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

Dataset card Data Studio Files
xet
Community
1
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36
81
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242
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16
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bool
2 classes
mentioned_in_github
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stringclasses
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https://paperswithcode.com/paper/learning-debiased-models-with-dynamic
Combating Unknown Bias with Effective Bias-Conflicting Scoring and Gradient Alignment
2111.13108
https://arxiv.org/abs/2111.13108v2
https://arxiv.org/pdf/2111.13108v2.pdf
https://github.com/parkgeonyeong/dcwp
false
false
true
pytorch
https://paperswithcode.com/paper/mud-towards-a-large-scale-and-noise-filtered
MUD: Towards a Large-Scale and Noise-Filtered UI Dataset for Modern Style UI Modeling
2405.07090
https://arxiv.org/abs/2405.07090v1
https://arxiv.org/pdf/2405.07090v1.pdf
https://github.com/sidongfeng/MUD
true
true
false
none
https://paperswithcode.com/paper/find-the-funding-entity-linking-with
Find the Funding: Entity Linking with Incomplete Funding Knowledge Bases
2209.00351
https://arxiv.org/abs/2209.00351v2
https://arxiv.org/pdf/2209.00351v2.pdf
https://github.com/informagi/fund-el
true
true
false
pytorch
https://paperswithcode.com/paper/dimsum-distributed-and-multilingual
DiMSum: Distributed and Multilingual Summarization of Financial Narratives
null
https://aclanthology.org/2022.fnp-1.9
https://aclanthology.org/2022.fnp-1.9.pdf
https://github.com/neeleshkshukla/DiMSum_FNP_2022
true
false
false
none
https://paperswithcode.com/paper/aesthetic-attribute-assessment-of-images
Aesthetic Attribute Assessment of Images Numerically on Mixed Multi-attribute Datasets
2207.01806
https://arxiv.org/abs/2207.01806v1
https://arxiv.org/pdf/2207.01806v1.pdf
https://github.com/BestiVictory/Aesthetic-Attribute-Assessment-Model
false
false
true
mindspore
https://paperswithcode.com/paper/splitee-early-exit-in-deep-neural-networks
SplitEE: Early Exit in Deep Neural Networks with Split Computing
2309.09195
https://arxiv.org/abs/2309.09195v1
https://arxiv.org/pdf/2309.09195v1.pdf
https://github.com/Div290/SplitEE/blob/main/README.md
false
false
false
pytorch
https://paperswithcode.com/paper/fourier-series-expansion-based-filter
Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions
2107.14519
https://arxiv.org/abs/2107.14519v2
https://arxiv.org/pdf/2107.14519v2.pdf
https://github.com/XieQi2015/F-Conv
true
true
false
pytorch
https://paperswithcode.com/paper/target-guided-open-domain-conversation-1
Target-Guided Open-Domain Conversation Planning
2209.09746
https://arxiv.org/abs/2209.09746v1
https://arxiv.org/pdf/2209.09746v1.pdf
https://github.com/y-kishinami/tgcp
true
true
false
none
https://paperswithcode.com/paper/agreement-or-disagreement-in-noise-tolerant
Agreement or Disagreement in Noise-tolerant Mutual Learning?
