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

Dataset card Data Studio Files
xet
Community
1
paper_url
stringlengths
36
81
paper_title
stringlengths
1
242
⌀
paper_arxiv_id
stringlengths
9
16
⌀
paper_url_abs
stringlengths
18
314
paper_url_pdf
stringlengths
21
935
⌀
repo_url
stringlengths
26
200
is_official
bool
2 classes
mentioned_in_paper
bool
2 classes
mentioned_in_github
bool
2 classes
framework
stringclasses
9 values
https://paperswithcode.com/paper/an-effective-theory-of-collective-deep
An effective theory of collective deep learning
2310.12802
https://arxiv.org/abs/2310.12802v2
https://arxiv.org/pdf/2310.12802v2.pdf
https://github.com/mystic-blue/collective-learning
true
true
true
none
https://paperswithcode.com/paper/bridging-topic-domain-and-language-shifts-an
How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field Study
2309.08316
https://arxiv.org/abs/2309.08316v3
https://arxiv.org/pdf/2309.08316v3.pdf
https://github.com/ukplab/acl2024-ood-compuational-argumentation
true
true
true
pytorch
https://paperswithcode.com/paper/flux-that-plays-music
FLUX that Plays Music
2409.00587
https://arxiv.org/abs/2409.00587v2
https://arxiv.org/pdf/2409.00587v2.pdf
https://github.com/feizc/fluxmusic
true
true
true
pytorch
https://paperswithcode.com/paper/ladder-a-model-agnostic-framework-boosting
Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level
2406.15741
https://arxiv.org/abs/2406.15741v3
https://arxiv.org/pdf/2406.15741v3.pdf
https://github.com/fzp0424/ladder
true
true
true
pytorch
https://paperswithcode.com/paper/fast-timing-conditioned-latent-audio
Fast Timing-Conditioned Latent Audio Diffusion
2402.04825
https://arxiv.org/abs/2402.04825v3
https://arxiv.org/pdf/2402.04825v3.pdf
https://github.com/stability-ai/stable-audio-metrics
true
true
false
pytorch
https://paperswithcode.com/paper/mathematical-modeling-of-epidemic-diseases-a
Mathematical Modeling of Epidemic Diseases; A Case Study of the COVID-19 Coronavirus
2003.11371
https://arxiv.org/abs/2003.11371v3
https://arxiv.org/pdf/2003.11371v3.pdf
https://github.com/rsameni/EpidemicModeling
true
true
true
none
https://paperswithcode.com/paper/energy-transformer
Energy Transformer
2302.07253
https://arxiv.org/abs/2302.07253v2
https://arxiv.org/pdf/2302.07253v2.pdf
https://github.com/bhoov/energy-transformer-jax
true
true
true
jax
https://paperswithcode.com/paper/symilo-a-symmetry-aware-learning-framework
SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
2409.19678
https://arxiv.org/abs/2409.19678v3
https://arxiv.org/pdf/2409.19678v3.pdf
https://github.com/netsysopt/symilo
true
true
true
pytorch
https://paperswithcode.com/paper/time-waits-for-no-one-analysis-and-challenges
Time Waits for No One! Analysis and Challenges of Temporal Misalignment
2111.07408
https://arxiv.org/abs/2111.07408v2
https://arxiv.org/pdf/2111.07408v2.pdf
https://github.com/KaiNylund/lm-weights-encode-time
false
false
true
pytorch
https://paperswithcode.com/paper/time-is-encoded-in-the-weights-of-finetuned
Time is Encoded in the Weights of Finetuned Language Models
2312.13401
https://arxiv.org/abs/2312.13401v2
https://arxiv.org/pdf/2312.13401v2.pdf
https://github.com/KaiNylund/lm-weights-encode-time
true
true
true
pytorch
https://paperswithcode.com/paper/dimensionality-driven-learning-with-noisy
Dimensionality-Driven Learning with Noisy Labels
1806.02612
http://arxiv.org/abs/1806.02612v2
http://arxiv.org/pdf/1806.02612v2.pdf
https://github.com/MindSpore-scientific-2/code-3/tree/main/Three-Dimensional-Lip-Motion-Network-for-Text-Independent-Speaker-Recognition-master
false
false
false
mindspore
https://paperswithcode.com/paper/se-3-diffusion-model-with-application-to
SE(3) diffusion model with application to protein backbone generation
2302.02277
https://arxiv.org/abs/2302.02277v3
https://arxiv.org/pdf/2302.02277v3.pdf
https://github.com/instadeepai/framedipt
false
false
true
pytorch
https://paperswithcode.com/paper/open3dsg-open-vocabulary-3d-scene-graphs-from
Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships
2402.12259
https://arxiv.org/abs/2402.12259v2
https://arxiv.org/pdf/2402.12259v2.pdf
https://github.com/boschresearch/Open3DSG
true
false
true
pytorch
https://paperswithcode.com/paper/less-is-more-toward-zero-shot-local-scene
Less is More: Toward Zero-Shot Local Scene Graph Generation via Foundation Models
2310.01356
https://arxiv.org/abs/2310.01356v1
https://arxiv.org/pdf/2310.01356v1.pdf
https://github.com/bowen-upenn/Multi-Agent-VQA
false
false
true
pytorch
https://paperswithcode.com/paper/an-accessible-toolkit-for-360-vr-studies
An Accessible Toolkit for 360 VR Studies
2304.03652
https://arxiv.org/abs/2304.03652v3
https://arxiv.org/pdf/2304.03652v3.pdf
https://github.com/corriedotdev/vr-360-player
true
true
true
none
https://paperswithcode.com/paper/robust-training-of-federated-models-with
Robust Training of Federated Models with Extremely Label Deficiency
2402.14430
https://arxiv.org/abs/2402.14430v1
https://arxiv.org/pdf/2402.14430v1.pdf
https://github.com/tmlr-group/twin-sight
true
true
false
pytorch
https://paperswithcode.com/paper/zero-shot-reinforcement-learning-via-function
Zero-Shot Reinforcement Learning via Function Encoders
2401.17173
https://arxiv.org/abs/2401.17173v2
https://arxiv.org/pdf/2401.17173v2.pdf
https://github.com/anonymousresearcher5642/functionencoderrl
true
true
false
pytorch
https://paperswithcode.com/paper/r-tuning-teaching-large-language-models-to
R-Tuning: Instructing Large Language Models to Say `I Don't Know'
2311.09677
https://arxiv.org/abs/2311.09677v3
https://arxiv.org/pdf/2311.09677v3.pdf
https://github.com/shizhediao/r-tuning
true
true
true
pytorch
https://paperswithcode.com/paper/compositional-few-shot-class-incremental
Compositional Few-Shot Class-Incremental Learning
2405.17022
https://arxiv.org/abs/2405.17022v1
https://arxiv.org/pdf/2405.17022v1.pdf
https://github.com/zoilsen/comp-fscil
true
true
false
pytorch
https://paperswithcode.com/paper/deepgleason-a-system-for-automated-gleason
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks
2403.16678
https://arxiv.org/abs/2403.16678v1
https://arxiv.org/pdf/2403.16678v1.pdf
https://github.com/frankkramer-lab/deepgleason
true
true
false
tf
https://paperswithcode.com/paper/big-bird-transformers-for-longer-sequences
Big Bird: Transformers for Longer Sequences
2007.14062
https://arxiv.org/abs/2007.14062v2
https://arxiv.org/pdf/2007.14062v2.pdf
https://github.com/mim-solutions/roberta_for_longer_texts
false
false
true
pytorch
https://paperswithcode.com/paper/crossing-linguistic-horizons-finetuning-and
Crossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models
2403.02715
https://arxiv.org/abs/2403.02715v2
https://arxiv.org/pdf/2403.02715v2.pdf
https://github.com/stair-lab/villm-eval
true
true
false
pytorch
https://paperswithcode.com/paper/usd-unsupervised-soft-contrastive-learning
USD: Unsupervised Soft Contrastive Learning for Fault Detection in Multivariate Time Series
2405.16258
https://arxiv.org/abs/2405.16258v1
https://arxiv.org/pdf/2405.16258v1.pdf
https://github.com/zangzelin/code_usd
true
true
false
pytorch
https://paperswithcode.com/paper/collaborative-distillation-meta-learning-for
DevFormer: A Symmetric Transformer for Context-Aware Device Placement
2205.13225
https://arxiv.org/abs/2205.13225v3
https://arxiv.org/pdf/2205.13225v3.pdf
https://github.com/kaist-silab/symmetric_replay
false
false
true
pytorch
https://paperswithcode.com/paper/off-policy-evaluation-of-slate-bandit
Off-Policy Evaluation of Slate Bandit Policies via Optimizing Abstraction
2402.02171
https://arxiv.org/abs/2402.02171v2
https://arxiv.org/pdf/2402.02171v2.pdf
https://github.com/aiueola/webconf2024-slate-ope-via-abstraction
true
true
false
pytorch
https://paperswithcode.com/paper/geoguide-geometric-guidance-of-diffusion
GeoGuide: Geometric guidance of diffusion models
2407.12889
https://arxiv.org/abs/2407.12889v1
