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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/random-reshuffling-for-stochastic-gradient
Random Reshuffling for Stochastic Gradient Langevin Dynamics
2501.16055
https://arxiv.org/abs/2501.16055v1
https://arxiv.org/pdf/2501.16055v1.pdf
https://github.com/lshaw8317/RandomReshuffleSGLD
true
false
false
pytorch
https://paperswithcode.com/paper/optimizing-near-field-computation-in-the
Optimizing Near Field Computation in the MLFMA Algorithm with Data Redundancy and Performance Modeling on a Single GPU
2403.01596
https://arxiv.org/abs/2403.01596v1
https://arxiv.org/pdf/2403.01596v1.pdf
https://github.com/mortezamsp/P2P_with_data_redundancy
true
false
true
none
https://paperswithcode.com/paper/fusionaudio-1-2m-towards-fine-grained-audio
FusionAudio-1.2M: Towards Fine-grained Audio Captioning with Multimodal Contextual Fusion
2506.01111
https://arxiv.org/abs/2506.01111v1
https://arxiv.org/pdf/2506.01111v1.pdf
https://github.com/satsuki2486441738/fusionaudio
true
true
true
jax
https://paperswithcode.com/paper/fastabx-a-library-for-efficient-computation
fastabx: A library for efficient computation of ABX discriminability
2505.02692
https://arxiv.org/abs/2505.02692v1
https://arxiv.org/pdf/2505.02692v1.pdf
https://github.com/bootphon/fastabx
true
true
true
pytorch
https://paperswithcode.com/paper/racnn-residual-attention-convolutional-neural
RACNN: Residual Attention Convolutional Neural Network for Near-Field Channel Estimation in 6G Wireless Communications
2503.02299
https://arxiv.org/abs/2503.02299v3
https://arxiv.org/pdf/2503.02299v3.pdf
https://github.com/DoHaiSon/RACNN
true
true
false
tf
https://paperswithcode.com/paper/transpl-vq-code-transition-matrices-for
TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation
2505.09955
https://arxiv.org/abs/2505.09955v1
https://arxiv.org/pdf/2505.09955v1.pdf
https://github.com/eai-lab/transpl
true
true
false
pytorch
https://paperswithcode.com/paper/an-invitation-to-tropical-alexandrov
An Invitation to Tropical Alexandrov Curvature
2105.07423
https://arxiv.org/abs/2105.07423v3
https://arxiv.org/pdf/2105.07423v3.pdf
https://github.com/antheamonod/TropAlex
true
true
true
none
https://paperswithcode.com/paper/a-multi-modal-neural-geometric-solver-with
A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram
2302.11097
https://arxiv.org/abs/2302.11097v2
https://arxiv.org/pdf/2302.11097v2.pdf
https://github.com/mingliangzhang2018/pgps
true
true
true
pytorch
https://paperswithcode.com/paper/socialjax-an-evaluation-suite-for-multi-agent
SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas
2503.14576
https://arxiv.org/abs/2503.14576v2
https://arxiv.org/pdf/2503.14576v2.pdf
https://github.com/cooperativex/socialjax
true
true
true
jax
https://paperswithcode.com/paper/seg-zero-reasoning-chain-guided-segmentation
Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement
2503.06520
https://arxiv.org/abs/2503.06520v1
https://arxiv.org/pdf/2503.06520v1.pdf
https://github.com/dvlab-research/VisionReasoner
false
false
true
pytorch
https://paperswithcode.com/paper/mri-super-resolution-reconstruction-using
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting
2503.01576
https://arxiv.org/abs/2503.01576v2
https://arxiv.org/pdf/2503.01576v2.pdf
https://github.com/mosaf/res-srdiff
true
true
true
pytorch
https://paperswithcode.com/paper/learning-hierarchical-prompt-with-structured
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
2312.06323
https://arxiv.org/abs/2312.06323v1
https://arxiv.org/pdf/2312.06323v1.pdf
https://github.com/vill-lab/2024-aaai-hpt
true
true
true
pytorch
https://paperswithcode.com/paper/hpt-hierarchically-prompting-vision-language
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