2203.15317
https://arxiv.org/abs/2203.15317v2
https://arxiv.org/pdf/2203.15317v2.pdf
https://github.com/jiarunliu/mlc
true
true
false
pytorch
https://paperswithcode.com/paper/perspective-phase-angle-model-for
Perspective Phase Angle Model for Polarimetric 3D Reconstruction
2207.09629
https://arxiv.org/abs/2207.09629v2
https://arxiv.org/pdf/2207.09629v2.pdf
https://github.com/gcchen97/ppa4p3d
true
true
true
none
https://paperswithcode.com/paper/hyp-2-loss-beyond-hypersphere-metric-space
HyP$^2$ Loss: Beyond Hypersphere Metric Space for Multi-label Image Retrieval
2208.06866
https://arxiv.org/abs/2208.06866v1
https://arxiv.org/pdf/2208.06866v1.pdf
https://github.com/jerryxu0129/hyp2-loss
true
true
false
pytorch
https://paperswithcode.com/paper/classification-of-small-triorthogonal-codes
Classification of Small Triorthogonal Codes
2107.09684
https://arxiv.org/abs/2107.09684v2
https://arxiv.org/pdf/2107.09684v2.pdf
https://github.com/sgnez/Tri_from_RM
true
true
false
none
https://paperswithcode.com/paper/multi-partition-embedding-interaction-with
Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion
2006.16365
https://arxiv.org/abs/2006.16365v2
https://arxiv.org/pdf/2006.16365v2.pdf
https://github.com/tranhungnghiep/AnalyzeKGE
false
false
true
tf
https://paperswithcode.com/paper/ensemble-of-expanded-ensembles-a-generalized
Replica exchange of expanded ensembles: A generalized ensemble approach with enhanced flexibility and parallelizability
2308.06938
https://arxiv.org/abs/2308.06938v2
https://arxiv.org/pdf/2308.06938v2.pdf
https://github.com/wehs7661/ensemble_md
true
true
true
none
https://paperswithcode.com/paper/visualization-guidelines-for-model
Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts
2205.05749
https://arxiv.org/abs/2205.05749v3
https://arxiv.org/pdf/2205.05749v3.pdf
https://github.com/tuftsvalt/modelcomm
true
true
false
none
https://paperswithcode.com/paper/bertoldo-the-historical-bert-for-italian
BERToldo, the Historical BERT for Italian
null
https://aclanthology.org/2022.lt4hala-1.10
https://aclanthology.org/2022.lt4hala-1.10.pdf
https://github.com/dhfbk/historical-bert
true
true
false
none
https://paperswithcode.com/paper/tt-bajes-bayesian-inference-of-multimessenger
${\tt bajes}$: Bayesian inference of multimessenger astrophysical data, methods and application to gravitational-waves
2102.00017
https://arxiv.org/abs/2102.00017v2
https://arxiv.org/pdf/2102.00017v2.pdf
https://github.com/roxgamba/bajes
false
false
true
none
https://paperswithcode.com/paper/text-alpha-2-discovering-logical-formulaic
$\text{Alpha}^2$: Discovering Logical Formulaic Alphas using Deep Reinforcement Learning
2406.16505
https://arxiv.org/abs/2406.16505v2
https://arxiv.org/pdf/2406.16505v2.pdf
https://github.com/x35f/alpha2
true
true
true
jax
https://paperswithcode.com/paper/an-image-is-worth-16x16-words-transformers-1
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
2010.11929
https://arxiv.org/abs/2010.11929v2
https://arxiv.org/pdf/2010.11929v2.pdf
https://github.com/smitheric95/MoCoViT-PyTorch
false
false
true
pytorch
https://paperswithcode.com/paper/predicting-hurricane-trajectories-using-a
Predicting Hurricane Trajectories using a Recurrent Neural Network
1802.02548
http://arxiv.org/abs/1802.02548v3
http://arxiv.org/pdf/1802.02548v3.pdf
https://github.com/stormalytics/hurricane-frocasting
false
false
true
pytorch
https://paperswithcode.com/paper/behanceqa-a-new-dataset-for-identifying
BehanceQA: A New Dataset for Identifying Question-Answer Pairs in Video Transcripts
null
https://aclanthology.org/2022.lrec-1.796
https://aclanthology.org/2022.lrec-1.796.pdf
https://github.com/amirveyseh/behanceqa
true
true
false
pytorch
https://paperswithcode.com/paper/scalable-computation-of-monge-maps-with
Neural Monge Map estimation and its applications
2106.03812
https://arxiv.org/abs/2106.03812v3