https://arxiv.org/pdf/2407.12889v1.pdf
https://github.com/mateuszpoleski/geoguide
true
false
true
pytorch
https://paperswithcode.com/paper/revisiting-confidence-estimation-towards
Revisiting Confidence Estimation: Towards Reliable Failure Prediction
2403.02886
https://arxiv.org/abs/2403.02886v1
https://arxiv.org/pdf/2403.02886v1.pdf
https://github.com/impression2805/fmfp
true
true
false
pytorch
https://paperswithcode.com/paper/micm-rethinking-unsupervised-pretraining-for
MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
2408.13385
https://arxiv.org/abs/2408.13385v1
https://arxiv.org/pdf/2408.13385v1.pdf
https://github.com/icgy96/micm
true
true
true
pytorch
https://paperswithcode.com/paper/qrisp-a-framework-for-compilable-high-level
Qrisp: A Framework for Compilable High-Level Programming of Gate-Based Quantum Computers
2406.14792
https://arxiv.org/abs/2406.14792v1
https://arxiv.org/pdf/2406.14792v1.pdf
https://github.com/eclipse-qrisp/qrisp
true
true
true
jax
https://paperswithcode.com/paper/gsina-improving-subgraph-extraction-for-graph
GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention
2402.07191
https://arxiv.org/abs/2402.07191v1
https://arxiv.org/pdf/2402.07191v1.pdf
https://github.com/dingfangyu/gsina
true
true
false
pytorch
https://paperswithcode.com/paper/asking-multimodal-clarifying-questions-in
Asking Multimodal Clarifying Questions in Mixed-Initiative Conversational Search
2402.07742
https://arxiv.org/abs/2402.07742v1
https://arxiv.org/pdf/2402.07742v1.pdf
https://github.com/yfyuan01/mqc
true
true
false
pytorch
https://paperswithcode.com/paper/laplace-hdc-understanding-the-geometry-of
Laplace-HDC: Understanding the geometry of binary hyperdimensional computing
2404.10759
https://arxiv.org/abs/2404.10759v2
https://arxiv.org/pdf/2404.10759v2.pdf
https://github.com/hdstat/laplace-hdc
true
true
false
pytorch
https://paperswithcode.com/paper/erase-then-rectify-a-training-free-parameter
Erase then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning
2409.16684
https://arxiv.org/abs/2409.16684v2
https://arxiv.org/pdf/2409.16684v2.pdf
https://github.com/allminerlab/etr
true
true
true
pytorch
https://paperswithcode.com/paper/treelearn-a-comprehensive-deep-learning
TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds
2309.08471
https://arxiv.org/abs/2309.08471v3
https://arxiv.org/pdf/2309.08471v3.pdf
https://github.com/ecker-lab/treelearn
true
true
true
pytorch
https://paperswithcode.com/paper/galapagos-automated-n-version-programming
Galapagos: Automated N-Version Programming with LLMs
2408.09536
https://arxiv.org/abs/2408.09536v2
https://arxiv.org/pdf/2408.09536v2.pdf
https://github.com/ASSERT-KTH/Galapagos
true
true
true
none
https://paperswithcode.com/paper/on-the-multi-turn-instruction-following-for
On the Multi-turn Instruction Following for Conversational Web Agents
2402.15057
https://arxiv.org/abs/2402.15057v1
https://arxiv.org/pdf/2402.15057v1.pdf
https://github.com/magicgh/self-map
true
true
true
pytorch
https://paperswithcode.com/paper/from-uncertainty-to-precision-enhancing
From Uncertainty to Precision: Enhancing Binary Classifier Performance through Calibration
2402.07790
https://arxiv.org/abs/2402.07790v1
https://arxiv.org/pdf/2402.07790v1.pdf
https://github.com/fer-agathe/calibration_binary_classifier
true
true
true
none
https://paperswithcode.com/paper/an-image-is-worth-16x16-words-transformers-1
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
2010.11929
https://arxiv.org/abs/2010.11929v2
https://arxiv.org/pdf/2010.11929v2.pdf
https://github.com/tintn/vision-transformer-from-scratch
false
false
true
pytorch
https://paperswithcode.com/paper/hfmf-hierarchical-fusion-meets-multi-stream
HFMF: Hierarchical Fusion Meets Multi-Stream Models for Deepfake Detection
2501.05631
https://arxiv.org/abs/2501.05631v1
https://arxiv.org/pdf/2501.05631v1.pdf
https://github.com/taco-group/hfmf
true
true
false
pytorch
https://paperswithcode.com/paper/parallel-friendly-spatio-temporal-graph