2408.14812
https://arxiv.org/abs/2408.14812v1
https://arxiv.org/pdf/2408.14812v1.pdf
https://github.com/vill-lab/2024-aaai-hpt
false
false
true
pytorch
https://paperswithcode.com/paper/learning-to-prompt-for-vision-language-models
Learning to Prompt for Vision-Language Models
2109.01134
https://arxiv.org/abs/2109.01134v6
https://arxiv.org/pdf/2109.01134v6.pdf
https://github.com/vill-lab/2024-aaai-hpt
false
false
true
pytorch
https://paperswithcode.com/paper/conditional-prompt-learning-for-vision
Conditional Prompt Learning for Vision-Language Models
2203.05557
https://arxiv.org/abs/2203.05557v2
https://arxiv.org/pdf/2203.05557v2.pdf
https://github.com/vill-lab/2024-aaai-hpt
false
false
true
pytorch
https://paperswithcode.com/paper/trajectory-class-aware-multi-agent
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
2503.01440
https://arxiv.org/abs/2503.01440v1
https://arxiv.org/pdf/2503.01440v1.pdf
https://github.com/aailab-kaist/trama
true
true
false
pytorch
https://paperswithcode.com/paper/nbnet-noise-basis-learning-for-image
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
2012.15028
https://arxiv.org/abs/2012.15028v2
https://arxiv.org/pdf/2012.15028v2.pdf
https://github.com/MindSpore-scientific-2/code-4/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
false
false
false
mindspore
https://paperswithcode.com/paper/full-scale-representation-guided-network-for
Full-scale Representation Guided Network for Retinal Vessel Segmentation
2501.18921
https://arxiv.org/abs/2501.18921v1
https://arxiv.org/pdf/2501.18921v1.pdf
https://github.com/zombasy/fsg-net-pytorch
true
true
true
pytorch
https://paperswithcode.com/paper/generalized-recorrupted-to-recorrupted-self
Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise
2412.04648
https://arxiv.org/abs/2412.04648v2
https://arxiv.org/pdf/2412.04648v2.pdf
https://github.com/deepinv/deepinv
false
true
false
pytorch
https://paperswithcode.com/paper/satori-towards-proactive-ar-assistant-with
Satori: Towards Proactive AR Assistant with Belief-Desire-Intention User Modeling
2410.16668
https://arxiv.org/abs/2410.16668v3
https://arxiv.org/pdf/2410.16668v3.pdf
https://github.com/vida-nyu/satori-assistance
true
true
true
pytorch
https://paperswithcode.com/paper/vmts-vision-assisted-teacher-student
VMTS: Vision-Assisted Teacher-Student Reinforcement Learning for Multi-Terrain Locomotion in Bipedal Robots
2503.07049
https://arxiv.org/abs/2503.07049v1
https://arxiv.org/pdf/2503.07049v1.pdf
https://github.com/chenfu-user/VMTS
true
false
true
pytorch
https://paperswithcode.com/paper/ethosgpt-mapping-human-value-diversity-to
EthosGPT: Mapping Human Value Diversity to Advance Sustainable Development Goals (SDGs)
2504.09861
https://arxiv.org/abs/2504.09861v1
https://arxiv.org/pdf/2504.09861v1.pdf
https://github.com/sunshineluyao/EthosGPT
false
true
false
none
https://paperswithcode.com/paper/q-eval-100k-evaluating-visual-quality-and
Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content
2503.02357
https://arxiv.org/abs/2503.02357v2
https://arxiv.org/pdf/2503.02357v2.pdf
https://github.com/zzc-1998/q-eval
true
true
true
pytorch
https://paperswithcode.com/paper/cmmloc-advancing-text-to-pointcloud
CMMLoc: Advancing Text-to-PointCloud Localization with Cauchy-Mixture-Model Based Framework
2503.02593
https://arxiv.org/abs/2503.02593v2
https://arxiv.org/pdf/2503.02593v2.pdf
https://github.com/kevin301342/cmmloc
true
true
true
pytorch
https://paperswithcode.com/paper/leveraging-optimization-for-adaptive-attacks
Leveraging Optimization for Adaptive Attacks on Image Watermarks
2309.16952
https://arxiv.org/abs/2309.16952v2
https://arxiv.org/pdf/2309.16952v2.pdf
https://github.com/nilslukas/adaptive-watermark-attacks
true
false
true
pytorch