https://arxiv.org/pdf/2106.03812v3.pdf
https://github.com/sbyebss/monge_map_solver
true
false
false
pytorch
https://paperswithcode.com/paper/convnext-v2-co-designing-and-scaling-convnets
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
2301.00808
https://arxiv.org/abs/2301.00808v1
https://arxiv.org/pdf/2301.00808v1.pdf
https://github.com/zibbini/convnext-v2_tensorflow
false
false
true
tf
https://paperswithcode.com/paper/privacy-induces-robustness-information
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation
2211.00724
https://arxiv.org/abs/2211.00724v2
https://arxiv.org/pdf/2211.00724v2.pdf
https://github.com/kristian-georgiev/privacy-induces-robustness
true
false
false
none
https://paperswithcode.com/paper/stylised-choropleth-maps-for-new-zealand
Stylised Choropleth Maps for New Zealand Regions and District Health Boards
1912.04435
https://arxiv.org/abs/1912.04435v1
https://arxiv.org/pdf/1912.04435v1.pdf
https://github.com/tslumley/DHBins
true
true
true
none
https://paperswithcode.com/paper/perturbed-self-distillation-weakly-supervised
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation
null
http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Perturbed_Self-Distillation_Weakly_Supervised_Large-Scale_Point_Cloud_Semantic_Segmentation_ICCV_2021_paper.html
http://openaccess.thecvf.com//content/ICCV2021/papers/Zhang_Perturbed_Self-Distillation_Weakly_Supervised_Large-Scale_Point_Cloud_Semantic_Segmentation_ICCV_2021_paper.pdf
https://github.com/yangyucheng000/PSD_Mindspore
false
false
false
mindspore
https://paperswithcode.com/paper/progressive-color-transfer-with-dense
Progressive Color Transfer with Dense Semantic Correspondences
1710.00756
http://arxiv.org/abs/1710.00756v2
http://arxiv.org/pdf/1710.00756v2.pdf
https://github.com/dev-Adrian-Vera/Second_Partial_Project
false
false
true
tf
https://paperswithcode.com/paper/automatic-annotation-of-direct-speech-in
Automatic Annotation of Direct Speech in Written French Narratives
2306.15634
https://arxiv.org/abs/2306.15634v2
https://arxiv.org/pdf/2306.15634v2.pdf
https://github.com/deezer/aads_french
true
true
false
none
https://paperswithcode.com/paper/lasso-hyperinterpolation-over-general-regions
Lasso hyperinterpolation over general regions
2011.00433
https://arxiv.org/abs/2011.00433v2
https://arxiv.org/pdf/2011.00433v2.pdf
https://github.com/HaoNingWu/LassoHyper
false
false
true
none
https://paperswithcode.com/paper/product-information-extraction-using-chatgpt
Product Information Extraction using ChatGPT
2306.14921
https://arxiv.org/abs/2306.14921v1
https://arxiv.org/pdf/2306.14921v1.pdf
https://github.com/wbsg-uni-mannheim/pie_chatgpt
true
true
false
none
https://paperswithcode.com/paper/finding-stable-groups-of-cross-correlated
Finding Groups of Cross-Correlated Features in Bi-View Data
2009.05079
https://arxiv.org/abs/2009.05079v4
https://arxiv.org/pdf/2009.05079v4.pdf
https://github.com/miheerdew/cbce
true
true
false
none
https://paperswithcode.com/paper/unsupervised-representation-learning-with-1
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
1511.06434
http://arxiv.org/abs/1511.06434v2
http://arxiv.org/pdf/1511.06434v2.pdf
https://github.com/MasoumehVahedi/GANs-Model
false
false
true
pytorch
https://paperswithcode.com/paper/ultra-high-resolution-unpaired-stain
Ultra-high-resolution unpaired stain transformation via Kernelized Instance Normalization
2208.10730
https://arxiv.org/abs/2208.10730v1
https://arxiv.org/pdf/2208.10730v1.pdf
https://github.com/kaminyou/urust
true
true
false
pytorch
https://paperswithcode.com/paper/the-spatially-correlative-loss-for-various
The Spatially-Correlative Loss for Various Image Translation Tasks
2104.00854
https://arxiv.org/abs/2104.00854v1
https://arxiv.org/pdf/2104.00854v1.pdf
https://github.com/kaminyou/urust
false
false
true
pytorch
https://paperswithcode.com/paper/unpaired-image-to-image-translation-using
