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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/mobile-robot-path-planning-in-dynamic
Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learning
2005.05420
https://arxiv.org/abs/2005.05420v2
https://arxiv.org/pdf/2005.05420v2.pdf
https://github.com/Tushar-ml/G2RL-Path-Planning
false
false
true
tf
https://paperswithcode.com/paper/making-large-language-models-perform-better
Making Large Language Models Perform Better in Knowledge Graph Completion
2310.06671
https://arxiv.org/abs/2310.06671v2
https://arxiv.org/pdf/2310.06671v2.pdf
https://github.com/zjukg/kopa
true
true
true
pytorch
https://paperswithcode.com/paper/focalunetr-a-focal-transformer-for-boundary
FocalUNETR: A Focal Transformer for Boundary-aware Segmentation of CT Images
2210.03189
https://arxiv.org/abs/2210.03189v2
https://arxiv.org/pdf/2210.03189v2.pdf
https://github.com/chengyinlee/focalunetr
true
true
true
pytorch
https://paperswithcode.com/paper/focal-loss-for-dense-object-detection
Focal Loss for Dense Object Detection
1708.02002
http://arxiv.org/abs/1708.02002v2
http://arxiv.org/pdf/1708.02002v2.pdf
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet152
false
false
false
mindspore
https://paperswithcode.com/paper/sight-a-large-annotated-dataset-on-student
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts
2306.09343
https://arxiv.org/abs/2306.09343v1
https://arxiv.org/pdf/2306.09343v1.pdf
https://github.com/rosewang2008/sight
true
true
true
none
https://paperswithcode.com/paper/revealing-biases-in-the-sampling-of
Revealing biases in the sampling of ecological interaction networks
1708.01242
http://arxiv.org/abs/1708.01242v1
http://arxiv.org/pdf/1708.01242v1.pdf
https://github.com/cran/EcoNetGen
false
false
true
none
https://paperswithcode.com/paper/a-generative-machine-learning-approach-for
A Generative Machine Learning Approach for Improving Precipitation from Earth System Models
2406.15026
https://arxiv.org/abs/2406.15026v1
https://arxiv.org/pdf/2406.15026v1.pdf
https://github.com/p-hss/consistency-climate-downscaling
true
true
false
pytorch
https://paperswithcode.com/paper/clapeyron-jl-an-extensible-open-source-julia
Clapeyron.jl: An extensible, open-source fluid-thermodynamics toolkit
2201.08927
https://arxiv.org/abs/2201.08927v2
https://arxiv.org/pdf/2201.08927v2.pdf
https://github.com/ClapeyronThermo/Clapeyron.jl
false
false
true
none
https://paperswithcode.com/paper/laughter-synthesis-using-pseudo-phonetic
Laughter Synthesis using Pseudo Phonetic Tokens with a Large-scale In-the-wild Laughter Corpus
2305.12442
https://arxiv.org/abs/2305.12442v2
https://arxiv.org/pdf/2305.12442v2.pdf
https://github.com/aria-k-alethia/laughter-synthesis
true
true
true
pytorch
https://paperswithcode.com/paper/dbf-unet-a-two-stage-framework-for-carotid
DBF-UNet: A Two-Stage Framework for Carotid Artery Segmentation with Pseudo-Label Generation
2504.00908
https://arxiv.org/abs/2504.00908v1
https://arxiv.org/pdf/2504.00908v1.pdf
https://github.com/haoxuanli-thu/dbf-unet
true
true
false
pytorch
https://paperswithcode.com/paper/a-benchmark-dataset-for-understandable
Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation
2012.02420
https://arxiv.org/abs/2012.02420v2
https://arxiv.org/pdf/2012.02420v2.pdf
https://github.com/machinelearning4health/medlane
true
true
false
pytorch
https://paperswithcode.com/paper/beyond-english-centric-multilingual-machine
Beyond English-Centric Multilingual Machine Translation
2010.11125
https://arxiv.org/abs/2010.11125v1
