Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
xet
Community
1
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/business-process-simulation-probabilistic
Business Process Simulation: Probabilistic Modeling of Intermittent Resource Availability and Multitasking Behavior
2410.16941
https://arxiv.org/abs/2410.16941v1
https://arxiv.org/pdf/2410.16941v1.pdf
https://github.com/orlenyslp/probabilistic_resource_calendars
true
true
false
none
https://paperswithcode.com/paper/a-class-of-modular-and-flexible-covariate
A class of modular and flexible covariate-based covariance functions for nonstationary spatial modeling
2410.16716
https://arxiv.org/abs/2410.16716v1
https://arxiv.org/pdf/2410.16716v1.pdf
https://github.com/blasif/cocons
true
true
true
none
https://paperswithcode.com/paper/objectadd-adding-objects-into-image-via-a
ObjectAdd: Adding Objects into Image via a Training-Free Diffusion Modification Fashion
2404.17230
https://arxiv.org/abs/2404.17230v2
https://arxiv.org/pdf/2404.17230v2.pdf
https://github.com/potato-kitty/objectadd
true
true
true
pytorch
https://paperswithcode.com/paper/deep-reinforcement-learning-via-object
Deep Reinforcement Learning via Object-Centric Attention
2504.03024
https://arxiv.org/abs/2504.03024v1
https://arxiv.org/pdf/2504.03024v1.pdf
https://github.com/VanillaWhey/OCAtariWrappers
true
true
true
pytorch
https://paperswithcode.com/paper/beyond-domain-randomization-event-inspired
Beyond Domain Randomization: Event-Inspired Perception for Visually Robust Adversarial Imitation from Videos
2505.18899
https://arxiv.org/abs/2505.18899v1
https://arxiv.org/pdf/2505.18899v1.pdf
https://github.com/vittoriogiammarino/eb-laifo
true
true
false
pytorch
https://paperswithcode.com/paper/a-statistical-analysis-of-deep-federated
A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data
2410.20659
https://arxiv.org/abs/2410.20659v1
https://arxiv.org/pdf/2410.20659v1.pdf
https://github.com/saptarshic27/fl
true
true
false
pytorch
https://paperswithcode.com/paper/thunderkittens-simple-fast-and-adorable-ai
ThunderKittens: Simple, Fast, and Adorable AI Kernels
2410.20399
https://arxiv.org/abs/2410.20399v1
https://arxiv.org/pdf/2410.20399v1.pdf
https://github.com/HazyResearch/ThunderKittens
true
true
true
pytorch
https://paperswithcode.com/paper/viclevr-a-visual-reasoning-dataset-and-hybrid
ViCLEVR: A Visual Reasoning Dataset and Hybrid Multimodal Fusion Model for Visual Question Answering in Vietnamese
2310.18046
https://arxiv.org/abs/2310.18046v1
https://arxiv.org/pdf/2310.18046v1.pdf
https://github.com/kvt0012/viclevr
true
true
true
pytorch
https://paperswithcode.com/paper/structchart-perception-structuring-reasoning
StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding
2309.11268
https://arxiv.org/abs/2309.11268v5
https://arxiv.org/pdf/2309.11268v5.pdf
https://github.com/unimodal4reasoning/chartvlm
true
true
true
pytorch
https://paperswithcode.com/paper/efficient-evasion-attacks-to-graph-neural
Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function
2009.00203
https://arxiv.org/abs/2009.00203v3
https://arxiv.org/pdf/2009.00203v3.pdf
https://github.com/ventr1c/infattack
true
true
true
pytorch
https://paperswithcode.com/paper/mlp-mixer-an-all-mlp-architecture-for-vision
MLP-Mixer: An all-MLP Architecture for Vision
2105.01601
https://arxiv.org/abs/2105.01601v4
https://arxiv.org/pdf/2105.01601v4.pdf
https://github.com/mli-lab/imaging_mlps
false
false
true
pytorch
https://paperswithcode.com/paper/disk-star-alignment-i-pre-main-sequence
Disk-Star Alignment I: Pre-Main-Sequence Stellar Parameters and the Statistical Alignment Between Disks and Stellar Rotation
2504.02990
https://arxiv.org/abs/2504.02990v1
https://arxiv.org/pdf/2504.02990v1.pdf