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
1703.10593
https://arxiv.org/abs/1703.10593v7
https://arxiv.org/pdf/1703.10593v7.pdf
https://github.com/kaminyou/urust
false
false
true
pytorch
https://paperswithcode.com/paper/sentimentarcs-a-novel-method-for-self
SentimentArcs: A Novel Method for Self-Supervised Sentiment Analysis of Time Series Shows SOTA Transformers Can Struggle Finding Narrative Arcs
2110.09454
https://arxiv.org/abs/2110.09454v1
https://arxiv.org/pdf/2110.09454v1.pdf
https://github.com/jon-chun/sentimentarcs_notebooks
true
false
true
none
https://paperswithcode.com/paper/deep-learning-software-engineering-state-of
Deep Learning & Software Engineering: State of Research and Future Directions
2009.08525
https://arxiv.org/abs/2009.08525v1
https://arxiv.org/pdf/2009.08525v1.pdf
https://gitlab.com/dlse-workshop/dlse-workshop-community-report
true
true
false
none
https://paperswithcode.com/paper/posetrans-a-simple-yet-effective-pose
PoseTrans: A Simple Yet Effective Pose Transformation Augmentation for Human Pose Estimation
2208.07755
https://arxiv.org/abs/2208.07755v1
https://arxiv.org/pdf/2208.07755v1.pdf
https://github.com/wtjiang98/PoseTrans
true
false
false
pytorch
https://paperswithcode.com/paper/flopping-mode-electron-dipole-spin-resonance
Flopping-mode electron dipole spin resonance in the strong-driving regime
2208.10548
https://arxiv.org/abs/2208.10548v1
https://arxiv.org/pdf/2208.10548v1.pdf
https://github.com/qutech/qopt-applications
true
true
false
none
https://paperswithcode.com/paper/a-time-domain-generalized-wiener-filter-for
A Time-domain Real-valued Generalized Wiener Filter for Multi-channel Neural Separation Systems
2112.03533
https://arxiv.org/abs/2112.03533v2
https://arxiv.org/pdf/2112.03533v2.pdf
https://github.com/yluo42/TAC
true
true
false
pytorch
https://paperswithcode.com/paper/on-the-complementarity-between-pre-training-1
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation
2209.03316
https://arxiv.org/abs/2209.03316v3
https://arxiv.org/pdf/2209.03316v3.pdf
https://github.com/zanchangtong/ptvsri
true
true
false
pytorch
https://paperswithcode.com/paper/crowdsourced-fact-checking-at-twitter-how
Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?
2208.09214
https://arxiv.org/abs/2208.09214v1
https://arxiv.org/pdf/2208.09214v1.pdf
https://github.com/mhmdsaiid/birdwatch
true
true
true
none
https://paperswithcode.com/paper/privacy-preserving-data-sharing-via
Privacy-preserving data sharing via probabilistic modelling
1912.04439
https://arxiv.org/abs/1912.04439v4
https://arxiv.org/pdf/1912.04439v4.pdf
https://github.com/DPBayes/twinify
false
false
true
jax
https://paperswithcode.com/paper/multi-objective-representation-learning-for
Multi-objective Representation Learning for Scientific Document Retrieval
null
https://aclanthology.org/2022.sdp-1.9
https://aclanthology.org/2022.sdp-1.9.pdf
https://github.com/zetaalphavector/multi-obj-repr-learning
true
true
false
pytorch
https://paperswithcode.com/paper/revision-transformers-getting-rit-of-no-nos
Revision Transformers: Instructing Language Models to Change their Values
2210.10332
https://arxiv.org/abs/2210.10332v3
https://arxiv.org/pdf/2210.10332v3.pdf
https://github.com/ml-research/revision-transformer
true
true
true
pytorch
https://paperswithcode.com/paper/longformer-the-long-document-transformer
Longformer: The Long-Document Transformer
2004.05150
https://arxiv.org/abs/2004.05150v2
https://arxiv.org/pdf/2004.05150v2.pdf
https://github.com/a-rios/ats-models
false
false
true
pytorch
https://paperswithcode.com/paper/corrclip-reconstructing-correlations-in-clip
CorrCLIP: Reconstructing Correlations in CLIP with Off-the-Shelf Foundation Models for Open-Vocabulary Semantic Segmentation
2411.10086
https://arxiv.org/abs/2411.10086v1
https://arxiv.org/pdf/2411.10086v1.pdf