https://paperswithcode.com/paper/exploring-the-physical-properties-of-type-ii
Exploring the physical properties of Type II Quasar candidates at intermediate redshifts with CIGALE
2503.03547
https://arxiv.org/abs/2503.03547v1
https://arxiv.org/pdf/2503.03547v1.pdf
https://github.com/pedro-acunha/AMELIA
true
true
false
none
https://paperswithcode.com/paper/flexible-and-probabilistic-topology-tracking
Flexible and Probabilistic Topology Tracking with Partial Optimal Transport
2302.02895
https://arxiv.org/abs/2302.02895v3
https://arxiv.org/pdf/2302.02895v3.pdf
https://github.com/tdavislab/gwmt
true
true
false
none
https://paperswithcode.com/paper/preference-diffusion-for-recommendation
Preference Diffusion for Recommendation
2410.13117
https://arxiv.org/abs/2410.13117v2
https://arxiv.org/pdf/2410.13117v2.pdf
https://github.com/lswhim/preferdiff
true
true
false
pytorch
https://paperswithcode.com/paper/dafi-an-open-source-framework-for-ensemble
DAFI: An Open-Source Framework for Ensemble-Based Data Assimilation and Field Inversion
2012.02651
https://arxiv.org/abs/2012.02651v1
https://arxiv.org/pdf/2012.02651v1.pdf
https://github.com/xiaoh/DAFI
true
true
true
none
https://paperswithcode.com/paper/regularized-ensemble-kalman-methods-for
Regularized Ensemble Kalman Methods for Inverse Problems
1910.01292
http://arxiv.org/abs/1910.01292v2
http://arxiv.org/pdf/1910.01292v2.pdf
https://github.com/xiaoh/DAFI
true
true
true
none
https://paperswithcode.com/paper/evaluation-of-ensemble-methods-for
Evaluation of ensemble methods for quantifying uncertainties in steady-state CFD applications with small ensemble sizes
2004.05541
http://arxiv.org/abs/2004.05541v1
http://arxiv.org/pdf/2004.05541v1.pdf
https://github.com/xiaoh/DAFI
true
false
true
none
https://paperswithcode.com/paper/talk-is-not-always-cheap-promoting-wireless
Talk is Not Always Cheap: Promoting Wireless Sensing Models with Text Prompts
2504.14621
https://arxiv.org/abs/2504.14621v1
https://arxiv.org/pdf/2504.14621v1.pdf
https://github.com/yangzhenkui/witalk
true
true
true
pytorch
https://paperswithcode.com/paper/fast-deep-learning-for-automatic-modulation
Fast Deep Learning for Automatic Modulation Classification
1901.05850
http://arxiv.org/abs/1901.05850v1
http://arxiv.org/pdf/1901.05850v1.pdf
https://github.com/dharaspatel/CNN_Signal_Classification
false
false
true
none
https://paperswithcode.com/paper/visual-sketchpad-sketching-as-a-visual-chain
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
2406.09403
https://arxiv.org/abs/2406.09403v3
https://arxiv.org/pdf/2406.09403v3.pdf
https://github.com/zhaochen0110/openthinkimg
false
false
true
pytorch
https://paperswithcode.com/paper/a-comparison-of-the-effects-of-different
A comparison of the effects of different methodologies on the statistics learning profiles of prospective primary education teachers from a gender perspective
2402.05479
https://arxiv.org/abs/2402.05479v1
https://arxiv.org/pdf/2402.05479v1.pdf
https://github.com/zhaochen0110/openthinkimg
false
false
true
pytorch
https://paperswithcode.com/paper/a-retrospective-systematic-study-on
A Retrospective Systematic Study on Hierarchical Sparse Query Transformer-assisted Ultrasound Screening for Early Hepatocellular Carcinoma
2502.03772
https://arxiv.org/abs/2502.03772v1
https://arxiv.org/pdf/2502.03772v1.pdf
https://github.com/Asunatan/HSQformer
true
true
true
pytorch
https://paperswithcode.com/paper/every-call-is-precious-global-optimization-of
Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants
2502.04290
https://arxiv.org/abs/2502.04290v1
https://arxiv.org/pdf/2502.04290v1.pdf
https://github.com/fouratifares/ECP
true
false
true
none
https://paperswithcode.com/paper/medalpaca-an-open-source-collection-of
MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data
2304.08247
https://arxiv.org/abs/2304.08247v2
https://arxiv.org/pdf/2304.08247v2.pdf
https://github.com/tuneinsight/federated-llms
false
false
true
pytorch
https://paperswithcode.com/paper/2506-06407
TimeWak: Temporal Chained-Hashing Watermark for Time Series Data
2506.06407
https://arxiv.org/abs/2506.06407v2
https://arxiv.org/pdf/2506.06407v2.pdf
https://github.com/soizhiwen/TimeWak
true
true
false
pytorch
https://paperswithcode.com/paper/profiling-electric-vehicles-via-early
Profiling Electric Vehicles via Early Charging Voltage Patterns
2506.07714
https://arxiv.org/abs/2506.07714v1
https://arxiv.org/pdf/2506.07714v1.pdf
https://github.com/spritz-group/EV-Volt-Auth
true
true
false
none
https://paperswithcode.com/paper/interactrank-personalized-web-scale-search
InteractRank: Personalized Web-Scale Search Pre-Ranking with Cross Interaction Features
2504.06609
https://arxiv.org/abs/2504.06609v1
https://arxiv.org/pdf/2504.06609v1.pdf
https://github.com/pinterest/atg-research
true
true
false
pytorch
https://paperswithcode.com/paper/copyspec-accelerating-llms-with-speculative
CopySpec: Accelerating LLMs with Speculative Copy-and-Paste Without Compromising Quality
2502.08923
https://arxiv.org/abs/2502.08923v1
https://arxiv.org/pdf/2502.08923v1.pdf
https://github.com/razvandu/copyspec
true
true
true
pytorch
https://paperswithcode.com/paper/cvalues-measuring-the-values-of-chinese-large
CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility
2307.09705
https://arxiv.org/abs/2307.09705v1
https://arxiv.org/pdf/2307.09705v1.pdf
https://github.com/sunshineluyao/EthosGPT
false
false
true
none
https://paperswithcode.com/paper/how-well-do-llms-represent-values-across
How Well Do LLMs Represent Values Across Cultures? Empirical Analysis of LLM Responses Based on Hofstede Cultural Dimensions
2406.14805
https://arxiv.org/abs/2406.14805v1
https://arxiv.org/pdf/2406.14805v1.pdf
https://github.com/sunshineluyao/EthosGPT
false
false
true
none
https://paperswithcode.com/paper/culturellm-incorporating-cultural-differences
CultureLLM: Incorporating Cultural Differences into Large Language Models
2402.10946
https://arxiv.org/abs/2402.10946v3
https://arxiv.org/pdf/2402.10946v3.pdf
https://github.com/sunshineluyao/EthosGPT
false
false
true
none
https://paperswithcode.com/paper/nextou-efficient-topology-aware-u-net-for
NexToU: Efficient Topology-Aware U-Net for Medical Image Segmentation
2305.15911
https://arxiv.org/abs/2305.15911v1
https://arxiv.org/pdf/2305.15911v1.pdf
https://github.com/PengchengShi1220/AortaSeg24
false
false
true
pytorch
https://paperswithcode.com/paper/mc-2-a-multilingual-corpus-of-minority
MC$^2$: Towards Transparent and Culturally-Aware NLP for Minority Languages in China
2311.08348
https://arxiv.org/abs/2311.08348v2
https://arxiv.org/pdf/2311.08348v2.pdf
https://github.com/luciusssss/mc2_corpus
true
true
true
none
https://paperswithcode.com/paper/mganet-a-robust-model-for-quality-enhancement
MGANet: A Robust Model for Quality Enhancement of Compressed Video
1811.09150
http://arxiv.org/abs/1811.09150v4
http://arxiv.org/pdf/1811.09150v4.pdf
https://github.com/MindSpore-scientific/code-8/tree/main/mgan-mindspore
false
false
false
mindspore
https://paperswithcode.com/paper/ptwt-the-pytorch-wavelet-toolbox
ptwt - The PyTorch Wavelet Toolbox
null
https://jmlr.org/papers/v25/23-0636.html
https://jmlr.org/papers/volume25/23-0636/23-0636.pdf
https://github.com/v0lta/pytorch-wavelet-toolbox
false
false
false
pytorch
https://paperswithcode.com/paper/scalable-image-coding-for-humans-and-machines
Scalable Image Coding for Humans and Machines
2107.08373
https://arxiv.org/abs/2107.08373v2
https://arxiv.org/pdf/2107.08373v2.pdf