https://github.com/mjfields/stelpar
true
true
true
none
https://paperswithcode.com/paper/hypernos-automated-and-parallel-library-for
HyperNOs: Automated and Parallel Library for Neural Operators Research
2503.18087
https://arxiv.org/abs/2503.18087v1
https://arxiv.org/pdf/2503.18087v1.pdf
https://github.com/MaxGhi8/HyperNOs
true
false
true
jax
https://paperswithcode.com/paper/all-is-not-lost-llm-recovery-without
All is Not Lost: LLM Recovery without Checkpoints
2506.15461
https://arxiv.org/abs/2506.15461v1
https://arxiv.org/pdf/2506.15461v1.pdf
https://github.com/gensyn-ai/checkfree
true
true
false
pytorch
https://paperswithcode.com/paper/updated-measurement-method-and-uncertainty
Updated measurement method and uncertainty budget for direct emissivity measurements at UPV/EHU
1910.08315
https://arxiv.org/abs/1910.08315v1
https://arxiv.org/pdf/1910.08315v1.pdf
https://github.com/inigogonzalezdearrieta/inigogonzalezdearrieta.github.io
false
false
true
none
https://paperswithcode.com/paper/lgs-a-light-weight-4d-gaussian-splatting-for
LGS: A Light-weight 4D Gaussian Splatting for Efficient Surgical Scene Reconstruction
2406.16073
https://arxiv.org/abs/2406.16073v1
https://arxiv.org/pdf/2406.16073v1.pdf
https://github.com/CUHK-AIM-Group/LGS
true
false
true
pytorch
https://paperswithcode.com/paper/hate-personified-investigating-the-role-of
Hate Personified: Investigating the role of LLMs in content moderation
2410.02657
https://arxiv.org/abs/2410.02657v1
https://arxiv.org/pdf/2410.02657v1.pdf
https://github.com/sahajps/Hate-Personified
true
false
false
pytorch
https://paperswithcode.com/paper/sciprompt-knowledge-augmented-prompting-for
SciPrompt: Knowledge-augmented Prompting for Fine-grained Categorization of Scientific Topics
2410.01946
https://arxiv.org/abs/2410.01946v1
https://arxiv.org/pdf/2410.01946v1.pdf
https://github.com/zhiwenyou103/SciPrompt
true
false
true
pytorch
https://paperswithcode.com/paper/autonomous-demon-exploiting-heat-and
Autonomous demon exploiting heat and information at the trajectory level
2409.05823
https://arxiv.org/abs/2409.05823v2
https://arxiv.org/pdf/2409.05823v2.pdf
https://zenodo.org/record/13740977
true
false
false
none
https://paperswithcode.com/paper/dip-unsupervised-dense-in-context-post
DIP: Unsupervised Dense In-Context Post-training of Visual Representations
2506.18463
https://arxiv.org/abs/2506.18463v1
https://arxiv.org/pdf/2506.18463v1.pdf
https://github.com/sirkosophia/dip
true
true
true
pytorch
https://paperswithcode.com/paper/overtuning-in-hyperparameter-optimization
Overtuning in Hyperparameter Optimization
2506.19540
https://arxiv.org/abs/2506.19540v1
https://arxiv.org/pdf/2506.19540v1.pdf
https://github.com/slds-lmu/paper_2025_overtuning
true
true
true
none
https://paperswithcode.com/paper/proteome-wide-prediction-of-mode-of
Proteome-wide prediction of mode of inheritance and molecular mechanism underlying genetic diseases using structural interactomics
2410.17708
https://arxiv.org/abs/2410.17708v2
https://arxiv.org/pdf/2410.17708v2.pdf
https://github.com/alisaadatv/structural-interactomics
true
true
false
none
https://paperswithcode.com/paper/dynaseg-a-deep-dynamic-fusion-method-for
DynaSeg: A Deep Dynamic Fusion Method for Unsupervised Image Segmentation Incorporating Feature Similarity and Spatial Continuity
2405.05477
https://arxiv.org/abs/2405.05477v4
https://arxiv.org/pdf/2405.05477v4.pdf
https://github.com/ryersonmultimedialab/dynaseg
true
true
false
pytorch
https://paperswithcode.com/paper/haichart-human-and-ai-paired-visualization
HAIChart: Human and AI Paired Visualization System
2406.11033
https://arxiv.org/abs/2406.11033v2
https://arxiv.org/pdf/2406.11033v2.pdf
https://github.com/hkustdial/haichart
true
true
false
tf