https://github.com/zdk258/CorrCLIP
true
false
true
pytorch
https://paperswithcode.com/paper/fast-and-accurate-importance-weighting-for
Fast and Accurate Importance Weighting for Correcting Sample Bias
2209.04215
https://arxiv.org/abs/2209.04215v1
https://arxiv.org/pdf/2209.04215v1.pdf
https://github.com/antoinedemathelin/importance-weighting-network
true
true
true
tf
https://paperswithcode.com/paper/policy-bifurcation-in-safe-reinforcement
Policy Bifurcation in Safe Reinforcement Learning
2403.12847
https://arxiv.org/abs/2403.12847v3
https://arxiv.org/pdf/2403.12847v3.pdf
https://github.com/thuzouwenjun/mupo
true
true
false
pytorch
https://paperswithcode.com/paper/exploring-the-potential-of-multimodal-llm
Exploring the Potential of Multimodal LLM with Knowledge-Intensive Multimodal ASR
2406.10880
https://arxiv.org/abs/2406.10880v2
https://arxiv.org/pdf/2406.10880v2.pdf
https://github.com/yuriak/ms-asr
true
true
true
none
https://paperswithcode.com/paper/mcunetv2-memory-efficient-patch-based
MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
2110.15352
https://arxiv.org/abs/2110.15352v2
https://arxiv.org/pdf/2110.15352v2.pdf
https://github.com/mit-han-lab/mcunet
false
false
true
tf
https://paperswithcode.com/paper/on-device-training-under-256kb-memory
On-Device Training Under 256KB Memory
2206.15472
https://arxiv.org/abs/2206.15472v4
https://arxiv.org/pdf/2206.15472v4.pdf
https://github.com/mit-han-lab/mcunet
false
false
true
tf
https://paperswithcode.com/paper/secure-shapley-value-for-cross-silo-federated
Secure Shapley Value for Cross-Silo Federated Learning (Technical Report)
2209.04856
https://arxiv.org/abs/2209.04856v5
https://arxiv.org/pdf/2209.04856v5.pdf
https://github.com/teijyogen/secsv
true
true
true
pytorch
https://paperswithcode.com/paper/neural-bayesian-network-understudy
Neural Bayesian Network Understudy
2211.08243
https://arxiv.org/abs/2211.08243v1
https://arxiv.org/pdf/2211.08243v1.pdf
https://github.com/prabaey/nbn-understudy
true
true
true
pytorch
https://paperswithcode.com/paper/constraints-on-the-cosmic-expansion-history
Constraints on the cosmic expansion history from GWTC-3
2111.03604
https://arxiv.org/abs/2111.03604v2
https://arxiv.org/pdf/2111.03604v2.pdf
https://github.com/mariapalfi/gwcosmo_coasting
false
false
true
none
https://paperswithcode.com/paper/dynamic-multi-scale-convolution-for-dialect
Dynamic Multi-scale Convolution for Dialect Identification
2108.07787
https://arxiv.org/abs/2108.07787v1
https://arxiv.org/pdf/2108.07787v1.pdf
https://github.com/yuyq96/d-tdnn
false
false
true
pytorch
https://paperswithcode.com/paper/variational-beam-search-for-online-learning
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning
2012.08101
https://arxiv.org/abs/2012.08101v3
https://arxiv.org/pdf/2012.08101v3.pdf
https://github.com/mandt-lab/variational-beam-search
true
false
false
tf
https://paperswithcode.com/paper/improving-children-s-speech-recognition-by
Improving Children's Speech Recognition by Fine-tuning Self-supervised Adult Speech Representations
2211.07769
https://arxiv.org/abs/2211.07769v1
https://arxiv.org/pdf/2211.07769v1.pdf
https://github.com/monomest/thesis
true
true
false
pytorch
https://paperswithcode.com/paper/probabilistic-auto-encoder
Probabilistic Autoencoder
2006.05479
https://arxiv.org/abs/2006.05479v4
https://arxiv.org/pdf/2006.05479v4.pdf
https://github.com/vmboehm/pae-ablation
true
true
true
tf
https://paperswithcode.com/paper/distribution-inference-risks-identifying-and
Distribution inference risks: Identifying and mitigating sources of leakage
2209.08541
https://arxiv.org/abs/2209.08541v1
https://arxiv.org/pdf/2209.08541v1.pdf
https://github.com/epfl-dlab/property-inference-attacks
true
true
true
pytorch
https://paperswithcode.com/paper/fastclass-a-time-efficient-approach-to-weakly
FastClass: A Time-Efficient Approach to Weakly-Supervised Text Classification
