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

Dataset card Data Studio Files
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https://paperswithcode.com/paper/generalized-measures-of-anticipation-and
Generalized Measures of Anticipation and Responsivity in Online Language Processing
2409.10728
https://arxiv.org/abs/2409.10728v2
https://arxiv.org/pdf/2409.10728v2.pdf
https://github.com/rycolab/generalized-surprisal
true
true
true
none
https://paperswithcode.com/paper/a-simple-baseline-for-multi-object-tracking
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
2004.01888
https://arxiv.org/abs/2004.01888v6
https://arxiv.org/pdf/2004.01888v6.pdf
https://github.com/ydhcg-bobo/stcmot
false
false
true
pytorch
https://paperswithcode.com/paper/can-graph-reordering-speed-up-graph-neural
Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study
2409.11129
https://arxiv.org/abs/2409.11129v1
https://arxiv.org/pdf/2409.11129v1.pdf
https://github.com/nikolaimerkel/reordering
true
true
false
pytorch
https://paperswithcode.com/paper/stcmot-spatio-temporal-cohesion-learning-for
STCMOT: Spatio-Temporal Cohesion Learning for UAV-Based Multiple Object Tracking
2409.11234
https://arxiv.org/abs/2409.11234v1
https://arxiv.org/pdf/2409.11234v1.pdf
https://github.com/ydhcg-bobo/stcmot
true
true
false
pytorch
https://paperswithcode.com/paper/unsupervised-hybrid-framework-for-anomaly
Unsupervised Hybrid framework for ANomaly Detection (HAND) -- applied to Screening Mammogram
2409.11534
https://arxiv.org/abs/2409.11534v1
https://arxiv.org/pdf/2409.11534v1.pdf
https://github.com/zheminzhang96/hand_mammo
true
true
false
pytorch
https://paperswithcode.com/paper/feature-re-embedding-towards-foundation-model
Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
2402.17228
https://arxiv.org/abs/2402.17228v4
https://arxiv.org/pdf/2402.17228v4.pdf
https://github.com/dearcaat/rrt-mil
true
true
true
pytorch
https://paperswithcode.com/paper/self-supervised-diffusion-mri-denoising-via
Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
2501.13514
https://arxiv.org/abs/2501.13514v3
https://arxiv.org/pdf/2501.13514v3.pdf
https://github.com/fouierl/di-fusion
true
true
true
pytorch
https://paperswithcode.com/paper/revisiting-end-to-end-learning-with-slide
Revisiting End-to-End Learning with Slide-level Supervision in Computational Pathology
2506.02408
https://arxiv.org/abs/2506.02408v1
https://arxiv.org/pdf/2506.02408v1.pdf
https://github.com/dearcaat/rrt-mil
false
false
true
pytorch
https://paperswithcode.com/paper/vista3d-unravel-the-3d-darkside-of-a-single
Vista3D: Unravel the 3D Darkside of a Single Image
2409.12193
https://arxiv.org/abs/2409.12193v1
https://arxiv.org/pdf/2409.12193v1.pdf
https://github.com/florinshen/vista3d
true
true
false
none
https://paperswithcode.com/paper/volvo-discovery-challenge-at-ecml-pkdd-2024
Volvo Discovery Challenge at ECML-PKDD 2024
2409.11446
https://arxiv.org/abs/2409.11446v1
https://arxiv.org/pdf/2409.11446v1.pdf
https://github.com/mal-to/volvo-discovery-challenge-ecml-pkdd-2024
true
true
false
pytorch
https://paperswithcode.com/paper/three-dimensional-particle-in-cell
Three-Dimensional Particle-In-Cell Simulations of Two-Dimensional Bernstein-Greene-Kruskal Modes
2410.16585
https://arxiv.org/abs/2410.16585v1
https://arxiv.org/pdf/2410.16585v1.pdf
https://github.com/psc-code/psc
true
false
false
none
https://paperswithcode.com/paper/high-resolution-particle-in-cell-simulations
High-Resolution Particle-In-Cell Simulations of Two-Dimensional Bernstein-Greene-Kruskal Modes
2311.08613
https://arxiv.org/abs/2311.08613v1
https://arxiv.org/pdf/2311.08613v1.pdf
https://github.com/psc-code/psc
true
false
false
none
https://paperswithcode.com/paper/sum-of-parts-models-faithful-attributions-for
Sum-of-Parts: Faithful Attributions for Groups of Features