https://paperswithcode.com/paper/multi-task-learning-approach-for-intracranial
Multi-task Learning Approach for Intracranial Hemorrhage Prognosis
2408.08784
https://arxiv.org/abs/2408.08784v2
https://arxiv.org/pdf/2408.08784v2.pdf
https://github.com/miriamcobo/multitasklearning_ich_prognosis
true
true
true
pytorch
https://paperswithcode.com/paper/2408-02954
WWW: Where, Which and Whatever Enhancing Interpretability in Multimodal Deepfake Detection
2408.02954
https://arxiv.org/abs/2408.02954v1
https://arxiv.org/pdf/2408.02954v1.pdf
https://github.com/lsy0882/FakeMix
true
false
false
pytorch
https://paperswithcode.com/paper/adaptive-test-generation-with-qgrams
Adaptive Random Testing with Q-grams: The Illusion Comes True
2410.17907
https://arxiv.org/abs/2410.17907v5
https://arxiv.org/pdf/2410.17907v5.pdf
https://github.com/testingautomated-usi/adaptive-tg-qgrams
true
true
false
none
https://paperswithcode.com/paper/2408-02140
VidModEx: Interpretable and Efficient Black Box Model Extraction for High-Dimensional Spaces
2408.02140
https://arxiv.org/abs/2408.02140v1
https://arxiv.org/pdf/2408.02140v1.pdf
https://github.com/vidmodex/vidmodex
true
false
false
pytorch
https://paperswithcode.com/paper/2408-01700
Integrating Large Language Models and Knowledge Graphs for Extraction and Validation of Textual Test Data
2408.01700
https://arxiv.org/abs/2408.01700v1
https://arxiv.org/pdf/2408.01700v1.pdf
https://github.com/Antonio-Dee/tasi-testdata
true
false
false
none
https://paperswithcode.com/paper/2407-21314
State-observation augmented diffusion model for nonlinear assimilation
2407.21314
https://arxiv.org/abs/2407.21314v1
https://arxiv.org/pdf/2407.21314v1.pdf
https://github.com/zylipku/SOAD
true
false
true
jax
https://paperswithcode.com/paper/periguru-a-peripheral-robotic-mobile-app
PeriGuru: A Peripheral Robotic Mobile App Operation Assistant based on GUI Image Understanding and Prompting with LLM
2409.09354
https://arxiv.org/abs/2409.09354v1
https://arxiv.org/pdf/2409.09354v1.pdf
https://github.com/z2sj4t/periguru
true
true
false
pytorch
https://paperswithcode.com/paper/copyright-protected-language-generation-via
Copyright-Protected Language Generation via Adaptive Model Fusion
2412.06619
https://arxiv.org/abs/2412.06619v1
https://arxiv.org/pdf/2412.06619v1.pdf
https://github.com/jaabmar/cp_fuse
true
false
true
pytorch
https://paperswithcode.com/paper/generalized-sparsity-promoting-solvers-for
Generalized sparsity-promoting solvers for Bayesian inverse problems: Versatile sparsifying transforms and unknown noise variances
2402.16623
https://arxiv.org/abs/2402.16623v2
https://arxiv.org/pdf/2402.16623v2.pdf
https://github.com/jlindbloom/generalizedsparsitysolvers
true
true
true
none
https://paperswithcode.com/paper/2408-01708
AVESFormer: Efficient Transformer Design for Real-Time Audio-Visual Segmentation
2408.01708
https://arxiv.org/abs/2408.01708v1
https://arxiv.org/pdf/2408.01708v1.pdf
https://github.com/MindCode-4/code-6/tree/main/aves
false
false
false
mindspore
https://paperswithcode.com/paper/lightautoml-automl-solution-for-a-large
LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
2109.01528
https://arxiv.org/abs/2109.01528v2
https://arxiv.org/pdf/2109.01528v2.pdf
https://github.com/sb-ai-lab/lightautoml
false
false
true
pytorch
https://paperswithcode.com/paper/a-comprehensive-analysis-of-social-tie
BTS: A Comprehensive Benchmark for Tie Strength Prediction
2410.19214
https://arxiv.org/abs/2410.19214v5
https://arxiv.org/pdf/2410.19214v5.pdf
https://github.com/XueqiC/Awesome-Tie-Strength-Prediction
true
true
true
pytorch
https://paperswithcode.com/paper/weighted-anisotropic-isotropic-total
Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising
2307.00439
https://arxiv.org/abs/2307.00439v1