Parallel-friendly Spatio-Temporal Graph Learning for Photovoltaic Degradation Analysis at Scale
2402.08470
https://arxiv.org/abs/2402.08470v1
https://arxiv.org/pdf/2402.08470v1.pdf
https://github.com/yangxin666/st-gtrend
true
true
false
pytorch
https://paperswithcode.com/paper/fleurs-few-shot-learning-evaluation-of
FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech
2205.12446
https://arxiv.org/abs/2205.12446v1
https://arxiv.org/pdf/2205.12446v1.pdf
https://github.com/samsunglabs/myqasr
false
false
true
pytorch
https://paperswithcode.com/paper/poisonedrag-knowledge-poisoning-attacks-to
PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models
2402.07867
https://arxiv.org/abs/2402.07867v3
https://arxiv.org/pdf/2402.07867v3.pdf
https://github.com/sleeepeer/poisonedrag
true
true
true
pytorch
https://paperswithcode.com/paper/accelerating-matrix-factorization-by-dynamic
Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation
2404.04265
https://arxiv.org/abs/2404.04265v1
https://arxiv.org/pdf/2404.04265v1.pdf
https://github.com/git-smsun/dp-mf
true
true
false
none
https://paperswithcode.com/paper/convolutional-deep-kernel-machines
Convolutional Deep Kernel Machines
2309.09814
https://arxiv.org/abs/2309.09814v3
https://arxiv.org/pdf/2309.09814v3.pdf
https://github.com/edwardmilsom/convdkmpaper
true
true
true
pytorch
https://paperswithcode.com/paper/neural-sph-improved-neural-modeling-of
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
2402.06275
https://arxiv.org/abs/2402.06275v2
https://arxiv.org/pdf/2402.06275v2.pdf
https://github.com/tumaer/lagrangebench
false
false
true
jax
https://paperswithcode.com/paper/learning-high-dimensional-mckean-vlasov
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence
2204.11924
https://arxiv.org/abs/2204.11924v3
https://arxiv.org/pdf/2204.11924v3.pdf
https://github.com/frankhan91/deepmvbsde
true
true
true
tf
https://paperswithcode.com/paper/sparsegnv-generating-novel-views-of-indoor
SparseGNV: Generating Novel Views of Indoor Scenes with Sparse Input Views
2305.07024
https://arxiv.org/abs/2305.07024v1
https://arxiv.org/pdf/2305.07024v1.pdf
https://github.com/xt4d/sparsegnv
true
true
true
pytorch
https://paperswithcode.com/paper/diffusional-exchange-versus-microscopic
Diffusion MRI with double diffusion encoding and variable mixing times disentangles water exchange from intrinsic kurtosis
2306.03661
https://arxiv.org/abs/2306.03661v4
https://arxiv.org/pdf/2306.03661v4.pdf
https://github.com/arthur-chakwizira/cti-mge
true
true
true
none
https://paperswithcode.com/paper/interfacial-effects-determine-nonequilibrium
Interfacial Effects Determine Nonequilibrium Phase Behaviors in Chemically Driven Fluids
2505.16824
https://arxiv.org/abs/2505.16824v1
https://arxiv.org/pdf/2505.16824v1.pdf
https://github.com/wmjac/chem-driven-lattice-fluid
true
true
false
none
https://paperswithcode.com/paper/minimizing-chebyshev-prototype-risk-magically
Minimizing Chebyshev Prototype Risk Magically Mitigates the Perils of Overfitting
2404.07083
https://arxiv.org/abs/2404.07083v2
https://arxiv.org/pdf/2404.07083v2.pdf
https://github.com/deano1718/regularization_excpr
true
true
false
pytorch
https://paperswithcode.com/paper/tree-of-problems-improving-structured-problem
Tree of Problems: Improving structured problem solving with compositionality
2410.06634
https://arxiv.org/abs/2410.06634v1
https://arxiv.org/pdf/2410.06634v1.pdf
https://github.com/masoudhashemi/AWMS
false
false
false
none
https://paperswithcode.com/paper/libfork-portable-continuation-stealing-with
Libfork: portable continuation-stealing with stackless coroutines
2402.18480
https://arxiv.org/abs/2402.18480v1
https://arxiv.org/pdf/2402.18480v1.pdf
https://github.com/conorwilliams/libfork
true
true
true
none
https://paperswithcode.com/paper/representation-learning-in-multiplex-graphs
Representation learning in multiplex graphs: Where and how to fuse information?