2310.16316
https://arxiv.org/abs/2310.16316v2
https://arxiv.org/pdf/2310.16316v2.pdf
https://github.com/debugml/sop
true
true
true
pytorch
https://paperswithcode.com/paper/quantifying-the-individual-differences-of
Quantifying the Individual Differences of Driver' Risk Perception with Just Four Interpretable Parameters
2211.10907
https://arxiv.org/abs/2211.10907v1
https://arxiv.org/pdf/2211.10907v1.pdf
https://github.com/ChenChenGith/PODAR_individual_modeling_code
true
false
true
pytorch
https://paperswithcode.com/paper/covomix-advancing-zero-shot-speech-generation
CoVoMix: Advancing Zero-Shot Speech Generation for Human-like Multi-talker Conversations
2404.06690
https://arxiv.org/abs/2404.06690v3
https://arxiv.org/pdf/2404.06690v3.pdf
https://github.com/vivian556123/neurips2024-covomix
true
true
true
pytorch
https://paperswithcode.com/paper/kernel-methods-for-the-approximation-of-the
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
2412.16588
https://arxiv.org/abs/2412.16588v1
https://arxiv.org/pdf/2412.16588v1.pdf
https://github.com/jonghyeon1998/koopman
true
true
false
none
https://paperswithcode.com/paper/less-is-more-a-simple-yet-effective-token
Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMs
2409.10994
https://arxiv.org/abs/2409.10994v3
https://arxiv.org/pdf/2409.10994v3.pdf
https://github.com/freedomintelligence/trim
true
true
true
pytorch
https://paperswithcode.com/paper/scanning-tables-for-the-layer-groups
Symmetries of all lines in monolayer crystals
2410.18750
https://arxiv.org/abs/2410.18750v2
https://arxiv.org/pdf/2410.18750v2.pdf
https://github.com/Griffin-Group/scanning-tables-layer-group-data
true
false
false
none
https://paperswithcode.com/paper/reward-modeling-with-weak-supervision-for
Reward Modeling with Weak Supervision for Language Models
2410.20869
https://arxiv.org/abs/2410.20869v1
https://arxiv.org/pdf/2410.20869v1.pdf
https://github.com/DFKI-NLP/weak-supervision-rlhf
true
false
false
none
https://paperswithcode.com/paper/conditional-variational-autoencoder-with
Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
2106.06103
https://arxiv.org/abs/2106.06103v1
https://arxiv.org/pdf/2106.06103v1.pdf
https://github.com/pwc-1/Paper-9/tree/main/1/vits
false
false
false
mindspore
https://paperswithcode.com/paper/simple-and-fast-distillation-of-diffusion
Simple and Fast Distillation of Diffusion Models
2409.19681
https://arxiv.org/abs/2409.19681v1
https://arxiv.org/pdf/2409.19681v1.pdf
https://github.com/zhyzhouu/amed-solver
false
false
true
pytorch
https://paperswithcode.com/paper/experience-and-evidence-are-the-eyes-of-an
Experience and Evidence are the eyes of an excellent summarizer! Towards Knowledge Infused Multi-modal Clinical Conversation Summarization
2309.15739
https://arxiv.org/abs/2309.15739v1
https://arxiv.org/pdf/2309.15739v1.pdf
https://github.com/nlp-rl/mm-cliconsummation
true
true
true
pytorch
https://paperswithcode.com/paper/seeding-with-differentially-private-network
Seeding with Differentially Private Network Information
2305.16590
https://arxiv.org/abs/2305.16590v4
https://arxiv.org/pdf/2305.16590v4.pdf
https://github.com/aminrahimian/dp-inf-max
true
true
false
none
https://paperswithcode.com/paper/where-s-ben-nevis-a-2d-optimisation-benchmark
Where's Ben Nevis? A 2D optimisation benchmark with 957,174 local optima based on Great Britain terrain data
2410.02422
https://arxiv.org/abs/2410.02422v1
https://arxiv.org/pdf/2410.02422v1.pdf
https://github.com/CardiacModelling/BenNevis
true
false
false
none
https://paperswithcode.com/paper/personalized-topology-informed-12-lead-ecg
Personalized Topology-Informed Localization of Standard 12-Lead ECG Electrode Placement from Incomplete Cardiac MRIs for Efficient Cardiac Digital Twins
2408.13945
https://arxiv.org/abs/2408.13945v2