https://arxiv.org/pdf/2010.11125v1.pdf
https://github.com/xhlulu/dl-translate
false
false
true
pytorch
https://paperswithcode.com/paper/client-wise-modality-selection-for-balanced
Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection
2401.00403
https://arxiv.org/abs/2401.00403v2
https://arxiv.org/pdf/2401.00403v2.pdf
https://github.com/fanyunfeng-bit/balanced-modality-selection-in-mfl
true
true
false
pytorch
https://paperswithcode.com/paper/no-language-left-behind-scaling-human-1
No Language Left Behind: Scaling Human-Centered Machine Translation
2207.04672
https://arxiv.org/abs/2207.04672v3
https://arxiv.org/pdf/2207.04672v3.pdf
https://github.com/xhlulu/dl-translate
false
false
true
pytorch
https://paperswithcode.com/paper/exposurediffusion-learning-to-expose-for-low
ExposureDiffusion: Learning to Expose for Low-light Image Enhancement
2307.07710
https://arxiv.org/abs/2307.07710v2
https://arxiv.org/pdf/2307.07710v2.pdf
https://github.com/wyf0912/ExposureDiffusion
true
true
true
pytorch
https://paperswithcode.com/paper/pyvrp-a-high-performance-vrp-solver-package
PyVRP: a high-performance VRP solver package
2403.13795
https://arxiv.org/abs/2403.13795v2
https://arxiv.org/pdf/2403.13795v2.pdf
https://github.com/informsjoc/2023.0055
true
true
false
none
https://paperswithcode.com/paper/genetic-programming-for-explainable-manifold
Genetic Programming for Explainable Manifold Learning
2403.14139
https://arxiv.org/abs/2403.14139v2
https://arxiv.org/pdf/2403.14139v2.pdf
https://github.com/cravies/gp-emal
true
true
false
none
https://paperswithcode.com/paper/audio-classification-with-dilated-convolution
Audio classification with Dilated Convolution with Learnable Spacings
2309.13972
https://arxiv.org/abs/2309.13972v2
https://arxiv.org/pdf/2309.13972v2.pdf
https://github.com/k-h-ismail/dcls-audio
true
true
true
pytorch
https://paperswithcode.com/paper/p1ac-revisiting-absolute-pose-from-a-single
P1AC: Revisiting Absolute Pose From a Single Affine Correspondence
2011.08790
https://arxiv.org/abs/2011.08790v6
https://arxiv.org/pdf/2011.08790v6.pdf
https://github.com/jonathanventura/p1ac
true
true
true
none
https://paperswithcode.com/paper/alternate-loss-functions-can-improve-the
Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks
2303.09935
https://arxiv.org/abs/2303.09935v4
https://arxiv.org/pdf/2303.09935v4.pdf
https://github.com/arindam-ds/alternate_loss_functions
true
false
true
none
https://paperswithcode.com/paper/assessing-keyness-using-permutation-tests
Assessing Keyness using Permutation Tests
2308.13383
https://arxiv.org/abs/2308.13383v1
https://arxiv.org/pdf/2308.13383v1.pdf
https://github.com/thmild/keyperm
true
true
false
none
https://paperswithcode.com/paper/towards-understanding-and-improving-knowledge
Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation
2305.08096
https://arxiv.org/abs/2305.08096v2
https://arxiv.org/pdf/2305.08096v2.pdf
https://github.com/songmzhang/nmt-kd
true
true
true
pytorch
https://paperswithcode.com/paper/a-one-stop-3d-target-reconstruction-and
A One Stop 3D Target Reconstruction and multilevel Segmentation Method
2308.06974
https://arxiv.org/abs/2308.06974v1
https://arxiv.org/pdf/2308.06974v1.pdf
https://github.com/ganlab/ostra
true
true
false
pytorch
https://paperswithcode.com/paper/fully-connected-spatial-temporal-graph-for
Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data
2309.05305
https://arxiv.org/abs/2309.05305v3
https://arxiv.org/pdf/2309.05305v3.pdf
https://github.com/Frank-Wang-oss/FCSTGNN
