracking using an Event Camera	1812.02895	http://arxiv.org/abs/1812.02895v2	http://arxiv.org/pdf/1812.02895v2.pdf	https://github.com/uzh-rpg/event-based_vision_resources	true	true	true	pytorch
https://paperswithcode.com/paper/exploiting-structural-and-semantic-context	Commonsense Knowledge Base Completion with Structural and Semantic Context	1910.02915	https://arxiv.org/abs/1910.02915v2	https://arxiv.org/pdf/1910.02915v2.pdf	https://github.com/allenai/commonsense-kg-completion	false	false	true	pytorch
https://paperswithcode.com/paper/altered-topological-structure-of-the-brain	Altered Topological Structure of the Brain White Matter in Maltreated Children through Topological Data Analysis	2304.05908	https://arxiv.org/abs/2304.05908v3	https://arxiv.org/pdf/2304.05908v3.pdf	https://github.com/laplcebeltrami/maltreated	true	true	false	none
https://paperswithcode.com/paper/phavip-phage-virion-protein-classification	PhaVIP: Phage VIrion Protein classification based on chaos game representation and Vision Transformer	2301.12422	https://arxiv.org/abs/2301.12422v2	https://arxiv.org/pdf/2301.12422v2.pdf	https://github.com/kennthshang/phavip	true	true	true	pytorch
https://paperswithcode.com/paper/it-takes-two-to-negotiate-modeling-social	It Takes Two to Negotiate: Modeling Social Exchange in Online Multiplayer Games	2311.08666	https://arxiv.org/abs/2311.08666v1	https://arxiv.org/pdf/2311.08666v1.pdf	https://github.com/kj2013/claff-diplomacy	true	true	false	none
https://paperswithcode.com/paper/sculpting-features-from-noise-reward-guided	Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation	2505.15152	https://arxiv.org/abs/2505.15152v1	https://arxiv.org/pdf/2505.15152v1.pdf	https://github.com/NanxuGong/DIFFT	true	false	false	pytorch
https://paperswithcode.com/paper/egg-fast-and-extensible-equality-saturation	egg: Fast and Extensible Equality Saturation	2004.03082	https://arxiv.org/abs/2004.03082v3	https://arxiv.org/pdf/2004.03082v3.pdf	https://github.com/jcberentsen/egg-nog	false	false	true	none
https://paperswithcode.com/paper/selectivenet-a-deep-neural-network-with-an	SelectiveNet: A Deep Neural Network with an Integrated Reject Option	1901.09192	https://arxiv.org/abs/1901.09192v4	https://arxiv.org/pdf/1901.09192v4.pdf	https://github.com/BorealisAI/towards-better-sel-cls	false	false	true	pytorch
https://paperswithcode.com/paper/deep-gamblers-learning-to-abstain-with	Deep Gamblers: Learning to Abstain with Portfolio Theory	1907.00208	https://arxiv.org/abs/1907.00208v2	https://arxiv.org/pdf/1907.00208v2.pdf	https://github.com/BorealisAI/towards-better-sel-cls	false	false	true	pytorch
https://paperswithcode.com/paper/constyle-v2-a-strong-prompter-for-all-in-one	ConStyle v2: A Strong Prompter for All-in-One Image Restoration	2406.18242	https://arxiv.org/abs/2406.18242v1	https://arxiv.org/pdf/2406.18242v1.pdf	https://github.com/Dongqi-Fan/ConStyle_v2	true	true	false	pytorch
https://paperswithcode.com/paper/compressai-a-pytorch-library-and-evaluation	CompressAI: a PyTorch library and evaluation platform for end-to-end compression research	2011.03029	https://arxiv.org/abs/2011.03029v1	https://arxiv.org/pdf/2011.03029v1.pdf	https://github.com/xinjie-q/ldmic	false	false	true	pytorch
https://paperswithcode.com/paper/spores-sum-product-optimization-via	SPORES: Sum-Product Optimization via Relational Equality Saturation for Large Scale Linear Algebra	2002.07951	https://arxiv.org/abs/2002.07951v2	https://arxiv.org/pdf/2002.07951v2.pdf	https://github.com/jcberentsen/egg-nog	false	false	true	none