https://arxiv.org/pdf/2408.13945v2.pdf
https://github.com/lileitech/12lead_ecg_electrode_localizer
true
true
false
pytorch
https://paperswithcode.com/paper/small-models-big-tasks-an-exploratory
Small Models, Big Tasks: An Exploratory Empirical Study on Small Language Models for Function Calling
2504.19277
https://arxiv.org/abs/2504.19277v1
https://arxiv.org/pdf/2504.19277v1.pdf
https://github.com/Raghav010/Small-Models-Big-Tasks
true
true
false
pytorch
https://paperswithcode.com/paper/controlled-evaluation-of-syntactic-knowledge
Controlled Evaluation of Syntactic Knowledge in Multilingual Language Models
2411.07474
https://arxiv.org/abs/2411.07474v2
https://arxiv.org/pdf/2411.07474v2.pdf
https://github.com/dariakryvosheieva/syntactic_generalization_multilingual
true
false
true
none
https://paperswithcode.com/paper/a-general-purpose-multimodal-foundation-model
A Multimodal Vision Foundation Model for Clinical Dermatology
2410.15038
https://arxiv.org/abs/2410.15038v2
https://arxiv.org/pdf/2410.15038v2.pdf
https://github.com/SiyuanYan1/PanDerm
true
false
true
pytorch
https://paperswithcode.com/paper/unraveling-cross-modality-knowledge-conflict
Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Models
2410.03659
https://arxiv.org/abs/2410.03659v2
https://arxiv.org/pdf/2410.03659v2.pdf
https://github.com/luka-group/vlm-knowledge-conflict
true
true
true
pytorch
https://paperswithcode.com/paper/stacked-conditional-generative-adversarial
Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal
1712.02478
http://arxiv.org/abs/1712.02478v1
http://arxiv.org/pdf/1712.02478v1.pdf
https://github.com/Param-Raval/shadow-sight
false
false
true
pytorch
https://paperswithcode.com/paper/federated-learning-with-label-masking
Federated Learning with Label-Masking Distillation
2409.13136
https://arxiv.org/abs/2409.13136v1
https://arxiv.org/pdf/2409.13136v1.pdf
https://github.com/wnma3mz/fedlmd
true
true
false
pytorch
https://paperswithcode.com/paper/policy-improvement-using-language-feedback
Policy Improvement using Language Feedback Models
2402.07876
https://arxiv.org/abs/2402.07876v6
https://arxiv.org/pdf/2402.07876v6.pdf
https://github.com/vzhong/language_feedback_models
true
false
false
pytorch
https://paperswithcode.com/paper/a-simple-image-segmentation-framework-via-in
A Simple Image Segmentation Framework via In-Context Examples
2410.04842
https://arxiv.org/abs/2410.04842v2
https://arxiv.org/pdf/2410.04842v2.pdf
https://github.com/aim-uofa/sine
true
true
true
pytorch
https://paperswithcode.com/paper/llava-prumerge-adaptive-token-reduction-for
LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models
2403.15388
https://arxiv.org/abs/2403.15388v5
https://arxiv.org/pdf/2403.15388v5.pdf
https://github.com/42Shawn/LLaVA-PruMerge
false
false
true
pytorch
https://paperswithcode.com/paper/swin-transformer-hierarchical-vision
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
2103.14030
https://arxiv.org/abs/2103.14030v2
https://arxiv.org/pdf/2103.14030v2.pdf
https://github.com/yangyucheng000/University/tree/main/model-3/swin
false
false
false
mindspore
https://paperswithcode.com/paper/on-the-detectability-and-parameterisation-of
On the detectability and parameterisation of binary stars through spectral energy distributions
2412.05606
https://arxiv.org/abs/2412.05606v1
https://arxiv.org/pdf/2412.05606v1.pdf
https://github.com/jikrant3/sed-analysis-tools
true
true
false
none
https://paperswithcode.com/paper/tetrahedral-diffusion-models-for-3d-shape
TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape Generation
2211.13220
https://arxiv.org/abs/2211.13220v3
https://arxiv.org/pdf/2211.13220v3.pdf
https://github.com/PeterTor/TetraDiffusion
true
false
true
pytorch
https://paperswithcode.com/paper/streamgen-connecting-populations-of-streams