true
true
true
pytorch
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/ahmed-alllam/Equinox/blob/main/examples/deep_convolutional_gan.ipynb
false
false
false
jax
https://paperswithcode.com/paper/consistent-manifold-representation-for
Consistent Manifold Representation for Topological Data Analysis
1606.02353
http://arxiv.org/abs/1606.02353v2
http://arxiv.org/pdf/1606.02353v2.pdf
https://gitlab.com/datafold-dev/datafold
false
false
true
none
https://paperswithcode.com/paper/invisible-watermarking-for-audio-generation
Invisible Watermarking for Audio Generation Diffusion Models
2309.13166
https://arxiv.org/abs/2309.13166v2
https://arxiv.org/pdf/2309.13166v2.pdf
https://github.com/mikiyaxi/watermark-audio-diffusion
true
true
true
pytorch
https://paperswithcode.com/paper/3d-gres-generalized-3d-referring-expression
3D-GRES: Generalized 3D Referring Expression Segmentation
2407.20664
https://arxiv.org/abs/2407.20664v1
https://arxiv.org/pdf/2407.20664v1.pdf
https://github.com/sosppxo/3d-gres
false
true
true
none
https://paperswithcode.com/paper/ummaformer-a-universal-multimodal-adaptive-1
UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localization
2308.14395
https://arxiv.org/abs/2308.14395v1
https://arxiv.org/pdf/2308.14395v1.pdf
https://github.com/ymhzyj/UMMAFormer
true
true
true
pytorch
https://paperswithcode.com/paper/can-gnn-be-good-adapter-for-llms
Can GNN be Good Adapter for LLMs?
2402.12984
https://arxiv.org/abs/2402.12984v1
https://arxiv.org/pdf/2402.12984v1.pdf
https://github.com/hxttkl/GraphAdapter
true
false
true
pytorch
https://paperswithcode.com/paper/diffusionret-generative-text-video-retrieval
DiffusionRet: Generative Text-Video Retrieval with Diffusion Model
2303.09867
https://arxiv.org/abs/2303.09867v2
https://arxiv.org/pdf/2303.09867v2.pdf
https://github.com/jpthu17/diffusionret
true
true
true
pytorch
https://paperswithcode.com/paper/an-exhaustive-addis-principle-for-online-fwer
An exhaustive ADDIS principle for online FWER control
2308.13827
https://arxiv.org/abs/2308.13827v2
https://arxiv.org/pdf/2308.13827v2.pdf
https://github.com/fischer23/exhaustive-addis-procedures
true
true
false
none
https://paperswithcode.com/paper/link-prediction-for-wikipedia-articles-as-a
Link Prediction for Wikipedia Articles as a Natural Language Inference Task
2308.16469
https://arxiv.org/abs/2308.16469v2
https://arxiv.org/pdf/2308.16469v2.pdf
https://github.com/phanchauthang/dsaa-2023-kaggle
true
true
false
none
https://paperswithcode.com/paper/video-adverb-retrieval-with-compositional
Video-adverb retrieval with compositional adverb-action embeddings
2309.15086
https://arxiv.org/abs/2309.15086v1
https://arxiv.org/pdf/2309.15086v1.pdf
https://github.com/ExplainableML/ReGaDa
true
false
true
pytorch
https://paperswithcode.com/paper/eaglevision-object-level-attribute-multimodal
EagleVision: Object-level Attribute Multimodal LLM for Remote Sensing
2503.23330
https://arxiv.org/abs/2503.23330v1
https://arxiv.org/pdf/2503.23330v1.pdf
https://github.com/xiangtodayeatswhat/eaglevision
true
true
true
pytorch
https://paperswithcode.com/paper/mila-memory-based-instance-level-adaptation
MILA: Memory-Based Instance-Level Adaptation for Cross-Domain Object Detection
null
https://arxiv.org/abs/2309.01086v1
https://arxiv.org/pdf/2309.01086v1.pdf
https://github.com/hitachi-rd-cv/MILA
false
false
false
pytorch
https://paperswithcode.com/paper/investigating-the-interplay-between-features
Investigating the Interplay between Features and Structures in Graph Learning