https://github.com/InterDigitalInc/CompressAI-Vision/blob/main/compressai_vision/codecs/sic_sfu2022.py
false
false
false
pytorch
https://paperswithcode.com/paper/gradient-surgery-for-multi-task-learning-1
Gradient Surgery for Multi-Task Learning
2001.06782
https://arxiv.org/abs/2001.06782v4
https://arxiv.org/pdf/2001.06782v4.pdf
https://github.com/MindSpore-scientific/code-10/tree/main/PCGrad-mindspore-example
false
false
false
mindspore
https://paperswithcode.com/paper/pyslam-an-open-source-modular-and-extensible
pySLAM: An Open-Source, Modular, and Extensible Framework for SLAM
2502.11955
https://arxiv.org/abs/2502.11955v2
https://arxiv.org/pdf/2502.11955v2.pdf
https://github.com/luigifreda/pyslam
true
false
true
pytorch
https://paperswithcode.com/paper/a-comprehensive-survey-of-mixture-of-experts
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
2503.07137
https://arxiv.org/abs/2503.07137v3
https://arxiv.org/pdf/2503.07137v3.pdf
https://github.com/deepseek-ai/DeepEP
true
false
false
pytorch
https://paperswithcode.com/paper/smtpd-a-new-benchmark-for-temporal-prediction
SMTPD: A New Benchmark for Temporal Prediction of Social Media Popularity
2503.04446
https://arxiv.org/abs/2503.04446v1
https://arxiv.org/pdf/2503.04446v1.pdf
https://github.com/zhuwei321/smtpd
true
true
true
pytorch
https://paperswithcode.com/paper/khuri-treiman-equations-for-3p-decays-of
Khuri-Treiman equations for $3π$ decays of particles with spin
1910.03107
https://arxiv.org/abs/1910.03107v1
https://arxiv.org/pdf/1910.03107v1.pdf
https://github.com/dwinney/jpacTriangle
false
false
true
none
https://paperswithcode.com/paper/navigation-world-models
Navigation World Models
2412.03572
https://arxiv.org/abs/2412.03572v2
https://arxiv.org/pdf/2412.03572v2.pdf
https://github.com/facebookresearch/nwm
false
false
true
pytorch
https://paperswithcode.com/paper/inn-par-invertible-neural-network-for-ppg-to
INN-PAR: Invertible Neural Network for PPG to ABP Reconstruction
2409.09021
https://arxiv.org/abs/2409.09021v2
https://arxiv.org/pdf/2409.09021v2.pdf
https://github.com/soumitra1992/innpar-ppg2abp
true
true
true
pytorch
https://paperswithcode.com/paper/energy-efficient-federated-learning-for-aiot
Energy-Efficient Federated Learning for AIoT using Clustering Methods
2505.09704
https://arxiv.org/abs/2505.09704v1
https://arxiv.org/pdf/2505.09704v1.pdf
https://github.com/robertomatheuspp/clustering_ee_fl
true
false
false
pytorch
https://paperswithcode.com/paper/elucidating-the-design-space-of-diffusion
Elucidating the Design Space of Diffusion-Based Generative Models
2206.00364
https://arxiv.org/abs/2206.00364v2
https://arxiv.org/pdf/2206.00364v2.pdf
https://github.com/dopplerchase/cira-diff
false
false
true
pytorch
https://paperswithcode.com/paper/denoising-diffusion-probabilistic-models
Denoising Diffusion Probabilistic Models
2006.11239
https://arxiv.org/abs/2006.11239v2
https://arxiv.org/pdf/2006.11239v2.pdf
https://github.com/dopplerchase/cira-diff
false
false
true
pytorch
https://paperswithcode.com/paper/arxivdigestables-synthesizing-scientific
ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models
2410.22360
https://arxiv.org/abs/2410.22360v1
https://arxiv.org/pdf/2410.22360v1.pdf
https://github.com/allenai/ai2-scholarqa-lib
false
false
true
pytorch
https://paperswithcode.com/paper/efficient-reasoning-models-a-survey
Efficient Reasoning Models: A Survey
2504.10903
https://arxiv.org/abs/2504.10903v1
https://arxiv.org/pdf/2504.10903v1.pdf
https://github.com/fscdc/awesome-efficient-reasoning-models
true
true
true
none
https://paperswithcode.com/paper/perfcam-digital-twinning-for-production-lines
PerfCam: Digital Twinning for Production Lines Using 3D Gaussian Splatting and Vision Models
2504.18165
https://arxiv.org/abs/2504.18165v1