StreamGen: Connecting Populations of Streams and Shells to Their Host Galaxies
2409.13810
https://arxiv.org/abs/2409.13810v1
https://arxiv.org/pdf/2409.13810v1.pdf
https://github.com/adropulic/streamgen
true
true
true
jax
https://paperswithcode.com/paper/to-glue-or-not-to-glue-classical-vs-learned
To Glue or Not to Glue? Classical vs Learned Image Matching for Mobile Mapping Cameras to Textured Semantic 3D Building Models
2505.17973
https://arxiv.org/abs/2505.17973v1
https://arxiv.org/pdf/2505.17973v1.pdf
https://github.com/simbauer/to_glue_or_not_to_glue
true
true
false
pytorch
https://paperswithcode.com/paper/simulating-the-two-dimensional-t-j-model-at
Simulating the two-dimensional $t-J$ model at finite doping with neural quantum states
2411.10430
https://arxiv.org/abs/2411.10430v2
https://arxiv.org/pdf/2411.10430v2.pdf
https://github.com/HannahLange/HFDSfortJ
true
false
true
jax
https://paperswithcode.com/paper/flame-financial-large-language-model
FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
2501.06211
https://arxiv.org/abs/2501.06211v1
https://arxiv.org/pdf/2501.06211v1.pdf
https://github.com/flame-ruc/flame
true
true
false
none
https://paperswithcode.com/paper/first-experiments-with-neural-cvc5
First Experiments with Neural cvc5
2501.09379
https://arxiv.org/abs/2501.09379v1
https://arxiv.org/pdf/2501.09379v1.pdf
https://github.com/jellepiepenbrock/mlcvc5-lpar
true
true
false
none
https://paperswithcode.com/paper/scaling-up-your-kernels-large-kernel-design
Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations
2410.08049
https://arxiv.org/abs/2410.08049v1
https://arxiv.org/pdf/2410.08049v1.pdf
https://github.com/ailab-cvc/unireplknet
true
true
true
pytorch
https://paperswithcode.com/paper/optimal-state-dynamics-estimation-for-physics
Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos
2410.07795
https://arxiv.org/abs/2410.07795v4
https://arxiv.org/pdf/2410.07795v4.pdf
https://github.com/cuongle1206/osdcap
true
true
true
pytorch
https://paperswithcode.com/paper/memsduino-an-arduino-based-mems-switch
MEMSDuino: An Arduino-Based MEMS Switch Controller
2501.03340
https://arxiv.org/abs/2501.03340v1
https://arxiv.org/pdf/2501.03340v1.pdf
https://github.com/lafefspietz/memsduino
true
true
true
none
https://paperswithcode.com/paper/query-enhanced-knowledge-intensive
Query Enhanced Knowledge-Intensive Conversation via Unsupervised Joint Modeling
2212.09588
https://arxiv.org/abs/2212.09588v2
https://arxiv.org/pdf/2212.09588v2.pdf
https://github.com/MindCode-4/code-12/tree/main/model-conversion-via
false
false
false
mindspore
https://paperswithcode.com/paper/pyramidal-flow-matching-for-efficient-video
Pyramidal Flow Matching for Efficient Video Generative Modeling
2410.05954
https://arxiv.org/abs/2410.05954v1
https://arxiv.org/pdf/2410.05954v1.pdf
https://github.com/jy0205/Pyramid-Flow
true
false
true
pytorch
https://paperswithcode.com/paper/aligning-few-step-diffusion-models-with-dense
Aligning Few-Step Diffusion Models with Dense Reward Difference Learning
2411.11727
https://arxiv.org/abs/2411.11727v1
https://arxiv.org/pdf/2411.11727v1.pdf
https://github.com/ziyizhang27/sdpo
true
true
true
pytorch
https://paperswithcode.com/paper/identifying-memorization-of-diffusion-models
Identifying Memorization of Diffusion Models through p-Laplace Analysis
2505.08246
https://arxiv.org/abs/2505.08246v1
https://arxiv.org/pdf/2505.08246v1.pdf
https://github.com/jonathanbrok/identifying-memorization-of-diffusion-models-through-p-laplace-analysis
true
true
false
pytorch
https://paperswithcode.com/paper/extreme-values-of-the-mass-distribution
Extreme values of the mass distribution associated with $d$-quasi-copulas via linear programming
2410.19339
https://arxiv.org/abs/2410.19339v2
https://arxiv.org/pdf/2410.19339v2.pdf
https://gitlab.com/mrcinv/quasicopula.jl