2308.09570
https://arxiv.org/abs/2308.09570v1
https://arxiv.org/pdf/2308.09570v1.pdf
https://github.com/danielecastellana22/feature-structure-interplay-graph-learning
true
true
true
pytorch
https://paperswithcode.com/paper/masked-motion-predictors-are-strong-3d-action
Masked Motion Predictors are Strong 3D Action Representation Learners
2308.07092
https://arxiv.org/abs/2308.07092v1
https://arxiv.org/pdf/2308.07092v1.pdf
https://github.com/maoyunyao/mamp
true
true
true
pytorch
https://paperswithcode.com/paper/advancing-vision-transformers-with-group-mix
Advancing Vision Transformers with Group-Mix Attention
2311.15157
https://arxiv.org/abs/2311.15157v1
https://arxiv.org/pdf/2311.15157v1.pdf
https://github.com/ailab-cvc/groupmixformer
true
true
false
pytorch
https://paperswithcode.com/paper/a-contrastive-knowledge-transfer-framework
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning
2303.07599
https://arxiv.org/abs/2303.07599v1
https://arxiv.org/pdf/2303.07599v1.pdf
https://github.com/kaiqi123/cktf
true
true
true
pytorch
https://paperswithcode.com/paper/measuring-complex-refractive-index-through
Measuring complex refractive index through deeplearning-enabled optical reflectometry
null
https://iopscience.iop.org/article/10.1088/2053-1583/acc59b
https://scholar.google.com/scholar_url?url=https://iopscience.iop.org/article/10.1088/2053-1583/acc59b/pdf%3Fcasa_token%3DJFntSMpPW5YAAAAA:00qHoX_1d3Ut8J9SVbIlQ0-TlyOCIw5ZNmAIWhhw1Ypdj1v3MMxbZUzoLn-OAt2smr3hHUuZDCPrbCbuiVykoPIZrRJC&hl=en&sa=T&oi=ucasa&ct=ucasa&ei=v3kqZsDlCe2R6rQPt66KqAQ&scisig=AFWwaeY3pnqlcMbnZM64FtFG_Hzv
https://github.com/tigerwang3133/ReflectoNet
true
false
false
pytorch
https://paperswithcode.com/paper/ask-me-in-english-instead-cross-lingual
Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queries
2310.13132
https://arxiv.org/abs/2310.13132v2
https://arxiv.org/pdf/2310.13132v2.pdf
https://github.com/claws-lab/XLingEval
true
true
true
none
https://paperswithcode.com/paper/pixels-progressive-image-xemplar-based
PIXELS: Progressive Image Xemplar-based Editing with Latent Surgery
2501.09826
https://arxiv.org/abs/2501.09826v1
https://arxiv.org/pdf/2501.09826v1.pdf
https://github.com/amazon-science/pixels
true
true
false
pytorch
https://paperswithcode.com/paper/methods-for-systematic-study-of-nuclear
Methods for systematic study of nuclear structure in high-energy collisions
2302.14026
https://arxiv.org/abs/2302.14026v1
https://arxiv.org/pdf/2302.14026v1.pdf
https://github.com/mluzum/isobar-sampler
false
false
true
none
https://paperswithcode.com/paper/a-quic-implementation-for-ns-3
A QUIC Implementation for ns-3
1902.06121
https://arxiv.org/abs/1902.06121v2
https://arxiv.org/pdf/1902.06121v2.pdf
https://github.com/signetlabdei/quic
true
false
true
none
https://paperswithcode.com/paper/studying-short-range-nuclear-correlations
Studying short-range nuclear correlations using relativistic heavy-ion collisions
2312.10129
https://arxiv.org/abs/2312.10129v1
https://arxiv.org/pdf/2312.10129v1.pdf
https://github.com/mluzum/isobar-sampler
true
true
true
none
https://paperswithcode.com/paper/reusing-convolutional-neural-network-models
Reusing Convolutional Neural Network Models through Modularization and Composition
2311.04438
https://arxiv.org/abs/2311.04438v1
https://arxiv.org/pdf/2311.04438v1.pdf
https://github.com/qibinhang/cnnsplitter
true
true
false
pytorch
https://paperswithcode.com/paper/conformal-prediction-interval-for-dynamic
Conformal prediction interval for dynamic time-series
2010.09107