https://paperswithcode.com/paper/accommodating-audio-modality-in-clip-for	Accommodating Audio Modality in CLIP for Multimodal Processing	2303.06591	https://arxiv.org/abs/2303.06591v1	https://arxiv.org/pdf/2303.06591v1.pdf	https://github.com/ludanruan/clip4vla	true	true	true	pytorch
https://paperswithcode.com/paper/transformer-encoder-with-multiscale-deep	Transformer Encoder with Multiscale Deep Learning for Pain Classification Using Physiological Signals	2303.06845	https://arxiv.org/abs/2303.06845v2	https://arxiv.org/pdf/2303.06845v2.pdf	https://github.com/zhenyuanlu/painattnnet	true	true	true	pytorch
https://paperswithcode.com/paper/ldmic-learning-based-distributed-multi-view	LDMIC: Learning-based Distributed Multi-view Image Coding	2301.09799	https://arxiv.org/abs/2301.09799v3	https://arxiv.org/pdf/2301.09799v3.pdf	https://github.com/xinjie-q/ldmic	true	true	true	pytorch
https://paperswithcode.com/paper/pet-neus-positional-encoding-tri-planes-for	PET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces	2305.05594	https://arxiv.org/abs/2305.05594v1	https://arxiv.org/pdf/2305.05594v1.pdf	https://github.com/yiqun-wang/pet-neus	true	true	true	pytorch
https://paperswithcode.com/paper/cosmological-measurements-from-void-galaxy	Cosmological measurements from void-galaxy and galaxy-galaxy clustering in the Sloan Digital Sky Survey	2303.06143	https://arxiv.org/abs/2303.06143v2	https://arxiv.org/pdf/2303.06143v2.pdf	https://github.com/alexwoodfinden/sdss-void-cosmology	true	true	true	none
https://paperswithcode.com/paper/transcription-free-filler-word-detection-with	Transcription free filler word detection with Neural semi-CRFs	2303.06475	https://arxiv.org/abs/2303.06475v1	https://arxiv.org/pdf/2303.06475v1.pdf	https://github.com/gzhu06/Filler-semi-CRF	true	true	true	pytorch
https://paperswithcode.com/paper/checkerboard-context-model-for-efficient	Checkerboard Context Model for Efficient Learned Image Compression	2103.15306	https://arxiv.org/abs/2103.15306v2	https://arxiv.org/pdf/2103.15306v2.pdf	https://github.com/xinjie-q/ldmic	false	false	true	pytorch
https://paperswithcode.com/paper/caloclouds-ii-ultra-fast-geometry-independent	CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation	2309.05704	https://arxiv.org/abs/2309.05704v2	https://arxiv.org/pdf/2309.05704v2.pdf	https://github.com/flc-qu-hep/caloclouds-2	true	true	true	pytorch
https://paperswithcode.com/paper/unsupervised-domain-adaptation-for-cardiac	Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization	2204.09334	https://arxiv.org/abs/2204.09334v3	https://arxiv.org/pdf/2204.09334v3.pdf	https://github.com/louey233/toward-mutual-information	true	true	true	pytorch
https://paperswithcode.com/paper/towards-safe-bayesian-optimization-with	Towards safe Bayesian optimization with Wiener kernel regression	2411.02253	https://arxiv.org/abs/2411.02253v3	https://arxiv.org/pdf/2411.02253v3.pdf	https://github.com/OptCon/SafeBO_WKR	true	false	true	none
https://paperswithcode.com/paper/the-distributional-hypothesis-does-not-fully	The Distributional Hypothesis Does Not Fully Explain the Benefits of Masked Language Model Pretraining	2310.16261	https://arxiv.org/abs/2310.16261v1	https://arxiv.org/pdf/2310.16261v1.pdf	https://github.com/usc-tamagotchi/dh-mlm	true	true	false	pytorch