2402.17906
https://arxiv.org/abs/2402.17906v1
https://arxiv.org/pdf/2402.17906v1.pdf
https://github.com/graphml-lab-pwr/multiplex-fusion
true
true
true
pytorch
https://paperswithcode.com/paper/hybrid-level-instruction-injection-for-video
Hybrid-Level Instruction Injection for Video Token Compression in Multi-modal Large Language Models
2503.16036
https://arxiv.org/abs/2503.16036v1
https://arxiv.org/pdf/2503.16036v1.pdf
https://github.com/lntzm/hicom
true
true
true
pytorch
https://paperswithcode.com/paper/comorbid-anxiety-symptoms-predict-lower-odds
Comorbid anxiety predicts lower odds of depression improvement during smartphone-delivered psychotherapy
2409.11183
https://arxiv.org/abs/2409.11183v2
https://arxiv.org/pdf/2409.11183v2.pdf
https://github.com/morganbdt/brighten-mdd-outcome-predict
true
true
false
none
https://paperswithcode.com/paper/transformer-based-rgb-t-tracking-with-channel
Transformer-based RGB-T Tracking with Channel and Spatial Feature Fusion
2405.03177
https://arxiv.org/abs/2405.03177v2
https://arxiv.org/pdf/2405.03177v2.pdf
https://github.com/liyunfenglyf/cstnet
true
true
true
pytorch
https://paperswithcode.com/paper/shapematcher-self-supervised-joint-shape
ShapeMatcher: Self-Supervised Joint Shape Canonicalization Segmentation Retrieval and Deformation
null
http://openaccess.thecvf.com//content/CVPR2024/html/Di_ShapeMatcher_Self-Supervised_Joint_Shape_Canonicalization_Segmentation_Retrieval_and_Deformation_CVPR_2024_paper.html
http://openaccess.thecvf.com//content/CVPR2024/papers/Di_ShapeMatcher_Self-Supervised_Joint_Shape_Canonicalization_Segmentation_Retrieval_and_Deformation_CVPR_2024_paper.pdf
https://github.com/det1999/shapemaker
true
true
false
pytorch
https://paperswithcode.com/paper/promise-prompt-driven-3d-medical-image
Promise:Prompt-driven 3D Medical Image Segmentation Using Pretrained Image Foundation Models
2310.19721
https://arxiv.org/abs/2310.19721v3
https://arxiv.org/pdf/2310.19721v3.pdf
https://github.com/medicl-vu/promise
true
true
true
pytorch
https://paperswithcode.com/paper/task-oriented-multi-user-semantic
Task-Oriented Multi-User Semantic Communications for VQA Task
2108.07357
https://arxiv.org/abs/2108.07357v3
https://arxiv.org/pdf/2108.07357v3.pdf
https://github.com/dimlight13/MU_SC_for_VQA
false
false
false
tf
https://paperswithcode.com/paper/towards-fair-and-efficient-learning-based
Towards Fair and Efficient Learning-based Congestion Control
2403.01798
https://arxiv.org/abs/2403.01798v1
https://arxiv.org/pdf/2403.01798v1.pdf
https://github.com/hkust-sing/astraea
true
true
false
none
https://paperswithcode.com/paper/badnets-identifying-vulnerabilities-in-the
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
1708.06733
http://arxiv.org/abs/1708.06733v2
http://arxiv.org/pdf/1708.06733v2.pdf
https://github.com/xandery-geek/BackdoorAttacks
false
false
true
pytorch
https://paperswithcode.com/paper/large-scale-biometry-with-interpretable
Large-scale biometry with interpretable neural network regression on UK Biobank body MRI
2002.06862
https://arxiv.org/abs/2002.06862v3
https://arxiv.org/pdf/2002.06862v3.pdf
https://github.com/tarolangner/mri-biometry
true
true
true
pytorch
https://paperswithcode.com/paper/areal-a-large-scale-asynchronous
AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning
2505.24298
https://arxiv.org/abs/2505.24298v2
https://arxiv.org/pdf/2505.24298v2.pdf
https://github.com/inclusionai/areal
true
true
true
pytorch
https://paperswithcode.com/paper/large-scale-inference-of-liver-fat-with