https://arxiv.org/pdf/2307.00439v1.pdf
https://github.com/kbui1993/official_aitv_poisson_denoising
true
true
true
none
https://paperswithcode.com/paper/juniper-an-open-source-nonlinear-branch-and
Juniper: An Open-Source Nonlinear Branch-and-Bound Solver in Julia
1804.07332
http://arxiv.org/abs/1804.07332v1
http://arxiv.org/pdf/1804.07332v1.pdf
https://github.com/lanl-ansi/Juniper.jl
true
true
true
none
https://paperswithcode.com/paper/a-simple-and-effective-l-2-norm-based
A Simple and Effective $L_2$ Norm-Based Strategy for KV Cache Compression
2406.11430
https://arxiv.org/abs/2406.11430v4
https://arxiv.org/pdf/2406.11430v4.pdf
https://github.com/alessiodevoto/l2compress
true
true
true
pytorch
https://paperswithcode.com/paper/modelling-and-verification-of-reconfigurable
Modelling and Verification of Reconfigurable Multi-Agent Systems
2104.10998
https://arxiv.org/abs/2104.10998v3
https://arxiv.org/pdf/2104.10998v3.pdf
https://github.com/dsynma/recipe
false
false
true
none
https://paperswithcode.com/paper/r-check-a-model-checker-for-verifying
R-CHECK: A Model Checker for Verifying Reconfigurable MAS
2201.06312
https://arxiv.org/abs/2201.06312v2
https://arxiv.org/pdf/2201.06312v2.pdf
https://github.com/dsynma/recipe
true
true
true
none
https://paperswithcode.com/paper/regress-don-t-guess-a-regression-like-loss-on
Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models
2411.02083
https://arxiv.org/abs/2411.02083v2
https://arxiv.org/pdf/2411.02083v2.pdf
https://github.com/tum-ai/number-token-loss
true
true
true
pytorch
https://paperswithcode.com/paper/scalable-efficient-training-of-large-language
Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention
2411.02063
https://arxiv.org/abs/2411.02063v1
https://arxiv.org/pdf/2411.02063v1.pdf
https://github.com/tsinghuac3i/lpa
true
true
true
pytorch
https://paperswithcode.com/paper/regression-for-astronomical-data-with
Regression for Astronomical Data with Realistic Distributions, Errors and Non-linearity
2411.08747
https://arxiv.org/abs/2411.08747v2
https://arxiv.org/pdf/2411.08747v2.pdf
https://github.com/astro-jingtao/raddest
true
true
false
jax
https://paperswithcode.com/paper/a-generalized-multiscale-bundle-based
A Generalized Multiscale Bundle-Based Hyperspectral Sparse Unmixing Algorithm
2401.13161
https://arxiv.org/abs/2401.13161v1
https://arxiv.org/pdf/2401.13161v1.pdf
https://github.com/lucayress/gmbua
true
true
false
none
https://paperswithcode.com/paper/discrete-cosine-transform-network-for-guided
Discrete Cosine Transform Network for Guided Depth Map Super-Resolution
2104.06977
https://arxiv.org/abs/2104.06977v3
https://arxiv.org/pdf/2104.06977v3.pdf
https://github.com/zhaozixiang1228/mmif-cddfuse
false
false
true
pytorch
https://paperswithcode.com/paper/image-fusion-via-vision-language-model
Image Fusion via Vision-Language Model
2402.02235
https://arxiv.org/abs/2402.02235v2
https://arxiv.org/pdf/2402.02235v2.pdf
https://github.com/zhaozixiang1228/mmif-cddfuse
false
false
true
pytorch
https://paperswithcode.com/paper/equivariant-multi-modality-image-fusion
Equivariant Multi-Modality Image Fusion
2305.11443
https://arxiv.org/abs/2305.11443v2
https://arxiv.org/pdf/2305.11443v2.pdf
https://github.com/zhaozixiang1228/mmif-cddfuse
false
false
true
pytorch
https://paperswithcode.com/paper/enhancing-inflation-nowcasting-with-llm
Enhancing Inflation Nowcasting with LLM: Sentiment Analysis on News
2410.20198
https://arxiv.org/abs/2410.20198v1
https://arxiv.org/pdf/2410.20198v1.pdf
https://github.com/paultltc/inflabert
true
true
false
none
https://paperswithcode.com/paper/sgseg-enabling-text-free-inference-in
SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance
2409.04758
https://arxiv.org/abs/2409.04758v1