https://arxiv.org/abs/2010.09107v9
https://arxiv.org/pdf/2010.09107v9.pdf
https://github.com/hamrel-cxu/EnbPI
true
true
true
pytorch
https://paperswithcode.com/paper/conformal-anomaly-detection-on-spatio
Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data
2105.11886
https://arxiv.org/abs/2105.11886v2
https://arxiv.org/pdf/2105.11886v2.pdf
https://github.com/hamrel-cxu/EnbPI
false
false
true
pytorch
https://paperswithcode.com/paper/slowfast-networks-for-video-recognition
SlowFast Networks for Video Recognition
1812.03982
https://arxiv.org/abs/1812.03982v3
https://arxiv.org/pdf/1812.03982v3.pdf
https://github.com/tianfr/semantic-flow
false
false
true
pytorch
https://paperswithcode.com/paper/well-tempered-teleparallel-horndeski
Well-tempered teleparallel Horndeski cosmology: a teleparallel variation to the cosmological constant problem
2107.08762
https://arxiv.org/abs/2107.08762v3
https://arxiv.org/pdf/2107.08762v3.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/stealth-black-hole-perturbations-in-kinetic
Stealth black hole perturbations in kinetic gravity braiding
2007.06006
https://arxiv.org/abs/2007.06006v4
https://arxiv.org/pdf/2007.06006v4.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/policy-optimization-in-a-noisy-neighborhood-1
Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
2309.14597
https://arxiv.org/abs/2309.14597v3
https://arxiv.org/pdf/2309.14597v3.pdf
https://github.com/nathanrahn/return-landscapes
true
true
false
jax
https://paperswithcode.com/paper/gated-attention-coding-for-training-high
Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks
2308.06582
https://arxiv.org/abs/2308.06582v2
https://arxiv.org/pdf/2308.06582v2.pdf
https://github.com/bollossom/GAC
true
true
true
pytorch
https://paperswithcode.com/paper/a-zero-few-shot-anomaly-classification-and
APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD
2305.17382
https://arxiv.org/abs/2305.17382v3
https://arxiv.org/pdf/2305.17382v3.pdf
https://github.com/hq-deng/AnoVL
false
false
true
pytorch
https://paperswithcode.com/paper/grad-cam-visual-explanations-from-deep
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
1610.02391
https://arxiv.org/abs/1610.02391v4
https://arxiv.org/pdf/1610.02391v4.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/learning-important-features-through
Learning Important Features Through Propagating Activation Differences
1704.02685
https://arxiv.org/abs/1704.02685v2
https://arxiv.org/pdf/1704.02685v2.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/captum-a-unified-and-generic-model
Captum: A unified and generic model interpretability library for PyTorch
2009.07896
https://arxiv.org/abs/2009.07896v1
https://arxiv.org/pdf/2009.07896v1.pdf
https://github.com/pytorch/captum
true
false
true
pytorch
https://paperswithcode.com/paper/axiomatic-attribution-for-deep-networks
Axiomatic Attribution for Deep Networks
1703.01365
http://arxiv.org/abs/1703.01365v2
http://arxiv.org/pdf/1703.01365v2.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/visualizing-and-understanding-convolutional
Visualizing and Understanding Convolutional Networks
1311.2901
http://arxiv.org/abs/1311.2901v3
http://arxiv.org/pdf/1311.2901v3.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/smoothgrad-removing-noise-by-adding-noise
SmoothGrad: removing noise by adding noise
1706.03825
http://arxiv.org/abs/1706.03825v1
http://arxiv.org/pdf/1706.03825v1.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/how-important-is-a-neuron
How Important Is a Neuron?