true
true
true
none
https://paperswithcode.com/paper/physics-informed-neural-networks-for-22
Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees
2410.18153
https://arxiv.org/abs/2410.18153v1
https://arxiv.org/pdf/2410.18153v1.pdf
https://github.com/taikimiyagawa/functionalpinn
true
true
true
pytorch
https://paperswithcode.com/paper/a-joint-learning-framework-with-feature
A Joint Learning Framework with Feature Reconstruction and Prediction for Incomplete Satellite Image Time Series in Agricultural Semantic Segmentation
2505.19159
https://arxiv.org/abs/2505.19159v1
https://arxiv.org/pdf/2505.19159v1.pdf
https://github.com/wangyuze-csu/joint_frp
true
true
false
none
https://paperswithcode.com/paper/a-survey-of-medical-vision-and-language
A Survey of Medical Vision-and-Language Applications and Their Techniques
2411.12195
https://arxiv.org/abs/2411.12195v1
https://arxiv.org/pdf/2411.12195v1.pdf
https://github.com/ytongxie/medical-vision-and-language-tasks-and-methodologies-a-survey
true
true
true
pytorch
https://paperswithcode.com/paper/local-and-global-decoding-in-text-generation
Local and Global Decoding in Text Generation
2410.10810
https://arxiv.org/abs/2410.10810v1
https://arxiv.org/pdf/2410.10810v1.pdf
https://github.com/lowlypalace/global-decoding
true
true
false
pytorch
https://paperswithcode.com/paper/bbsea-an-exploration-of-brain-body
BBSEA: An Exploration of Brain-Body Synchronization for Embodied Agents
2402.08212
https://arxiv.org/abs/2402.08212v1
https://arxiv.org/pdf/2402.08212v1.pdf
https://github.com/yangsizhe/bbsea
false
false
true
pytorch
https://paperswithcode.com/paper/multi-type-preference-learning-empowering
Multi-Type Preference Learning: Empowering Preference-Based Reinforcement Learning with Equal Preferences
2409.07268
https://arxiv.org/abs/2409.07268v2
https://arxiv.org/pdf/2409.07268v2.pdf
https://github.com/feicuilengmmbb/paper_mtpl
true
true
true
none
https://paperswithcode.com/paper/towards-better-multi-head-attention-via
Towards Better Multi-head Attention via Channel-wise Sample Permutation
2410.10914
https://arxiv.org/abs/2410.10914v1
https://arxiv.org/pdf/2410.10914v1.pdf
https://github.com/dashenzi721/csp
true
true
false
pytorch
https://paperswithcode.com/paper/automato-a-parameter-free-persistence-based
AuToMATo: An Out-Of-The-Box Persistence-Based Clustering Algorithm
2408.06958
https://arxiv.org/abs/2408.06958v2
https://arxiv.org/pdf/2408.06958v2.pdf
https://github.com/m-a-huber/AuToMATo
true
false
false
none
https://paperswithcode.com/paper/denial-of-service-poisoning-attacks-against
Denial-of-Service Poisoning Attacks against Large Language Models
2410.10760
https://arxiv.org/abs/2410.10760v1
https://arxiv.org/pdf/2410.10760v1.pdf
https://github.com/sail-sg/p-dos
true
true
true
pytorch
https://paperswithcode.com/paper/ar-tta-a-simple-method-for-real-world
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation
2309.10109
https://arxiv.org/abs/2309.10109v2
https://arxiv.org/pdf/2309.10109v2.pdf
https://github.com/dmn-sjk/ar-tta
true
true
true
none
https://paperswithcode.com/paper/v2m-visual-2-dimensional-mamba-for-image
V2M: Visual 2-Dimensional Mamba for Image Representation Learning
2410.10382
https://arxiv.org/abs/2410.10382v1
https://arxiv.org/pdf/2410.10382v1.pdf
https://github.com/wangck20/v2m
true
true
true
pytorch
https://paperswithcode.com/paper/finetuning-pretrained-transformers-into-rnns
Finetuning Pretrained Transformers into RNNs
2103.13076
https://arxiv.org/abs/2103.13076v2
https://arxiv.org/pdf/2103.13076v2.pdf
https://github.com/hazyresearch/lolcats
false
false
true
pytorch
https://paperswithcode.com/paper/the-hedgehog-the-porcupine-expressive-linear
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry
2402.04347
https://arxiv.org/abs/2402.04347v1
https://arxiv.org/pdf/2402.04347v1.pdf