https://arxiv.org/pdf/2409.04758v1.pdf
https://github.com/shuchangye-bib/sgseg
true
true
true
pytorch
https://paperswithcode.com/paper/neural-localizer-fields-for-continuous-3d
Neural Localizer Fields for Continuous 3D Human Pose and Shape Estimation
2407.07532
https://arxiv.org/abs/2407.07532v2
https://arxiv.org/pdf/2407.07532v2.pdf
https://github.com/isarandi/smplfitter
true
true
false
pytorch
https://paperswithcode.com/paper/origen-enhancing-rtl-code-generation-with
OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection
2407.16237
https://arxiv.org/abs/2407.16237v2
https://arxiv.org/pdf/2407.16237v2.pdf
https://github.com/pku-liang/origen
true
true
true
pytorch
https://paperswithcode.com/paper/on-the-ability-of-deep-networks-to-learn
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
2412.11521
https://arxiv.org/abs/2412.11521v1
https://arxiv.org/pdf/2412.11521v1.pdf
https://github.com/andrea-perin/gpsymm
true
true
false
jax
https://paperswithcode.com/paper/superpoint-self-supervised-interest-point
SuperPoint: Self-Supervised Interest Point Detection and Description
1712.07629
http://arxiv.org/abs/1712.07629v4
http://arxiv.org/pdf/1712.07629v4.pdf
https://github.com/AliYoussef97/SuperPoint-PrP
false
false
true
pytorch
https://paperswithcode.com/paper/2408-02750
Privacy-Safe Iris Presentation Attack Detection
2408.02750
https://arxiv.org/abs/2408.02750v1
https://arxiv.org/pdf/2408.02750v1.pdf
https://github.com/CVRL/PrivacySafeIrisPAD
true
false
true
pytorch
https://paperswithcode.com/paper/2408-00874
Medical SAM 2: Segment medical images as video via Segment Anything Model 2
2408.00874
https://arxiv.org/abs/2408.00874v2
https://arxiv.org/pdf/2408.00874v2.pdf
https://github.com/medicinetoken/medical-sam2
true
true
true
pytorch
https://paperswithcode.com/paper/right-on-time-revising-time-series-models-by
Right on Time: Revising Time Series Models by Constraining their Explanations
2402.12921
https://arxiv.org/abs/2402.12921v4
https://arxiv.org/pdf/2402.12921v4.pdf
https://github.com/ml-research/riot
true
true
true
pytorch
https://paperswithcode.com/paper/joint-rgb-spectral-decomposition-model-guided
Joint RGB-Spectral Decomposition Model Guided Image Enhancement in Mobile Photography
2407.17996
https://arxiv.org/abs/2407.17996v2
https://arxiv.org/pdf/2407.17996v2.pdf
https://github.com/calayzhou/jdm-hdrnet
true
true
true
pytorch
https://paperswithcode.com/paper/m2ost-many-to-one-regression-for-predicting
M2OST: Many-to-one Regression for Predicting Spatial Transcriptomics from Digital Pathology Images
2409.15092
https://arxiv.org/abs/2409.15092v4
https://arxiv.org/pdf/2409.15092v4.pdf
https://github.com/dootmaan/m2ost
true
true
false
pytorch
https://paperswithcode.com/paper/vsformer-mining-correlations-in-flexible-view
VSFormer: Mining Correlations in Flexible View Set for Multi-view 3D Shape Understanding
2409.09254
https://arxiv.org/abs/2409.09254v1
https://arxiv.org/pdf/2409.09254v1.pdf
https://github.com/auniquesun/vsformer
true
true
false
pytorch
https://paperswithcode.com/paper/vtrain-a-simulation-framework-for-evaluating
vTrain: A Simulation Framework for Evaluating Cost-effective and Compute-optimal Large Language Model Training
2312.12391
https://arxiv.org/abs/2312.12391v2
https://arxiv.org/pdf/2312.12391v2.pdf
https://github.com/via-research/vtrain
true
true
true
pytorch
https://paperswithcode.com/paper/counterfactual-generative-modeling-with
Counterfactual Generative Modeling with Variational Causal Inference
2410.12730
https://arxiv.org/abs/2410.12730v3
https://arxiv.org/pdf/2410.12730v3.pdf
https://github.com/yulun-rayn/variational-causal-inference
true
true
true
pytorch
https://paperswithcode.com/paper/image-blind-denoising-using-dual
Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection
2304.01620
https://arxiv.org/abs/2304.01620v1
https://arxiv.org/pdf/2304.01620v1.pdf
https://github.com/WenCongWu/DCBDNet
true
true
true
pytorch
https://paperswithcode.com/paper/finer-financial-named-entity-recognition
FiNER-ORD: Financial Named Entity Recognition Open Research Dataset
2302.11157
https://arxiv.org/abs/2302.11157v2
https://arxiv.org/pdf/2302.11157v2.pdf
https://github.com/gtfintechlab/finer
true
true
true
none
https://paperswithcode.com/paper/mimo-unlocking-the-reasoning-potential-of
MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining
2505.07608
https://arxiv.org/abs/2505.07608v1
https://arxiv.org/pdf/2505.07608v1.pdf
https://github.com/xiaomimimo/mimo
true
true
true
pytorch
https://paperswithcode.com/paper/grid-a-next-generation-data-parallel-c-qcd
Grid: A next generation data parallel C++ QCD library
1512.03487
http://arxiv.org/abs/1512.03487v1
http://arxiv.org/pdf/1512.03487v1.pdf
https://github.com/lehner/Grid
false
false
true
none
https://paperswithcode.com/paper/phi-s-distribution-balancing-for-label-free
PHI-S: Distribution Balancing for Label-Free Multi-Teacher Distillation
2410.01680
https://arxiv.org/abs/2410.01680v1
https://arxiv.org/pdf/2410.01680v1.pdf
https://github.com/nvlabs/radio
false
false
true
pytorch
https://paperswithcode.com/paper/exploring-the-design-space-of-diffusion
Fast-DiM: Towards Fast Diffusion Morphs
2310.09484
https://arxiv.org/abs/2310.09484v3
https://arxiv.org/pdf/2310.09484v3.pdf
https://github.com/zblasingame/DiM
true
false
true
pytorch
https://paperswithcode.com/paper/safe-navigation-in-dynamic-environments-using
Safe Navigation in Dynamic Environments using Density Functions
2411.12206
https://arxiv.org/abs/2411.12206v2
https://arxiv.org/pdf/2411.12206v2.pdf
https://github.com/sriram-2502/time_varying_density
true
false
false
none
https://paperswithcode.com/paper/orbital-torus-imaging-using-element
Orbital Torus Imaging: Using Element Abundances to Map Orbits and Mass in the Milky Way
2012.00015
https://arxiv.org/abs/2012.00015v2
https://arxiv.org/pdf/2012.00015v2.pdf
https://github.com/adrn/torusimaging
false
false
true
jax
https://paperswithcode.com/paper/composite-layers-for-deep-anomaly-detection
Composite Convolution: a Flexible Operator for Deep Learning on 3D Point Clouds
2209.11796
https://arxiv.org/abs/2209.11796v2
https://arxiv.org/pdf/2209.11796v2.pdf
https://github.com/sirolf-otrebla/compositenet
true
true
false
pytorch
https://paperswithcode.com/paper/a-novel-approach-to-identifying-open-star
A Novel Approach to Identifying Open Star Cluster Members in {\it Gaia} DR3: Integrating MST and GMM Techniques
2502.18082
https://arxiv.org/abs/2502.18082v1
https://arxiv.org/pdf/2502.18082v1.pdf
https://github.com/Astrolab-AUT/MST-GMM-membersip
true
true
false
none
https://paperswithcode.com/paper/causal-inference-in-spatiotemporal-climate
A data-driven framework for dimensionality reduction and causal inference in climate fields
2306.14433
https://arxiv.org/abs/2306.14433v3
https://arxiv.org/pdf/2306.14433v3.pdf
https://github.com/fabrifalasca/linear-response-and-causal-inference
true
true
true
none
https://paperswithcode.com/paper/towards-optimal-adversarial-robust-q-learning
Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error
2402.02165
https://arxiv.org/abs/2402.02165v2
https://arxiv.org/pdf/2402.02165v2.pdf
https://github.com/leoranlmia/CAR-DQN
true
true
true
pytorch
https://paperswithcode.com/paper/self-intersections-of-surfaces-that-contain
Self-intersections of surfaces that contain two circles through each point
2409.19253
https://arxiv.org/abs/2409.19253v1
https://arxiv.org/pdf/2409.19253v1.pdf
https://github.com/niels-lubbes/celestial-surfaces
true