1805.12233
http://arxiv.org/abs/1805.12233v1
http://arxiv.org/pdf/1805.12233v1.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/computationally-efficient-measures-of
Computationally Efficient Measures of Internal Neuron Importance
1807.09946
http://arxiv.org/abs/1807.09946v1
http://arxiv.org/pdf/1807.09946v1.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/influence-directed-explanations-for-deep
Influence-Directed Explanations for Deep Convolutional Networks
1802.03788
http://arxiv.org/abs/1802.03788v2
http://arxiv.org/pdf/1802.03788v2.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/how-sensitive-are-sensitivity-based
On the (In)fidelity and Sensitivity for Explanations
1901.09392
https://arxiv.org/abs/1901.09392v4
https://arxiv.org/pdf/1901.09392v4.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/feature-dropout-revisiting-the-role-of
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
null
https://openreview.net/forum?id=M7hijAPA4B
https://openreview.net/pdf?id=M7hijAPA4B
https://github.com/xiluohe/feature-dropout
true
true
false
pytorch
https://paperswithcode.com/paper/estimating-training-data-influence-by
Estimating Training Data Influence by Tracing Gradient Descent
2002.08484
https://arxiv.org/abs/2002.08484v3
https://arxiv.org/pdf/2002.08484v3.pdf
https://github.com/pytorch/captum
false
false
true
pytorch
https://paperswithcode.com/paper/improving-online-continual-learning
Improving Online Continual Learning Performance and Stability with Temporal Ensembles
2306.16817
https://arxiv.org/abs/2306.16817v2
https://arxiv.org/pdf/2306.16817v2.pdf
https://github.com/albinsou/online_ema
true
true
true
pytorch
https://paperswithcode.com/paper/reading-between-the-lines-modeling-user
Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming
2210.14306
https://arxiv.org/abs/2210.14306v5
https://arxiv.org/pdf/2210.14306v5.pdf
https://github.com/microsoft/coderec_programming_states
true
true
true
none
https://paperswithcode.com/paper/self-similarity-based-and-novelty-based-loss
Self-Similarity-Based and Novelty-based loss for music structure analysis
2309.02243
https://arxiv.org/abs/2309.02243v1
https://arxiv.org/pdf/2309.02243v1.pdf
https://github.com/geoffroypeeters/ssmnet_ISMIR2023
true
true
true
pytorch
https://paperswithcode.com/paper/enhancing-joint-multiple-intent-detection-and
Enhancing Joint Multiple Intent Detection and Slot Filling with Global Intent-Slot Co-occurrence
null
https://aclanthology.org/2022.emnlp-main.543/
https://aclanthology.org/2022.emnlp-main.543.pdf
https://github.com/smxiao/GISCo
false
true
false
pytorch
https://paperswithcode.com/paper/task-oriented-communication-for-edge-video
Task-Oriented Communication for Edge Video Analytics
2211.14049
https://arxiv.org/abs/2211.14049v3
https://arxiv.org/pdf/2211.14049v3.pdf
https://github.com/shaojiawei07/tocom-tem
true
true
true
pytorch
https://paperswithcode.com/paper/task-oriented-communication-for-multi-device
Task-Oriented Communication for Multi-Device Cooperative Edge Inference
2109.00172
https://arxiv.org/abs/2109.00172v3
https://arxiv.org/pdf/2109.00172v3.pdf
https://github.com/shaojiawei07/tocom-tem
false
false
true
pytorch
https://paperswithcode.com/paper/few-shot-medical-image-segmentation-via-a
Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer
2309.04825
https://arxiv.org/abs/2309.04825v1
https://arxiv.org/pdf/2309.04825v1.pdf
https://github.com/yazhouzhu19/rpt
true
true
false
pytorch
https://paperswithcode.com/paper/parameter-efficient-language-model-tuning
Parameter-Efficient Language Model Tuning with Active Learning in Low-Resource Settings
2305.14576
https://arxiv.org/abs/2305.14576v2