https://github.com/hazyresearch/lolcats
false
false
true
pytorch
https://paperswithcode.com/paper/geometry-informed-neural-networks
Geometry-Informed Neural Networks
2402.14009
https://arxiv.org/abs/2402.14009v3
https://arxiv.org/pdf/2402.14009v3.pdf
https://github.com/ml-jku/ginns-geometry-informed-neural-networks
true
true
true
pytorch
https://paperswithcode.com/paper/implicit-multi-spectral-transformer-an
Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model
2404.07072
https://arxiv.org/abs/2404.07072v2
https://arxiv.org/pdf/2404.07072v2.pdf
https://github.com/CXH-Research/IRFormer
true
false
true
pytorch
https://paperswithcode.com/paper/a-quick-primer-on-machine-learning-in
A Quick Primer on Machine Learning in Wireless Communications
2312.17713
https://arxiv.org/abs/2312.17713v6
https://arxiv.org/pdf/2312.17713v6.pdf
https://github.com/farismismar/eesc7v86-fall22
true
true
true
tf
https://paperswithcode.com/paper/subjective-and-objective-analysis-of-indian
Subjective and Objective Analysis of Indian Social Media Video Quality
2401.02794
https://arxiv.org/abs/2401.02794v1
https://arxiv.org/pdf/2401.02794v1.pdf
https://github.com/sandeep-sm/live-sc
true
true
true
none
https://paperswithcode.com/paper/inflation-of-test-accuracy-due-to-data
Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images
2202.12267
https://arxiv.org/abs/2202.12267v2
https://arxiv.org/pdf/2202.12267v2.pdf
https://github.com/iulianemiltampu/split_properly_oct_data
true
true
false
tf
https://paperswithcode.com/paper/topa-extend-large-language-models-for-video
TOPA: Extending Large Language Models for Video Understanding via Text-Only Pre-Alignment
2405.13911
https://arxiv.org/abs/2405.13911v2
https://arxiv.org/pdf/2405.13911v2.pdf
https://github.com/dhg-wei/topa
true
true
true
pytorch
https://paperswithcode.com/paper/unsupervised-homography-estimation-on
Unsupervised Homography Estimation on Multimodal Image Pair via Alternating Optimization
2411.13036
https://arxiv.org/abs/2411.13036v1
https://arxiv.org/pdf/2411.13036v1.pdf
https://github.com/songsang7/alto
true
true
true
pytorch
https://paperswithcode.com/paper/vista-dataset-do-vision-language-models
ViSTa Dataset: Do vision-language models understand sequential tasks?
2411.13211
https://arxiv.org/abs/2411.13211v2
https://arxiv.org/pdf/2411.13211v2.pdf
https://github.com/eugleo/vista-dataset
true
true
true
pytorch
https://paperswithcode.com/paper/whales-a-multi-agent-scheduling-dataset-for
WHALES: A Multi-agent Scheduling Dataset for Enhanced Cooperation in Autonomous Driving
2411.13340
https://arxiv.org/abs/2411.13340v1
https://arxiv.org/pdf/2411.13340v1.pdf
https://github.com/chensiweithu/whales
true
true
false
pytorch
https://paperswithcode.com/paper/teaching-vlms-to-localize-specific-objects
Teaching VLMs to Localize Specific Objects from In-context Examples
2411.13317
https://arxiv.org/abs/2411.13317v1
https://arxiv.org/pdf/2411.13317v1.pdf
https://github.com/sivandoveh/iploc
true
true
false
pytorch
https://paperswithcode.com/paper/joint-vision-language-social-bias-removal-for
Joint Vision-Language Social Bias Removal for CLIP
2411.12785
https://arxiv.org/abs/2411.12785v1
https://arxiv.org/pdf/2411.12785v1.pdf
https://github.com/haoyusimon/VL_Debiasing
true
false
true
pytorch
https://paperswithcode.com/paper/fg-dfpn-flow-guided-deformable-frame
FG-DFPN: Flow Guided Deformable Frame Prediction Network
2503.11343
https://arxiv.org/abs/2503.11343v1
https://arxiv.org/pdf/2503.11343v1.pdf
https://github.com/KUIS-AI-Tekalp-Research-Group/frame-prediction
true
false
false
pytorch
https://paperswithcode.com/paper/consistency-models
Consistency Models
2303.01469
https://arxiv.org/abs/2303.01469v2
https://arxiv.org/pdf/2303.01469v2.pdf
https://github.com/cloneofsimo/consistency_models
false
false
true