false
false
none
https://paperswithcode.com/paper/towards-optimal-adversarial-robust
Towards Optimal Adversarial Robust Reinforcement Learning with Infinity Measurement Error
2502.16734
https://arxiv.org/abs/2502.16734v1
https://arxiv.org/pdf/2502.16734v1.pdf
https://github.com/leoranlmia/CAR-DQN
false
false
true
pytorch
https://paperswithcode.com/paper/escaping-the-big-data-paradigm-in-self
Escaping The Big Data Paradigm in Self-Supervised Representation Learning
2502.18056
https://arxiv.org/abs/2502.18056v1
https://arxiv.org/pdf/2502.18056v1.pdf
https://github.com/inescopresearch/scott
true
true
true
pytorch
https://paperswithcode.com/paper/pigeons-jl-distributed-sampling-from
Pigeons.jl: Distributed Sampling From Intractable Distributions
2308.09769
https://arxiv.org/abs/2308.09769v1
https://arxiv.org/pdf/2308.09769v1.pdf
https://github.com/julia-tempering/pigeons.jl
true
true
true
none
https://paperswithcode.com/paper/adversarial-coevolutionary-illumination-with
Adversarial Coevolutionary Illumination with Generational Adversarial MAP-Elites
2505.06617
https://arxiv.org/abs/2505.06617v1
https://arxiv.org/pdf/2505.06617v1.pdf
https://github.com/Timothee-ANNE/GAME
true
false
false
jax
https://paperswithcode.com/paper/ekf-based-radar-inertial-odometry-with-online
EKF-Based Radar-Inertial Odometry with Online Temporal Calibration
2502.00661
https://arxiv.org/abs/2502.00661v2
https://arxiv.org/pdf/2502.00661v2.pdf
https://github.com/spearwin/ekf-rio-tc
true
true
false
none
https://paperswithcode.com/paper/unlocking-the-power-of-diffusion-models-in
Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach
2505.19544
https://arxiv.org/abs/2505.19544v1
https://arxiv.org/pdf/2505.19544v1.pdf
https://github.com/nemo-1024/adrec
true
true
true
pytorch
https://paperswithcode.com/paper/w2v-bert-combining-contrastive-learning-and
W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training
2108.06209
https://arxiv.org/abs/2108.06209v2
https://arxiv.org/pdf/2108.06209v2.pdf
https://github.com/pwc-1/Paper-9/tree/main/1/wav2vec2_bert
false
false
false
mindspore
https://paperswithcode.com/paper/zero-shot-low-light-image-enhancement-via
Zero-Shot Low-Light Image Enhancement via Joint Frequency Domain Priors Guided Diffusion
2411.13961
https://arxiv.org/abs/2411.13961v1
https://arxiv.org/pdf/2411.13961v1.pdf
https://github.com/hejh8/joint-wavelet-and-fourier-priors-guided-diffusion
true
true
true
pytorch
https://paperswithcode.com/paper/read-over-the-lines-attacking-llms-and
Read Over the Lines: Attacking LLMs and Toxicity Detection Systems with ASCII Art to Mask Profanity
2409.18708
https://arxiv.org/abs/2409.18708v4
https://arxiv.org/pdf/2409.18708v4.pdf
https://github.com/Serbernari/ToxASCII
true
true
true
none
https://paperswithcode.com/paper/adaptive-depth-networks-with-skippable-sub
Adaptive Depth Networks with Skippable Sub-Paths
2312.16392
https://arxiv.org/abs/2312.16392v3
https://arxiv.org/pdf/2312.16392v3.pdf
https://github.com/wchkang/depth
true
false
true
pytorch
https://paperswithcode.com/paper/kad-no-more-fad-an-effective-and-efficient
KAD: No More FAD! An Effective and Efficient Evaluation Metric for Audio Generation
2502.15602
https://arxiv.org/abs/2502.15602v2
https://arxiv.org/pdf/2502.15602v2.pdf
https://github.com/YoonjinXD/kadtk
true
false
true
pytorch
https://paperswithcode.com/paper/bound-entangled-states-are-useful-in-prepare
Bound entangled states are useful in prepare-and-measure scenarios
2410.15388
https://arxiv.org/abs/2410.15388v2
https://arxiv.org/pdf/2410.15388v2.pdf
https://github.com/chalswater/bound_entanglement_conjecture
true
false
false
none
https://paperswithcode.com/paper/sc-bench-a-large-scale-dataset-for-smart
SC-Bench: A Large-Scale Dataset for Smart Contract Auditing