2212.05506
https://arxiv.org/abs/2212.05506v2
https://arxiv.org/pdf/2212.05506v2.pdf
https://github.com/xiatingyu/fastclass
true
true
false
pytorch
https://paperswithcode.com/paper/formalizing-distribution-inference-risks
Formalizing Distribution Inference Risks
2106.03699
https://arxiv.org/abs/2106.03699v4
https://arxiv.org/pdf/2106.03699v4.pdf
https://github.com/epfl-dlab/property-inference-attacks
false
false
true
pytorch
https://paperswithcode.com/paper/towards-a-perceptual-evaluation-framework-for
Towards a Perceptual Evaluation Framework for Lighting Estimation
2312.04334
https://arxiv.org/abs/2312.04334v3
https://arxiv.org/pdf/2312.04334v3.pdf
https://github.com/JustineGiroux/Lightsome
true
false
false
none
https://paperswithcode.com/paper/improving-rare-word-translation-with
Improving Rare Word Translation With Dictionaries and Attention Masking
2408.09075
https://arxiv.org/abs/2408.09075v2
https://arxiv.org/pdf/2408.09075v2.pdf
https://github.com/kennethsible/dictionary-attention
true
true
false
pytorch
https://paperswithcode.com/paper/high-stable-and-accurate-vehicle-selection
High stable and accurate vehicle selection scheme based on federated edge learning in vehicular networks
2208.01890
https://arxiv.org/abs/2208.01890v2
https://arxiv.org/pdf/2208.01890v2.pdf
https://github.com/qiongwu86/Vehicle-selection
true
true
false
tf
https://paperswithcode.com/paper/interactively-generating-explanations-for
Interactively Providing Explanations for Transformer Language Models
2110.02058
https://arxiv.org/abs/2110.02058v4
https://arxiv.org/pdf/2110.02058v4.pdf
https://github.com/felifri/xaitransformer
true
true
false
pytorch
https://paperswithcode.com/paper/usln-a-statistically-guided-lightweight
USLN: A statistically guided lightweight network for underwater image enhancement via dual-statistic white balance and multi-color space stretch
2209.02221
https://arxiv.org/abs/2209.02221v1
https://arxiv.org/pdf/2209.02221v1.pdf
https://github.com/deepxzy/usln
true
true
true
pytorch
https://paperswithcode.com/paper/rethinking-causal-relationships-learning-in
Rethinking Causal Relationships Learning in Graph Neural Networks
2312.09613
https://arxiv.org/abs/2312.09613v1
https://arxiv.org/pdf/2312.09613v1.pdf
https://github.com/yaoyao-yaoyao-cell/crcg
true
true
false
pytorch
https://paperswithcode.com/paper/gnmr-a-provable-one-line-algorithm-for-low
GNMR: A provable one-line algorithm for low rank matrix recovery
2106.12933
https://arxiv.org/abs/2106.12933v3
https://arxiv.org/pdf/2106.12933v3.pdf
https://github.com/pizilber/GNMR
true
true
true
none
https://paperswithcode.com/paper/learning-from-the-dark-boosting-graph
Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples
2210.00728
https://arxiv.org/abs/2210.00728v1
https://arxiv.org/pdf/2210.00728v1.pdf
https://github.com/Wei9711/NegGCNs
true
false
false
none
https://paperswithcode.com/paper/towards-reliable-predictive-analytics-a
Towards reliable predictive analytics: a generalized calibration framework
2309.08559
https://arxiv.org/abs/2309.08559v1
https://arxiv.org/pdf/2309.08559v1.pdf
https://github.com/bavodc/papergeneralizedcalibrationcurves
true
true
false
none
https://paperswithcode.com/paper/privileged-knowledge-distillation-for-sim-to
Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective
2305.18464
https://arxiv.org/abs/2305.18464v2
https://arxiv.org/pdf/2305.18464v2.pdf
https://github.com/tinnerhrhe/HIB_Policy
true
false
true
none
https://paperswithcode.com/paper/leandojo-theorem-proving-with-retrieval-1
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
2306.15626
https://arxiv.org/abs/2306.15626v2
https://arxiv.org/pdf/2306.15626v2.pdf
https://github.com/lean-dojo/leandojochatgpt
true
true
false
none
https://paperswithcode.com/paper/motor-crosslinking-augments-elasticity-in
Motor crosslinking augments elasticity in active nematics