pytorch
https://paperswithcode.com/paper/developing-a-top-tier-framework-in
Developing a Top-tier Framework in Naturalistic Conditions Challenge for Categorized Emotion Prediction: From Speech Foundation Models and Learning Objective to Data Augmentation and Engineering Choices
2505.22133
https://arxiv.org/abs/2505.22133v2
https://arxiv.org/pdf/2505.22133v2.pdf
https://github.com/tiantiaf0627/vox-profile-release
true
true
false
pytorch
https://paperswithcode.com/paper/gaze-guided-learning-avoiding-shortcut-bias
Gaze-Guided Learning: Avoiding Shortcut Bias in Visual Classification
2504.05583
https://arxiv.org/abs/2504.05583v1
https://arxiv.org/pdf/2504.05583v1.pdf
https://github.com/rekkles2/Gaze-CIFAR-10
true
true
true
pytorch
https://paperswithcode.com/paper/trustworthy-deep-learning-via-proper
Better Uncertainty Calibration via Proper Scores for Classification and Beyond
2203.07835
https://arxiv.org/abs/2203.07835v4
https://arxiv.org/pdf/2203.07835v4.pdf
https://github.com/MLO-lab/better_uncertainty_calibration_via_proper_scores_for_classification_and_beyond
true
false
true
pytorch
https://paperswithcode.com/paper/flipsketch-flipping-static-drawings-to-text
FlipSketch: Flipping Static Drawings to Text-Guided Sketch Animations
2411.10818
https://arxiv.org/abs/2411.10818v1
https://arxiv.org/pdf/2411.10818v1.pdf
https://github.com/hmrishavbandy/flipsketch
true
true
true
pytorch
https://paperswithcode.com/paper/intruding-with-words-towards-understanding
Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
2405.16405
https://arxiv.org/abs/2405.16405v2
https://arxiv.org/pdf/2405.16405v2.pdf
https://github.com/leirunlin/text-level-graph-attack
true
true
true
pytorch
https://paperswithcode.com/paper/a-llm-based-ranking-method-for-the-evaluation
A LLM-Based Ranking Method for the Evaluation of Automatic Counter-Narrative Generation
2406.15227
https://arxiv.org/abs/2406.15227v3
https://arxiv.org/pdf/2406.15227v3.pdf
https://github.com/hitz-zentroa/cn-eval
true
true
true
pytorch
https://paperswithcode.com/paper/adjointdeis-efficient-gradients-for-diffusion
AdjointDEIS: Efficient Gradients for Diffusion Models
2405.15020
https://arxiv.org/abs/2405.15020v3
https://arxiv.org/pdf/2405.15020v3.pdf
https://github.com/zblasingame/adjointdeis
true
true
true
pytorch
https://paperswithcode.com/paper/simulation-of-nanorobots-with-artificial
Simulation of Nanorobots with Artificial Intelligence and Reinforcement Learning for Advanced Cancer Cell Detection and Tracking
2411.02345
https://arxiv.org/abs/2411.02345v1
https://arxiv.org/pdf/2411.02345v1.pdf
https://github.com/shahab-k93/cancer-and-smart-nanorobot
true
true
false
none
https://paperswithcode.com/paper/generative-ai-aided-optimization-for-ai
Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services
2303.13052
https://arxiv.org/abs/2303.13052v3
https://arxiv.org/pdf/2303.13052v3.pdf
https://github.com/lizonghang/agod
true
true
true
pytorch
https://paperswithcode.com/paper/neural-audio-synthesis-of-musical-notes-with
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
1704.01279
http://arxiv.org/abs/1704.01279v1
http://arxiv.org/pdf/1704.01279v1.pdf
https://github.com/MindSpore-scientific/code-6/tree/main/neural-audio-synthesis-wavenet
false
false
false
mindspore
https://paperswithcode.com/paper/normalization-layer-per-example-gradients-are
Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers
2411.00999
https://arxiv.org/abs/2411.00999v1
https://arxiv.org/pdf/2411.00999v1.pdf
https://github.com/cerebrasresearch/nanogns
true
true
true
pytorch
https://paperswithcode.com/paper/interpreting-clip-with-sparse-linear-concept
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
2402.10376
https://arxiv.org/abs/2402.10376v2
https://arxiv.org/pdf/2402.10376v2.pdf
https://github.com/ai4life-group/splice