2410.06176
https://arxiv.org/abs/2410.06176v2
https://arxiv.org/pdf/2410.06176v2.pdf
https://github.com/system-pclub/SC-Bench
true
false
false
none
https://paperswithcode.com/paper/bitnet-a4-8-4-bit-activations-for-1-bit-llms
BitNet a4.8: 4-bit Activations for 1-bit LLMs
2411.04965
https://arxiv.org/abs/2411.04965v1
https://arxiv.org/pdf/2411.04965v1.pdf
https://github.com/microsoft/bitblas
false
false
true
pytorch
https://paperswithcode.com/paper/automated-unsupervised-and-auto-parameterized
Automated, Unsupervised, and Auto-parameterized Inference of Data Patterns and Anomaly Detection
2412.05240
https://arxiv.org/abs/2412.05240v1
https://arxiv.org/pdf/2412.05240v1.pdf
https://github.com/mooselab/discover-data-quality-with-riolu
true
true
false
none
https://paperswithcode.com/paper/learning-discrete-world-models-for-heuristic
Learning Discrete World Models for Heuristic Search
null
https://rlj.cs.umass.edu/2024/papers/Paper225.html
https://rlj.cs.umass.edu/2024/papers/RLJ_RLC_2024_225.pdf
https://github.com/misaghsoltani/DeepCubeAI
false
false
false
pytorch
https://paperswithcode.com/paper/rapid-learning-in-constrained-minimax-games
Rapid Learning in Constrained Minimax Games with Negative Momentum
2501.00533
https://arxiv.org/abs/2501.00533v1
https://arxiv.org/pdf/2501.00533v1.pdf
https://github.com/kkkaiaiai/NM-Method
true
false
true
none
https://paperswithcode.com/paper/kvc-ongoing-keystroke-verification-challenge
KVC-onGoing: Keystroke Verification Challenge
2412.20530
https://arxiv.org/abs/2412.20530v1
https://arxiv.org/pdf/2412.20530v1.pdf
https://github.com/yamagishi0824/kvc-dualnet
true
false
false
pytorch
https://paperswithcode.com/paper/caprompt-cyclic-prompt-aggregation-for-pre
CAPrompt: Cyclic Prompt Aggregation for Pre-Trained Model Based Class Incremental Learning
2412.08929
https://arxiv.org/abs/2412.08929v2
https://arxiv.org/pdf/2412.08929v2.pdf
https://github.com/zhoujiahuan1991/aaai2025-caprompt
true
true
true
pytorch
https://paperswithcode.com/paper/pyramidkv-dynamic-kv-cache-compression-based
PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling
2406.02069
https://arxiv.org/abs/2406.02069v4
https://arxiv.org/pdf/2406.02069v4.pdf
https://github.com/zefan-cai/pyramidkv
true
true
false
pytorch
https://paperswithcode.com/paper/ernie-enhanced-representation-through
ERNIE: Enhanced Representation through Knowledge Integration
1904.09223
http://arxiv.org/abs/1904.09223v1
http://arxiv.org/pdf/1904.09223v1.pdf
https://github.com/MindCode-4/code-3/tree/main/ernie
false
false
false
mindspore
https://paperswithcode.com/paper/causal-bald-deep-bayesian-active-learning-of
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
2111.02275
https://arxiv.org/abs/2111.02275v2
https://arxiv.org/pdf/2111.02275v2.pdf
https://github.com/uqhwen2/FCCM
false
false
true
pytorch
https://paperswithcode.com/paper/black-box-batch-active-learning-for
Black-Box Batch Active Learning for Regression
2302.08981
https://arxiv.org/abs/2302.08981v2
https://arxiv.org/pdf/2302.08981v2.pdf
https://github.com/uqhwen2/FCCM
false
false
true
pytorch
https://paperswithcode.com/paper/a-hybrid-artificial-intelligence-system-for
A Hybrid Artificial Intelligence System for Automated EEG Background Analysis and Report Generation
2411.09874
https://arxiv.org/abs/2411.09874v1
https://arxiv.org/pdf/2411.09874v1.pdf
https://github.com/tcs211/ai_eeeg_report
true
true
true
tf
https://paperswithcode.com/paper/a-critical-assessment-of-visual-sound-source
A Critical Assessment of Visual Sound Source Localization Models Including Negative Audio
2410.01020
https://arxiv.org/abs/2410.01020v3
https://arxiv.org/pdf/2410.01020v3.pdf
https://github.com/xavijuanola/vssl_eval
true
true
true
pytorch