2308.16831
https://arxiv.org/abs/2308.16831v1
https://arxiv.org/pdf/2308.16831v1.pdf
https://github.com/gardel-lab/responsefunction
true
true
false
none
https://paperswithcode.com/paper/floquet-theory-and-stability-for-hamiltonian
Floquet theory and stability for Hamiltonian partial differential equations
2309.03962
https://arxiv.org/abs/2309.03962v1
https://arxiv.org/pdf/2309.03962v1.pdf
https://github.com/JaredCBronski/Hamiltonian-Floquet
true
false
false
none
https://paperswithcode.com/paper/ideal-improved-dense-local-contrastive
IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image Segmentation
2210.15075
https://arxiv.org/abs/2210.15075v2
https://arxiv.org/pdf/2210.15075v2.pdf
https://github.com/rohit-kundu/ideal-icassp23
true
true
true
none
https://paperswithcode.com/paper/on-a-three-dimensional-and-two-four
On a three-dimensional and two four-dimensional oncolytic viro-therapy models
2210.00401
https://arxiv.org/abs/2210.00401v1
https://arxiv.org/pdf/2210.00401v1.pdf
https://github.com/rim-adenane/oncolytic-viro-therapy-models-m
true
true
false
none
https://paperswithcode.com/paper/pesotif-a-challenging-visual-dataset-for
PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in Long-tail Traffic Scenarios
2211.03402
https://arxiv.org/abs/2211.03402v1
https://arxiv.org/pdf/2211.03402v1.pdf
https://github.com/sotif-avlab/pesotif
true
true
true
none
https://paperswithcode.com/paper/mmdetection-open-mmlab-detection-toolbox-and
MMDetection: Open MMLab Detection Toolbox and Benchmark
1906.07155
https://arxiv.org/abs/1906.07155v1
https://arxiv.org/pdf/1906.07155v1.pdf
https://github.com/sotif-avlab/pesotif
false
false
true
none
https://paperswithcode.com/paper/bert-and-pals-projected-attention-layers-for
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
1902.02671
https://arxiv.org/abs/1902.02671v2
https://arxiv.org/pdf/1902.02671v2.pdf
https://github.com/josselinsomervilleroberts/ptsl
false
false
true
pytorch
https://paperswithcode.com/paper/sotif-entropy-online-sotif-risk
SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving
2211.04009
https://arxiv.org/abs/2211.04009v1
https://arxiv.org/pdf/2211.04009v1.pdf
https://github.com/sotif-avlab/pesotif
true
true
true
none
https://paperswithcode.com/paper/odd-a-benchmark-dataset-for-the-nlp-based
ODD: A Benchmark Dataset for the Natural Language Processing based Opioid Related Aberrant Behavior Detection
2307.02591
https://arxiv.org/abs/2307.02591v4
https://arxiv.org/pdf/2307.02591v4.pdf
https://github.com/soon91jae/orab_mimic
true
true
false
pytorch
https://paperswithcode.com/paper/convnext-v2-co-designing-and-scaling-convnets
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
2301.00808
https://arxiv.org/abs/2301.00808v1
https://arxiv.org/pdf/2301.00808v1.pdf
https://github.com/facebookresearch/convnext-v2
true
true
true
pytorch
https://paperswithcode.com/paper/text2traj2text-learning-by-synthesis
Text2Traj2Text: Learning-by-Synthesis Framework for Contextual Captioning of Human Movement Trajectories
2409.12670
https://arxiv.org/abs/2409.12670v1
https://arxiv.org/pdf/2409.12670v1.pdf
https://github.com/cyberagentailab/text2traj2text
true
true
true
jax
https://paperswithcode.com/paper/qmes-derivation-mathematica-package-for-the
QMeS-Derivation: Mathematica package for the symbolic derivation of functional equations
2102.01410
https://arxiv.org/abs/2102.01410v2
https://arxiv.org/pdf/2102.01410v2.pdf
https://github.com/QMeS-toolbox/QMeS-Derivation
false
false
true
none
https://paperswithcode.com/paper/integrative-imaging-informatics-for-cancer
Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO)
2210.03151
https://arxiv.org/abs/2210.03151v1
https://arxiv.org/pdf/2210.03151v1.pdf
https://github.com/satrajitgithub/nrg_ai_neuroonco_segment
true
true
true
none
https://paperswithcode.com/paper/hyperparameter-optimization-as-a-service-on