Large-scale inference of liver fat with neural networks on UK Biobank body MRI
2006.16777
https://arxiv.org/abs/2006.16777v1
https://arxiv.org/pdf/2006.16777v1.pdf
https://github.com/tarolangner/mri-biometry
true
true
true
pytorch
https://paperswithcode.com/paper/fast-graph-cut-based-optimization-for
Fast Graph-Cut Based Optimization for Practical Dense Deformable Registration of Volume Images
1810.08427
http://arxiv.org/abs/1810.08427v1
http://arxiv.org/pdf/1810.08427v1.pdf
https://github.com/tarolangner/mri-biometry
false
false
true
pytorch
https://paperswithcode.com/paper/verified-low-level-programming-embedded-in-f
Verified Low-Level Programming Embedded in F*
1703.00053
http://arxiv.org/abs/1703.00053v5
http://arxiv.org/pdf/1703.00053v5.pdf
https://github.com/FStarLang/kremlin
true
true
true
none
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/tarolangner/mri-biometry
false
false
true
pytorch
https://paperswithcode.com/paper/a-new-backdoor-attack-in-cnns-by-training-set
A new Backdoor Attack in CNNs by training set corruption without label poisoning
1902.11237
http://arxiv.org/abs/1902.11237v1
http://arxiv.org/pdf/1902.11237v1.pdf
https://github.com/xandery-geek/BackdoorAttacks
false
false
true
pytorch
https://paperswithcode.com/paper/performance-of-confidential-computing-gpus
Performance of Confidential Computing GPUs
2505.16501
https://arxiv.org/abs/2505.16501v1
https://arxiv.org/pdf/2505.16501v1.pdf
https://github.com/antonio-mi/sincere
true
true
false
pytorch
https://paperswithcode.com/paper/fiba-frequency-injection-based-backdoor
FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis
2112.01148
https://arxiv.org/abs/2112.01148v2
https://arxiv.org/pdf/2112.01148v2.pdf
https://github.com/xandery-geek/BackdoorAttacks
false
false
true
pytorch
https://paperswithcode.com/paper/absence-of-breakdown-of-ferrodark-solitons
Absence of the breakdown of ferrodark solitons exhibiting a snake instability
2402.05351
https://arxiv.org/abs/2402.05351v2
https://arxiv.org/pdf/2402.05351v2.pdf
https://github.com/Xiaoquanyu/resaerch-group-on-quantum-liquid
false
false
true
none
https://paperswithcode.com/paper/pptc-r-benchmark-towards-evaluating-the
PPTC-R benchmark: Towards Evaluating the Robustness of Large Language Models for PowerPoint Task Completion
2403.03788
https://arxiv.org/abs/2403.03788v1
https://arxiv.org/pdf/2403.03788v1.pdf
https://github.com/zekaigalaxy/pptcr
true
true
false
none
https://paperswithcode.com/paper/xxmd-benchmarking-neural-force-fields-using
Beyond MD17: the reactive xxMD dataset
2308.11155
https://arxiv.org/abs/2308.11155v3
https://arxiv.org/pdf/2308.11155v3.pdf
https://github.com/zpengmei/xxmd
true
true
false
pytorch
https://paperswithcode.com/paper/accelerating-the-super-resolution
Accelerating the Super-Resolution Convolutional Neural Network
1608.00367
http://arxiv.org/abs/1608.00367v1
http://arxiv.org/pdf/1608.00367v1.pdf
https://github.com/NicoCeresa/FSRCNN-2016
false
false
true
pytorch
https://paperswithcode.com/paper/the-hidden-attention-of-mamba-models
The Hidden Attention of Mamba Models
2403.01590
https://arxiv.org/abs/2403.01590v2
https://arxiv.org/pdf/2403.01590v2.pdf
https://github.com/ameenali/hiddenmambaattn
true
true
true
pytorch
https://paperswithcode.com/paper/llmcrit-teaching-large-language-models-to-use
LLMCRIT: Teaching Large Language Models to Use Criteria
2403.01069
https://arxiv.org/abs/2403.01069v2
https://arxiv.org/pdf/2403.01069v2.pdf
https://github.com/yyy-apple/llmcrit
true