true
true
true
pytorch
https://paperswithcode.com/paper/flexchunk-enabling-100mx100m-out-of-core-spmv
FlexChunk: Enabling 100M×100M Out-of-Core SpMV (~1.8 min, ~1.7 GB RAM) with Near-Linear Scaling
null
https://www.lesswrong.com/posts/zpRhsdDkWygTDScxb/flexchunk-enabling-100m-100m-out-of-core-spmv-1-8-min-1-7-gb
https://github.com/DanielSwift1992/FlexChunk/blob/main/docs/lesswrong.com-FlexChunk.pdf
https://github.com/DanielSwift1992/FlexChunk
false
false
false
none
https://paperswithcode.com/paper/gateformer-advancing-multivariate-time-series
Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations
2505.00307
https://arxiv.org/abs/2505.00307v2
https://arxiv.org/pdf/2505.00307v2.pdf
https://github.com/nyuolab/gateformer
true
true
true
pytorch
https://paperswithcode.com/paper/c-pmi-conditional-pointwise-mutual
C-PMI: Conditional Pointwise Mutual Information for Turn-level Dialogue Evaluation
2306.15245
https://arxiv.org/abs/2306.15245v3
https://arxiv.org/pdf/2306.15245v3.pdf
https://github.com/renll/c-pmi
true
true
true
none
https://paperswithcode.com/paper/tip-of-the-tongue-query-elicitation-for
Tip of the Tongue Query Elicitation for Simulated Evaluation
2502.17776
https://arxiv.org/abs/2502.17776v1
https://arxiv.org/pdf/2502.17776v1.pdf
https://github.com/kimdanny/human-tot-query-elicitation-mturk
true
false
false
none
https://paperswithcode.com/paper/luminance-attentive-networks-for-hdr-image
Luminance Attentive Networks for HDR Image and Panorama Reconstruction
2109.06688
https://arxiv.org/abs/2109.06688v1
https://arxiv.org/pdf/2109.06688v1.pdf
https://github.com/MindSpore-scientific/code-13/tree/main/Luminance-Guided-Chrominance-Enhancement-for-HEVC-Intra-Coding
false
false
false
mindspore
https://paperswithcode.com/paper/in-context-learning-with-hypothesis-class
In-Context Learning with Hypothesis-Class Guidance
2502.19787
https://arxiv.org/abs/2502.19787v1
https://arxiv.org/pdf/2502.19787v1.pdf
https://github.com/uw-madison-lee-lab/icl-hcg
true
true
false
none
https://paperswithcode.com/paper/steerable-conditional-diffusion-for-out-of
Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Medical Image Reconstruction
2308.14409
https://arxiv.org/abs/2308.14409v3
https://arxiv.org/pdf/2308.14409v3.pdf
https://github.com/alexdenker/SteerableConditionalDiffusion
true
true
true
pytorch
https://paperswithcode.com/paper/deft-efficient-finetuning-of-conditional
DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised $h$-transform
2406.01781
https://arxiv.org/abs/2406.01781v5
https://arxiv.org/pdf/2406.01781v5.pdf
https://github.com/alexdenker/deft
true
true
true
pytorch
https://paperswithcode.com/paper/strategic-learning-and-trading-in-broker
Strategic Learning and Trading in Broker-Mediated Markets
2412.20847
https://arxiv.org/abs/2412.20847v1
https://arxiv.org/pdf/2412.20847v1.pdf
https://github.com/muhammadalifaqsha/broker_informed_noise_filtering_game
true
false
false
none
https://paperswithcode.com/paper/the-bigger-the-better-accurate-molecular
The Bigger the Better? Accurate Molecular Potential Energy Surfaces from Minimalist Neural Networks
2411.18121
https://arxiv.org/abs/2411.18121v1
https://arxiv.org/pdf/2411.18121v1.pdf
https://github.com/MMunibas/KerNN
true
false
true
pytorch
https://paperswithcode.com/paper/model-x-ray-detect-backdoored-models-via
Model X-ray:Detecting Backdoored Models via Decision Boundary
2402.17465
https://arxiv.org/abs/2402.17465v2
https://arxiv.org/pdf/2402.17465v2.pdf
https://github.com/SuYanghao/Model_X-ray
true
false
true
pytorch
https://paperswithcode.com/paper/pruning-in-the-face-of-adversaries
Pruning in the Face of Adversaries
2108.08560
https://arxiv.org/abs/2108.08560v1
https://arxiv.org/pdf/2108.08560v1.pdf
https://github.com/FlorianMerkle/network-pruning-and-robustness
false
false
true
tf