https://paperswithcode.com/paper/iocr-informed-optical-character-recognition	iOCR: Informed Optical Character Recognition for Election Ballot Tallies	2208.00865	https://arxiv.org/abs/2208.00865v1	https://arxiv.org/pdf/2208.00865v1.pdf	https://github.com/wolfgarbe/symspell	true	true	true	none
https://paperswithcode.com/paper/high-dimensional-overdispersed-generalized	High-Dimensional Overdispersed Generalized Factor Model with Application to Single-Cell Sequencing Data Analysis	2408.11272	https://arxiv.org/abs/2408.11272v1	https://arxiv.org/pdf/2408.11272v1.pdf	https://github.com/feiyoung/GFM	true	false	false	none
https://paperswithcode.com/paper/evaluating-physics-informed-neural-network	Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquakes and Explosions	2403.04952	https://arxiv.org/abs/2403.04952v1	https://arxiv.org/pdf/2403.04952v1.pdf	https://github.com/qingkaikong/physicsml-pinn-empiricalrelationship	true	true	true	none
https://paperswithcode.com/paper/harnessing-the-power-of-large-language-model	Harnessing the Power of Large Language Model for Uncertainty Aware Graph Processing	2404.00589	https://arxiv.org/abs/2404.00589v2	https://arxiv.org/pdf/2404.00589v2.pdf	https://github.com/code4paper-2024/code4paper	true	true	false	pytorch
https://paperswithcode.com/paper/cm-tts-enhancing-real-time-text-to-speech	CM-TTS: Enhancing Real Time Text-to-Speech Synthesis Efficiency through Weighted Samplers and Consistency Models	2404.00569	https://arxiv.org/abs/2404.00569v1	https://arxiv.org/pdf/2404.00569v1.pdf	https://github.com/xiangli2022/cm-tts	true	true	false	pytorch
https://paperswithcode.com/paper/multimedia-generative-script-learning-for	Multimedia Generative Script Learning for Task Planning	2208.12306	https://arxiv.org/abs/2208.12306v3	https://arxiv.org/pdf/2208.12306v3.pdf	https://github.com/EagleW/Multimedia-Generative-Script-Learning-for-Task-Planning	true	false	true	pytorch
https://paperswithcode.com/paper/lswinsr-uav-imagery-super-resolution-based-on	LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer	2303.10232	https://arxiv.org/abs/2303.10232v1	https://arxiv.org/pdf/2303.10232v1.pdf	https://github.com/lironui/geosr	true	true	true	pytorch
https://paperswithcode.com/paper/short-time-ssvep-data-extension-by-a-novel	Short-length SSVEP data extension by a novel generative adversarial networks based framework	2301.05599	https://arxiv.org/abs/2301.05599v5	https://arxiv.org/pdf/2301.05599v5.pdf	https://github.com/yudongpan/tegan	true	true	false	pytorch
https://paperswithcode.com/paper/bridging-the-gap-between-model-explanations	Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification	2304.01804	https://arxiv.org/abs/2304.01804v1	https://arxiv.org/pdf/2304.01804v1.pdf	https://github.com/youngwk/bridgegapexplanationpamc	true	true	true	pytorch
https://paperswithcode.com/paper/one-shot-unsupervised-domain-adaptation-with	One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models	2303.18080	https://arxiv.org/abs/2303.18080v2	https://arxiv.org/pdf/2303.18080v2.pdf	https://github.com/yasserben/datum	true	true	true	pytorch
https://paperswithcode.com/paper/reliaavatar-a-robust-real-time-avatar	ReliaAvatar: A Robust Real-Time Avatar Animator with Integrated Motion Prediction	2407.02129	https://arxiv.org/abs/2407.02129v1	https://arxiv.org/pdf/2407.02129v1.pdf	https://github.com/MindSpore-scientific-2/code-7/tree/main/DocREfiner	false	false	false	mindspore