https://arxiv.org/pdf/2305.14576v2.pdf
https://github.com/josipjukic/adapter-al
true
true
false
pytorch
https://paperswithcode.com/paper/llm4plc-harnessing-large-language-models-for
LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems
2401.05443
https://arxiv.org/abs/2401.05443v1
https://arxiv.org/pdf/2401.05443v1.pdf
https://github.com/AICPS/LLM_4_PLC
true
false
false
none
https://paperswithcode.com/paper/multiview-detection-with-feature-perspective
Multiview Detection with Feature Perspective Transformation
2007.07247
https://arxiv.org/abs/2007.07247v2
https://arxiv.org/pdf/2007.07247v2.pdf
https://github.com/shaojiawei07/tocom-tem
false
false
true
pytorch
https://paperswithcode.com/paper/controlling-large-language-models-to-generate
Large Language Models for Code: Security Hardening and Adversarial Testing
2302.05319
https://arxiv.org/abs/2302.05319v5
https://arxiv.org/pdf/2302.05319v5.pdf
https://github.com/eth-sri/sven
true
true
true
none
https://paperswithcode.com/paper/a-conversational-paradigm-for-program
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
2203.13474
https://arxiv.org/abs/2203.13474v5
https://arxiv.org/pdf/2203.13474v5.pdf
https://github.com/eth-sri/sven
false
false
true
none
https://paperswithcode.com/paper/event-stream-based-visual-object-tracking-a
Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline
2309.14611
https://arxiv.org/abs/2309.14611v1
https://arxiv.org/pdf/2309.14611v1.pdf
https://github.com/event-ahu/coesot
true
true
true
pytorch
https://paperswithcode.com/paper/treating-motion-as-option-with-output
Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation
2309.14786
https://arxiv.org/abs/2309.14786v1
https://arxiv.org/pdf/2309.14786v1.pdf
https://github.com/suhwan-cho/tmo
true
true
true
pytorch
https://paperswithcode.com/paper/formalmath-benchmarking-formal-mathematical
FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models
2505.02735
https://arxiv.org/abs/2505.02735v1
https://arxiv.org/pdf/2505.02735v1.pdf
https://github.com/sphere-ai-lab/formalmath-bench
true
true
true
pytorch
https://paperswithcode.com/paper/catch-me-if-you-search-when-contextual-web
Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
2504.01153
https://arxiv.org/abs/2504.01153v3
https://arxiv.org/pdf/2504.01153v3.pdf
https://github.com/MahjabinNahar/CatchMeIfYouSearch
true
true
true
none
https://paperswithcode.com/paper/llama-open-and-efficient-foundation-language-1
LLaMA: Open and Efficient Foundation Language Models
2302.13971
https://arxiv.org/abs/2302.13971v1
https://arxiv.org/pdf/2302.13971v1.pdf
https://github.com/xzhang97666/alpacare
false
false
true
none
https://paperswithcode.com/paper/llama-2-open-foundation-and-fine-tuned-chat
Llama 2: Open Foundation and Fine-Tuned Chat Models
2307.09288
https://arxiv.org/abs/2307.09288v2
https://arxiv.org/pdf/2307.09288v2.pdf
https://github.com/xzhang97666/alpacare
false
false
true
none
https://paperswithcode.com/paper/efficiently-modeling-long-sequences-with-1
Efficiently Modeling Long Sequences with Structured State Spaces
2111.00396
https://arxiv.org/abs/2111.00396v3
https://arxiv.org/pdf/2111.00396v3.pdf
https://github.com/nicolaszucchet/minimal-lru
false
false
true
jax
https://paperswithcode.com/paper/resurrecting-recurrent-neural-networks-for
Resurrecting Recurrent Neural Networks for Long Sequences
2303.06349
https://arxiv.org/abs/2303.06349v1
https://arxiv.org/pdf/2303.06349v1.pdf
https://github.com/nicolaszucchet/minimal-lru
false
false
true
jax
https://paperswithcode.com/paper/classification-of-influenza-hemagglutinin
Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks
2108.04240
https://arxiv.org/abs/2108.04240v1