https://arxiv.org/pdf/2504.18165v1.pdf
https://github.com/AstraZeneca/PerfCam
true
false
false
none
https://paperswithcode.com/paper/dfpn-deformable-frame-prediction-network
DFPN: Deformable Frame Prediction Network
2105.12794
https://arxiv.org/abs/2105.12794v1
https://arxiv.org/pdf/2105.12794v1.pdf
https://github.com/KUIS-AI-Tekalp-Research-Group/frame-prediction
false
false
true
pytorch
https://paperswithcode.com/paper/rsafe-incentivizing-proactive-reasoning-to
RSafe: Incentivizing proactive reasoning to build robust and adaptive LLM safeguards
2506.07736
https://arxiv.org/abs/2506.07736v1
https://arxiv.org/pdf/2506.07736v1.pdf
https://github.com/sophiezheng998/rsafe
true
true
false
pytorch
https://paperswithcode.com/paper/reinforcement-learning-for-reasoning-in-small
Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't
2503.16219
https://arxiv.org/abs/2503.16219v1
https://arxiv.org/pdf/2503.16219v1.pdf
https://github.com/knoveleng/open-rs
true
true
true
pytorch
https://paperswithcode.com/paper/2505-11239
Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks
2505.11239
https://arxiv.org/abs/2505.11239v2
https://arxiv.org/pdf/2505.11239v2.pdf
https://github.com/cruiseresearchgroup/massive-steps
true
true
true
none
https://paperswithcode.com/paper/diffusion-posterior-sampling-for-general
Diffusion Posterior Sampling for General Noisy Inverse Problems
2209.14687
https://arxiv.org/abs/2209.14687v4
https://arxiv.org/pdf/2209.14687v4.pdf
https://github.com/alexdenker/SteerableConditionalDiffusion
false
false
true
pytorch
https://paperswithcode.com/paper/rankclip-ranking-consistent-language-image
RankCLIP: Ranking-Consistent Language-Image Pretraining
2404.09387
https://arxiv.org/abs/2404.09387v2
https://arxiv.org/pdf/2404.09387v2.pdf
https://github.com/jam1ezhang/rankclip
true
true
true
pytorch
https://paperswithcode.com/paper/estimating-object-physical-properties-from-1
Estimating Object Physical Properties from RGB-D Vision and Depth Robot Sensors Using Deep Learning
2507.05029
https://arxiv.org/abs/2507.05029v1
https://arxiv.org/pdf/2507.05029v1.pdf
https://github.com/RavineWindteer/Depth-mass-estimator
true
true
false
pytorch
https://paperswithcode.com/paper/polynomial-description-for-the-t-orbit-spaces
Orbit spaces of Weyl groups acting on compact tori: a unified and explicit polynomial description
2203.13152
https://arxiv.org/abs/2203.13152v2
https://arxiv.org/pdf/2203.13152v2.pdf
https://github.com/tobiasmetzlaff/generalizedchebyshev
true
true
false
none
https://paperswithcode.com/paper/adiabatic-replay-for-continual-learning
Adiabatic replay for continual learning
2303.13157
https://arxiv.org/abs/2303.13157v1
https://arxiv.org/pdf/2303.13157v1.pdf
https://github.com/alexk1704/scclv2
true
true
false
tf
https://paperswithcode.com/paper/semantic-decoupled-spatial-partition-guided
Semantic-decoupled Spatial Partition Guided Point-supervised Oriented Object Detection
2506.10601
https://arxiv.org/abs/2506.10601v1
https://arxiv.org/pdf/2506.10601v1.pdf
https://github.com/antxinyuan/ssp
true
true
true
pytorch
https://paperswithcode.com/paper/cradmap-applied-distributed-volumetric
CRADMap: Applied Distributed Volumetric Mapping with 5G-Connected Multi-Robots and 4D Radar Perception
2503.00262
https://arxiv.org/abs/2503.00262v2
https://arxiv.org/pdf/2503.00262v2.pdf
https://github.com/Maaz-qureshi98/VolumetricMapping
true
false
true
none
https://paperswithcode.com/paper/hierarchically-accelerated-coverage-path
Hierarchically Accelerated Coverage Path Planning for Redundant Manipulators
2502.19591
https://arxiv.org/abs/2502.19591v1
https://arxiv.org/pdf/2502.19591v1.pdf
https://github.com/uwgraphics/arm_coverage
true
false
true
none
https://paperswithcode.com/paper/mom-linear-sequence-modeling-with-mixture-of