https://paperswithcode.com/paper/learning-to-defer-to-multiple-experts	Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles	2210.16955	https://arxiv.org/abs/2210.16955v2	https://arxiv.org/pdf/2210.16955v2.pdf	https://github.com/rajevv/multi_l2d	true	true	true	pytorch
https://paperswithcode.com/paper/translist-a-transformer-based-linguistically	TransLIST: A Transformer-Based Linguistically Informed Sanskrit Tokenizer	2210.11753	https://arxiv.org/abs/2210.11753v1	https://arxiv.org/pdf/2210.11753v1.pdf	https://github.com/rsingha108/translist	true	true	true	pytorch
https://paperswithcode.com/paper/q-net-query-informed-few-shot-medical-image	Q-Net: Query-Informed Few-Shot Medical Image Segmentation	2208.11451	https://arxiv.org/abs/2208.11451v3	https://arxiv.org/pdf/2208.11451v3.pdf	https://github.com/zjlab-ammi/q-net	true	true	true	pytorch
https://paperswithcode.com/paper/self-supervision-with-superpixels-training	Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation	2007.09886	https://arxiv.org/abs/2007.09886v2	https://arxiv.org/pdf/2007.09886v2.pdf	https://github.com/zjlab-ammi/q-net	false	false	true	pytorch
https://paperswithcode.com/paper/damo-nlp-at-semeval-2023-task-2-a-unified	DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition	2305.03688	https://arxiv.org/abs/2305.03688v3	https://arxiv.org/pdf/2305.03688v3.pdf	https://github.com/modelscope/adaseq	true	true	false	pytorch
https://paperswithcode.com/paper/hipool-modeling-long-documents-using-graph	HiPool: Modeling Long Documents Using Graph Neural Networks	2305.03319	https://arxiv.org/abs/2305.03319v2	https://arxiv.org/pdf/2305.03319v2.pdf	https://github.com/irenezihuili/hipool	true	true	true	pytorch
https://paperswithcode.com/paper/factuality-enhanced-language-models-for-open	Factuality Enhanced Language Models for Open-Ended Text Generation	2206.04624	https://arxiv.org/abs/2206.04624v3	https://arxiv.org/pdf/2206.04624v3.pdf	https://github.com/triton-inference-server/fastertransformer_backend	false	false	true	pytorch
https://paperswithcode.com/paper/suspected-undeclared-use-of-artificial	Suspected Undeclared Use of Artificial Intelligence in the Academic Literature: An Analysis of the Academ-AI Dataset	2411.15218	https://arxiv.org/abs/2411.15218v1	https://arxiv.org/pdf/2411.15218v1.pdf	https://github.com/alex-glynn/academ-ai-analysis	true	false	false	none
https://paperswithcode.com/paper/black-hole-spectroscopy-by-mode-cleaning	Black hole spectroscopy by mode cleaning	2301.06705	https://arxiv.org/abs/2301.06705v2	https://arxiv.org/pdf/2301.06705v2.pdf	https://github.com/sizheng-ma/qnm_filter	true	true	true	none
https://paperswithcode.com/paper/towards-a-coq-formalization-of-a-quantified	Towards a Coq formalization of a quantified modal logic	2206.03358	https://arxiv.org/abs/2206.03358v2	https://arxiv.org/pdf/2206.03358v2.pdf	https://gitlab.com/ana-borges/QRC1-Coq	true	false	true	none
https://paperswithcode.com/paper/optical-aberration-correction-in	Optical Aberration Correction in Postprocessing using Imaging Simulation	2305.05867	https://arxiv.org/abs/2305.05867v1	https://arxiv.org/pdf/2305.05867v1.pdf	https://github.com/tangeego/imagingsimulation	true	true	false	pytorch
https://paperswithcode.com/paper/collective-filters-a-new-approach-to-analyze	Quasinormal-mode filters: a new approach to analyze the gravitational-wave ringdown of binary black-hole mergers	2207.10870	https://arxiv.org/abs/2207.10870v2	https://arxiv.org/pdf/2207.10870v2.pdf	https://github.com/sizheng-ma/qnm_filter	false	false	true	none