true
true
none
https://paperswithcode.com/paper/mobileclip-fast-image-text-models-through
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
2311.17049
https://arxiv.org/abs/2311.17049v2
https://arxiv.org/pdf/2311.17049v2.pdf
https://github.com/apple/ml-mobileclip
true
true
true
pytorch
https://paperswithcode.com/paper/pointnet-deep-learning-on-point-sets-for-3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
1612.00593
http://arxiv.org/abs/1612.00593v2
http://arxiv.org/pdf/1612.00593v2.pdf
https://github.com/ali-stanford/pointnetcfd
false
false
true
tf
https://paperswithcode.com/paper/drattack-prompt-decomposition-and
DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers
2402.16914
https://arxiv.org/abs/2402.16914v3
https://arxiv.org/pdf/2402.16914v3.pdf
https://github.com/xirui-li/drattack
true
true
true
none
https://paperswithcode.com/paper/chemner-fine-grained-chemistry-named-entity
ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-Guided Distant Supervision
null
https://aclanthology.org/2021.emnlp-main.424
https://aclanthology.org/2021.emnlp-main.424.pdf
https://github.com/xuanwang91/chemner
true
true
false
none
https://paperswithcode.com/paper/neurogauss4d-pci-4d-neural-fields-and
NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation
2405.14241
https://arxiv.org/abs/2405.14241v1
https://arxiv.org/pdf/2405.14241v1.pdf
https://github.com/jiangchaokang/neurogauss4d-pci
true
true
false
pytorch
https://paperswithcode.com/paper/effcient-projection-onto-the-nonconvex-ell-p
Towards An Efficient Approach for the Nonconvex $\ell_p$ Ball Projection: Algorithm and Analysis
2101.01350
https://arxiv.org/abs/2101.01350v6
https://arxiv.org/pdf/2101.01350v6.pdf
https://github.com/won-j/lpballprojection
false
false
true
none
https://paperswithcode.com/paper/shapemaker-self-supervised-joint-shape
ShapeMatcher: Self-Supervised Joint Shape Canonicalization, Segmentation, Retrieval and Deformation
2311.11106
https://arxiv.org/abs/2311.11106v2
https://arxiv.org/pdf/2311.11106v2.pdf
https://github.com/det1999/shapemaker
true
true
false
pytorch
https://paperswithcode.com/paper/cdlt-a-dataset-with-concept-drift-and-long
Concept Drift and Long-Tailed Distribution in Fine-Grained Visual Categorization: Benchmark and Method
2306.02346
https://arxiv.org/abs/2306.02346v2
https://arxiv.org/pdf/2306.02346v2.pdf
https://github.com/sye-hub/cdlt
true
true
true
none
https://paperswithcode.com/paper/preconditioning-techniques-for-generalized
Preconditioning techniques for generalized Sylvester matrix equations
2307.07884
https://arxiv.org/abs/2307.07884v2
https://arxiv.org/pdf/2307.07884v2.pdf
https://github.com/yannisvoet/sylvester
true
true
false
none
https://paperswithcode.com/paper/investigating-annotator-bias-in-large
Investigating Annotator Bias in Large Language Models for Hate Speech Detection
2406.11109
https://arxiv.org/abs/2406.11109v5
https://arxiv.org/pdf/2406.11109v5.pdf
https://github.com/MindCode-4/code-12/tree/main/Investigating
false
false
false
mindspore
https://paperswithcode.com/paper/d4d-an-rgbd-diffusion-model-to-boost
D4D: An RGBD diffusion model to boost monocular depth estimation
2403.07516
https://arxiv.org/abs/2403.07516v1
https://arxiv.org/pdf/2403.07516v1.pdf
https://github.com/lorenzopapa5/diffusion4d
true
true
false
none
https://paperswithcode.com/paper/dynamic-u-net-adaptively-calibrate-features
Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ Segmentation
2403.07303
https://arxiv.org/abs/2403.07303v1