MoM: Linear Sequence Modeling with Mixture-of-Memories
2502.13685
https://arxiv.org/abs/2502.13685v2
https://arxiv.org/pdf/2502.13685v2.pdf
https://github.com/opensparsellms/linear-moe
true
true
true
pytorch
https://paperswithcode.com/paper/lasp-2-rethinking-sequence-parallelism-for
LASP-2: Rethinking Sequence Parallelism for Linear Attention and Its Hybrid
2502.07563
https://arxiv.org/abs/2502.07563v1
https://arxiv.org/pdf/2502.07563v1.pdf
https://github.com/opensparsellms/linear-moe
true
true
true
pytorch
https://paperswithcode.com/paper/clip-adapter-better-vision-language-models
CLIP-Adapter: Better Vision-Language Models with Feature Adapters
2110.04544
https://arxiv.org/abs/2110.04544v2
https://arxiv.org/pdf/2110.04544v2.pdf
https://github.com/gaopengcuhk/clip-adapter
true
true
true
pytorch
https://paperswithcode.com/paper/progressive-rendering-distillation-adapting
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data
2503.21694
https://arxiv.org/abs/2503.21694v1
https://arxiv.org/pdf/2503.21694v1.pdf
https://github.com/theericma/triplaneturbo
true
true
true
jax
https://paperswithcode.com/paper/non-centering-for-discrete-valued-state
Non-centering for discrete-valued state transition models: an application to ESBL-producing E. coli transmission in Malawi
2504.11836
https://arxiv.org/abs/2504.11836v2
https://arxiv.org/pdf/2504.11836v2.pdf
https://github.com/neilljn/antidote_methods
true
true
false
jax
https://paperswithcode.com/paper/differentially-private-permutation-tests
Differentially Private Permutation Tests: Applications to Kernel Methods
2310.19043
https://arxiv.org/abs/2310.19043v2
https://arxiv.org/pdf/2310.19043v2.pdf
https://github.com/antoninschrab/dckernel-paper
false
false
true
jax
https://paperswithcode.com/paper/deep-reinforcement-learning-for-controlled
Deep Reinforcement Learning for Controlled Traversing of the Attractor Landscape of Boolean Models in the Context of Cellular Reprogramming
2402.08491
https://arxiv.org/abs/2402.08491v3
https://arxiv.org/pdf/2402.08491v3.pdf
https://github.com/jakub-zarzycki2022/gattaca
false
false
true
pytorch
https://paperswithcode.com/paper/reasoning-towards-fairness-mitigating-bias-in
Reasoning Towards Fairness: Mitigating Bias in Language Models through Reasoning-Guided Fine-Tuning
2504.05632
https://arxiv.org/abs/2504.05632v2
https://arxiv.org/pdf/2504.05632v2.pdf
https://github.com/Sanchit-404/Reasoing-Towards-Fairness
true
false
false
pytorch
https://paperswithcode.com/paper/data-driven-learning-of-geometric-scattering-1
Data-Driven Learning of Geometric Scattering Networks
2010.02415
https://arxiv.org/abs/2010.02415v3
https://arxiv.org/pdf/2010.02415v3.pdf
https://github.com/KrishnaswamyLab/LearnableScattering
false
false
true
pytorch
https://paperswithcode.com/paper/relational-representation-learning-network
Relational Representation Learning Network for Cross-Spectral Image Patch Matching
2403.11751
https://arxiv.org/abs/2403.11751v3
https://arxiv.org/pdf/2403.11751v3.pdf
https://github.com/yuchuang1205/rrl-net
true
true
true
tf
https://paperswithcode.com/paper/non-hermitian-numerical-renormalization-group
Non-Hermitian Numerical Renormalization Group: Solution of the non-Hermitian Kondo model
2504.07019
https://arxiv.org/abs/2504.07019v2
https://arxiv.org/pdf/2504.07019v2.pdf
https://github.com/phillipbc/nonhermitiannrg
true
true
true
none
https://paperswithcode.com/paper/bayesian-model-averaging-in-causal
Bayesian Model Averaging in Causal Instrumental Variable Models
2504.13520
https://arxiv.org/abs/2504.13520v3
https://arxiv.org/pdf/2504.13520v3.pdf
https://github.com/gregorsteiner/givbma.jl
true
true
false
none
https://paperswithcode.com/paper/turning-trash-into-treasure-accelerating
Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling
2408.08696
https://arxiv.org/abs/2408.08696v2
https://arxiv.org/pdf/2408.08696v2.pdf
https://github.com/luowaterbi/tokenrecycling
true
true
true
pytorch
https://paperswithcode.com/paper/using-time-structure-to-estimate-causal
Using Time Structure to Estimate Causal Effects
2504.11076
https://arxiv.org/abs/2504.11076v2
https://arxiv.org/pdf/2504.11076v2.pdf
https://gitlab.com/dlr-dw/using_time_structure_to_estimate_causal_effects_code
true
true
true
none
https://paperswithcode.com/paper/a-combined-channel-approach-for-decoding
A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy through Spatial Information Integration
2412.06336
https://arxiv.org/abs/2412.06336v1
https://arxiv.org/pdf/2412.06336v1.pdf
https://github.com/Navid-Ziaei/combined-channel-iEEG-decoder
true
false
true
none
https://paperswithcode.com/paper/cfics-graph-based-classification-of-common
CFiCS: Graph-Based Classification of Common Factors and Microcounseling Skills
2503.22277
https://arxiv.org/abs/2503.22277v1
https://arxiv.org/pdf/2503.22277v1.pdf
https://github.com/smidtfab/CFiCS
true
false
false
pytorch
https://paperswithcode.com/paper/federated-semantic-learning-for-privacy
Federated Semantic Learning for Privacy-preserving Cross-domain Recommendation
2503.23026
https://arxiv.org/abs/2503.23026v1
https://arxiv.org/pdf/2503.23026v1.pdf
https://github.com/sapphire-star/ffmsr
true
true
false
pytorch
https://paperswithcode.com/paper/instantid-zero-shot-identity-preserving
InstantID: Zero-shot Identity-Preserving Generation in Seconds
2401.07519
https://arxiv.org/abs/2401.07519v2
https://arxiv.org/pdf/2401.07519v2.pdf
https://github.com/instantx-research/instantid
false
false
true
pytorch
https://paperswithcode.com/paper/moving-object-segmentation-in-point-cloud
Moving Object Segmentation in Point Cloud Data using Hidden Markov Models
2410.18638
https://arxiv.org/abs/2410.18638v1
https://arxiv.org/pdf/2410.18638v1.pdf
https://github.com/vb44/hmm-mos
true
true
true
none
https://paperswithcode.com/paper/omniesi-a-unified-framework-for-enzyme
OmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning
2506.17963
https://arxiv.org/abs/2506.17963v1
https://arxiv.org/pdf/2506.17963v1.pdf
https://github.com/hong-yu-zhang/omniesi
true
true
true
pytorch
https://paperswithcode.com/paper/how-is-llm-reasoning-distracted-by-irrelevant
How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled Benchmark
2505.18761
https://arxiv.org/abs/2505.18761v1
https://arxiv.org/pdf/2505.18761v1.pdf
https://github.com/mlyann/gsm-dc
true
true
false
pytorch
https://paperswithcode.com/paper/counterfactual-query-rewriting-to-use
Counterfactual Query Rewriting to Use Historical Relevance Feedback
2502.03891
https://arxiv.org/abs/2502.03891v1
https://arxiv.org/pdf/2502.03891v1.pdf
https://github.com/webis-de/ecir25-counterfactual-query-rewriting
true
false
false
none
https://paperswithcode.com/paper/sundial-a-family-of-highly-capable-time
Sundial: A Family of Highly Capable Time Series Foundation Models
2502.00816
https://arxiv.org/abs/2502.00816v1
https://arxiv.org/pdf/2502.00816v1.pdf
https://github.com/thuml/Sundial
false
false
true
pytorch
https://paperswithcode.com/paper/why-should-adversarial-perturbations-be
Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP
2210.10683
https://arxiv.org/abs/2210.10683v1
https://arxiv.org/pdf/2210.10683v1.pdf
https://github.com/yang-yan-yang-yan/sop
false
false
true
none
https://paperswithcode.com/paper/sop-unlock-the-power-of-social-facilitation
SeqAR: Jailbreak LLMs with Sequential Auto-Generated Characters
2407.01902
https://arxiv.org/abs/2407.01902v2
https://arxiv.org/pdf/2407.01902v2.pdf
https://github.com/yang-yan-yang-yan/sop
true
true
true
none