https://paperswithcode.com/paper/video-object-segmentation-in-panoptic-wild	Video Object Segmentation in Panoptic Wild Scenes	2305.04470	https://arxiv.org/abs/2305.04470v2	https://arxiv.org/pdf/2305.04470v2.pdf	https://github.com/yoxu515/viposeg-benchmark	true	true	true	none
https://paperswithcode.com/paper/a-new-particle-pusher-with-hadronic	A New Particle Pusher with Hadronic Interactions for Modeling Multimessenger Emission from Compact Objects	2410.22781	https://arxiv.org/abs/2410.22781v1	https://arxiv.org/pdf/2410.22781v1.pdf	https://github.com/Mynghao/pusher-library	true	false	true	none
https://paperswithcode.com/paper/a-virtual-reality-training-system-for	A Virtual Reality Training System for Automotive Engines Assembly and Disassembly	2311.02108	https://arxiv.org/abs/2311.02108v1	https://arxiv.org/pdf/2311.02108v1.pdf	https://github.com/ladissonlai/sustech_vrengine	true	true	false	none
https://paperswithcode.com/paper/cone-unsupervised-contrastive-opinion	Cone: Unsupervised Contrastive Opinion Extraction	2305.04599	https://arxiv.org/abs/2305.04599v1	https://arxiv.org/pdf/2305.04599v1.pdf	https://github.com/blpxspg/cone	true	true	false	pytorch
https://paperswithcode.com/paper/scidasynth-interactive-structured-knowledge	SciDaSynth: Interactive Structured Knowledge Extraction and Synthesis from Scientific Literature with Large Language Model	2404.13765	https://arxiv.org/abs/2404.13765v1	https://arxiv.org/pdf/2404.13765v1.pdf	https://github.com/xingbow/SciDaEx	true	false	true	none
https://paperswithcode.com/paper/actively-discovering-new-slots-for-task	Actively Discovering New Slots for Task-oriented Conversation	2305.04049	https://arxiv.org/abs/2305.04049v1	https://arxiv.org/pdf/2305.04049v1.pdf	https://github.com/newslotdetection/newslotdetection	true	true	false	pytorch
https://paperswithcode.com/paper/multi-scale-deformable-alignment-and-content	Multi-Scale Deformable Alignment and Content-Adaptive Inference for Flexible-Rate Bi-Directional Video Compression	2306.16544	https://arxiv.org/abs/2306.16544v1	https://arxiv.org/pdf/2306.16544v1.pdf	https://github.com/KUIS-AI-Tekalp-Research-Group/video-compression	true	true	false	pytorch
https://paperswithcode.com/paper/characterizing-deep-learning-package-supply	Characterizing Deep Learning Package Supply Chains in PyPI: Domains, Clusters, and Disengagement	2306.16307	https://arxiv.org/abs/2306.16307v2	https://arxiv.org/pdf/2306.16307v2.pdf	https://github.com/gaokai320/pypi-dlsc	true	true	false	tf
https://paperswithcode.com/paper/backprop-free-reinforcement-learning-with	Backprop-Free Reinforcement Learning with Active Neural Generative Coding	2107.07046	https://arxiv.org/abs/2107.07046v1	https://arxiv.org/pdf/2107.07046v1.pdf	https://github.com/ago109/active-neural-generative-coding	true	false	false	jax
https://paperswithcode.com/paper/nine-year-wilkinson-microwave-anisotropy-1	Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Final Maps and Results	1212.5225	https://arxiv.org/abs/1212.5225v3	https://arxiv.org/pdf/1212.5225v3.pdf	https://github.com/htjense/pywmap	false	false	true	none
https://paperswithcode.com/paper/learning-based-lossless-point-cloud-geometry	Learning-based Lossless Point Cloud Geometry Coding using Sparse Tensors	2204.05043	https://arxiv.org/abs/2204.05043v2	https://arxiv.org/pdf/2204.05043v2.pdf	https://github.com/Weafre/CNeT	false	false	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.