https://arxiv.org/pdf/2108.04240v1.pdf
https://gitlab.com/charalambos.chrysostomou/embc21_influenza
true
false
false
tf
https://paperswithcode.com/paper/a-simple-latent-diffusion-approach-for
A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting
2401.10227
https://arxiv.org/abs/2401.10227v2
https://arxiv.org/pdf/2401.10227v2.pdf
https://github.com/segments-ai/latent-diffusion-segmentation
true
true
true
pytorch
https://paperswithcode.com/paper/counterfactual-prediction-under-selective
Counterfactual Prediction Under Selective Confounding
2310.14064
https://arxiv.org/abs/2310.14064v1
https://arxiv.org/pdf/2310.14064v1.pdf
https://github.com/sohaib730/causalml
true
true
false
none
https://paperswithcode.com/paper/svdd-2024-the-inaugural-singing-voice
SVDD 2024: The Inaugural Singing Voice Deepfake Detection Challenge
2408.16132
https://arxiv.org/abs/2408.16132v2
https://arxiv.org/pdf/2408.16132v2.pdf
https://github.com/svddchallenge/ctrsvdd2024_baseline
true
true
true
pytorch
https://paperswithcode.com/paper/from-chebnet-to-chebgibbsnet-1
From ChebNet to ChebGibbsNet
2412.01789
https://arxiv.org/abs/2412.01789v1
https://arxiv.org/pdf/2412.01789v1.pdf
https://github.com/hazdzz/ChebGibbsNet
true
false
true
pytorch
https://paperswithcode.com/paper/attention-guided-residual-u-net-with-se
Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy Images
null
https://doi.org/10.1089/cmb.2023.0446
https://doi.org/10.1089/cmb.2023.0446
https://github.com/jovialniyo93/cell-segmentation
false
false
false
tf
https://paperswithcode.com/paper/how-large-language-models-are-transforming
How Large Language Models are Transforming Machine-Paraphrased Plagiarism
2210.03568
https://arxiv.org/abs/2210.03568v3
https://arxiv.org/pdf/2210.03568v3.pdf
https://github.com/jpwahle/emnlp23-paraphrase-types
false
false
true
pytorch
https://paperswithcode.com/paper/ssd-single-shot-multibox-detector
SSD: Single Shot MultiBox Detector
1512.02325
http://arxiv.org/abs/1512.02325v5
http://arxiv.org/pdf/1512.02325v5.pdf
https://github.com/lufficc/SSD
false
false
true
pytorch
https://paperswithcode.com/paper/colmap-pcd-an-open-source-tool-for-fine-image
Colmap-PCD: An Open-source Tool for Fine Image-to-point cloud Registration
2310.05504
https://arxiv.org/abs/2310.05504v1
https://arxiv.org/pdf/2310.05504v1.pdf
https://github.com/xiaobaiiiiii/colmap-pcd
true
true
true
none
https://paperswithcode.com/paper/commander-s-intent-a-dataset-and-modeling
A Computational Interface to Translate Strategic Intent from Unstructured Language in a Low-Data Setting
2208.08374
https://arxiv.org/abs/2208.08374v2
https://arxiv.org/pdf/2208.08374v2.pdf
https://github.com/anonymousturtle433/anonymized-code
true
true
false
pytorch
https://paperswithcode.com/paper/an-interpretable-clustering-approach-to
An interpretable clustering approach to safety climate analysis: examining driver group distinction in safety climate perceptions
2310.19841
https://arxiv.org/abs/2310.19841v1
https://arxiv.org/pdf/2310.19841v1.pdf
https://github.com/nus-dbe/truck-driver-safety-climate
true
true
false
none
https://paperswithcode.com/paper/self-supervised-one-shot-learning-for
Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images
2303.05639
https://arxiv.org/abs/2303.05639v3
https://arxiv.org/pdf/2303.05639v3.pdf
https://github.com/avm-debatr/ganecdotes
true
true
true
pytorch
https://paperswithcode.com/paper/self-instruct-aligning-language-model-with
Self-Instruct: Aligning Language Models with Self-Generated Instructions
2212.10560
https://arxiv.org/abs/2212.10560v2
https://arxiv.org/pdf/2212.10560v2.pdf
https://github.com/xzhang97666/alpacare
false
false
true
none