https://arxiv.org/pdf/2403.07303v1.pdf
https://github.com/sotiraslab/dynamicunet
true
true
false
pytorch
https://paperswithcode.com/paper/frequency-aware-deepfake-detection-improving
Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learning
2403.07240
https://arxiv.org/abs/2403.07240v1
https://arxiv.org/pdf/2403.07240v1.pdf
https://github.com/chuangchuangtan/freqnet-deepfakedetection
true
true
true
pytorch
https://paperswithcode.com/paper/human-emotion-knowledge-representation
Language-Specific Representation of Emotion-Concept Knowledge Causally Supports Emotion Inference
2302.09582
https://arxiv.org/abs/2302.09582v5
https://arxiv.org/pdf/2302.09582v5.pdf
https://github.com/thunlp/model_emotion
true
true
true
pytorch
https://paperswithcode.com/paper/urban-radiance-field-representation-with
Urban Radiance Field Representation with Deformable Neural Mesh Primitives
2307.10776
https://arxiv.org/abs/2307.10776v1
https://arxiv.org/pdf/2307.10776v1.pdf
https://github.com/vision-sjtu/lightning-nerf
false
false
true
pytorch
https://paperswithcode.com/paper/cat-enhancing-multimodal-large-language-model
CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios
2403.04640
https://arxiv.org/abs/2403.04640v1
https://arxiv.org/pdf/2403.04640v1.pdf
https://github.com/rikeilong/bay-cat
true
true
true
pytorch
https://paperswithcode.com/paper/adaptive-inertial-method
Adaptive Inertial Method
2505.15114
https://arxiv.org/abs/2505.15114v1
https://arxiv.org/pdf/2505.15114v1.pdf
https://github.com/harmoke/aim
true
true
true
none
https://paperswithcode.com/paper/splatam-splat-track-map-3d-gaussians-for
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM
2312.02126
https://arxiv.org/abs/2312.02126v3
https://arxiv.org/pdf/2312.02126v3.pdf
https://github.com/spla-tam/splatam
true
true
true
pytorch
https://paperswithcode.com/paper/tensor-network-simulations-for-non-orientable
Tensor network simulations for non-orientable surfaces
2402.15507
https://arxiv.org/abs/2402.15507v2
https://arxiv.org/pdf/2402.15507v2.pdf
https://github.com/elle-et-noire/hotrg-nonorientablesurface
true
true
true
none
https://paperswithcode.com/paper/move-as-you-say-interact-as-you-can-language
Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordance
2403.18036
https://arxiv.org/abs/2403.18036v1
https://arxiv.org/pdf/2403.18036v1.pdf
https://github.com/afford-motion/afford-motion
true
false
true
pytorch
https://paperswithcode.com/paper/revisiting-color-event-based-tracking-a
Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric
2211.11010
https://arxiv.org/abs/2211.11010v2
https://arxiv.org/pdf/2211.11010v2.pdf
https://github.com/event-ahu/coesot
true
true
true
pytorch
https://paperswithcode.com/paper/spurious-reconstruction-from-brain-activity
Spurious reconstruction from brain activity
2405.10078
https://arxiv.org/abs/2405.10078v5
https://arxiv.org/pdf/2405.10078v5.pdf
https://github.com/KamitaniLab/GOD_stimuli_annotations
true
false
false
none
https://paperswithcode.com/paper/online-deep-learning-learning-deep-neural
Online Deep Learning: Learning Deep Neural Networks on the Fly
1711.03705
http://arxiv.org/abs/1711.03705v1
http://arxiv.org/pdf/1711.03705v1.pdf
https://github.com/alison-carrera/onn
false
false
true
pytorch
https://paperswithcode.com/paper/a-survey-of-online-experiment-design-with-the
A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit
1510.00757
http://arxiv.org/abs/1510.00757v4
http://arxiv.org/pdf/1510.00757v4.pdf
https://github.com/alison-carrera/onn
false
false
true
pytorch