Hyperparameter Optimization as a Service on INFN Cloud
2301.05522
https://arxiv.org/abs/2301.05522v3
https://arxiv.org/pdf/2301.05522v3.pdf
https://github.com/landerlini/hopaas_client
false
false
false
none
https://paperswithcode.com/paper/a-multi-head-model-for-continual-learning-via
A Multi-Head Model for Continual Learning via Out-of-Distribution Replay
2208.09734
https://arxiv.org/abs/2208.09734v1
https://arxiv.org/pdf/2208.09734v1.pdf
https://github.com/k-gyuhak/clom
false
false
true
pytorch
https://paperswithcode.com/paper/self-supervised-predictive-convolutional
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection
2111.09099
https://arxiv.org/abs/2111.09099v6
https://arxiv.org/pdf/2111.09099v6.pdf
https://github.com/wasve/DRAEM-SSPCAB
false
false
false
mindspore
https://paperswithcode.com/paper/ds-k3dom-3-d-dynamic-occupancy-mapping-with
DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory
2209.07764
https://arxiv.org/abs/2209.07764v2
https://arxiv.org/pdf/2209.07764v2.pdf
https://github.com/JuyeopHan/dsk3dom_public
true
true
true
none
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/code-implementation1/Code5/tree/main/lresnet100e_ir
false
false
false
mindspore
https://paperswithcode.com/paper/diffmatch-diffusion-model-for-dense-matching
Diffusion Model for Dense Matching
2305.19094
https://arxiv.org/abs/2305.19094v2
https://arxiv.org/pdf/2305.19094v2.pdf
https://github.com/KU-CVLAB/DiffMatch
true
false
true
pytorch
https://paperswithcode.com/paper/cute-lock-behavioral-and-structural-multi-key
Cute-Lock: Behavioral and Structural Multi-Key Logic Locking Using Time Base Keys
2501.17402
https://arxiv.org/abs/2501.17402v1
https://arxiv.org/pdf/2501.17402v1.pdf
https://github.com/cars-lab-repo/cute-lock
true
true
false
none
https://paperswithcode.com/paper/desed-dialogue-based-explanation-for-sentence
DESED: Dialogue-based Explanation for Sentence-level Event Detection
null
https://aclanthology.org/2022.coling-1.219
https://aclanthology.org/2022.coling-1.219.pdf
https://github.com/ydongd/desed
true
true
false
pytorch
https://paperswithcode.com/paper/mc-mlp-multiple-coordinate-frames-in-all-mlp
MC-MLP:Multiple Coordinate Frames in all-MLP Architecture for Vision
2304.03917
https://arxiv.org/abs/2304.03917v1
https://arxiv.org/pdf/2304.03917v1.pdf
https://github.com/zzm11/mc-mlp
true
true
false
pytorch
https://paperswithcode.com/paper/rigorous-dynamical-mean-field-theory-for
Rigorous dynamical mean field theory for stochastic gradient descent methods
2210.06591
https://arxiv.org/abs/2210.06591v3
https://arxiv.org/pdf/2210.06591v3.pdf
https://github.com/spoc-group/rigorous-dynamical-mean-field-theory
true
true
false
none
https://paperswithcode.com/paper/utilizing-supervised-models-to-infer
CROWDLAB: Supervised learning to infer consensus labels and quality scores for data with multiple annotators
2210.06812
https://arxiv.org/abs/2210.06812v2
https://arxiv.org/pdf/2210.06812v2.pdf
https://github.com/cleanlab/multiannotator-benchmarks
true
true
true
none
https://paperswithcode.com/paper/convolutional-conditional-neural-processes-1
Convolutional Conditional Neural Processes
1910.13556
https://arxiv.org/abs/1910.13556v5
https://arxiv.org/pdf/1910.13556v5.pdf
https://github.com/peterholderrieth/steerable_cnps
false
false
true
pytorch
https://paperswithcode.com/paper/divide-and-contrast-source-free-domain
Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning
2211.06612
https://arxiv.org/abs/2211.06612v1
https://arxiv.org/pdf/2211.06612v1.pdf
https://github.com/zyezhang/dac
true
true
true
pytorch
https://paperswithcode.com/paper/pkcam-previous-knowledge-channel-attention-1
PKCAM: Previous Knowledge Channel Attention Module
2211.07521
https://arxiv.org/abs/2211.07521v2
https://arxiv.org/pdf/2211.07521v2.pdf
https://github.com/eslambakr/emca
true
true
false
pytorch