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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/ssd-single-shot-multibox-detector
SSD: Single Shot MultiBox Detector
1512.02325
http://arxiv.org/abs/1512.02325v5
http://arxiv.org/pdf/1512.02325v5.pdf
https://github.com/krstevskipetar/SSDLite320-MobileNetV3-object-detection
false
false
false
pytorch
https://paperswithcode.com/paper/training-language-models-for-social-deduction
Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning
2502.06060
https://arxiv.org/abs/2502.06060v1
https://arxiv.org/pdf/2502.06060v1.pdf
https://github.com/SocialDeductionLLM/SocialDeductionLLM
true
false
false
pytorch
https://paperswithcode.com/paper/identify-critical-kv-cache-in-llm-inference
Identify Critical KV Cache in LLM Inference from an Output Perturbation Perspective
2502.03805
https://arxiv.org/abs/2502.03805v1
https://arxiv.org/pdf/2502.03805v1.pdf
https://github.com/NVIDIA/kvpress
true
true
true
pytorch
https://paperswithcode.com/paper/td3-tucker-decomposition-based-dataset
TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation
2502.02854
https://arxiv.org/abs/2502.02854v2
https://arxiv.org/pdf/2502.02854v2.pdf
https://github.com/ustc-starteam/td3
true
true
false
pytorch
https://paperswithcode.com/paper/a-truncated-newton-method-for-optimal-1
A Truncated Newton Method for Optimal Transport
2504.02067
https://arxiv.org/abs/2504.02067v1
https://arxiv.org/pdf/2504.02067v1.pdf
https://github.com/metekemertas/mdot_tnt
false
true
false
pytorch
https://paperswithcode.com/paper/faster-segment-anything-towards-lightweight
Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
2306.14289
https://arxiv.org/abs/2306.14289v2
https://arxiv.org/pdf/2306.14289v2.pdf
https://github.com/ksugar/samapi
false
false
true
pytorch
https://paperswithcode.com/paper/segment-anything
Segment Anything
2304.02643
https://arxiv.org/abs/2304.02643v1
https://arxiv.org/pdf/2304.02643v1.pdf
https://github.com/ksugar/samapi
false
false
true
pytorch
https://paperswithcode.com/paper/instance-dependent-early-stopping
Instance-dependent Early Stopping
2502.07547
https://arxiv.org/abs/2502.07547v1
https://arxiv.org/pdf/2502.07547v1.pdf
https://github.com/tmllab/2025_ICLR_IES
true
false
false
pytorch
https://paperswithcode.com/paper/gs-pinn-greedy-sampling-for-parameter
GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations
2405.08537
https://arxiv.org/abs/2405.08537v1
https://arxiv.org/pdf/2405.08537v1.pdf
https://github.com/Ali-Forootani/PINN_DEIM
true
true
false
pytorch
https://paperswithcode.com/paper/position-aware-automatic-circuit-discovery
Position-aware Automatic Circuit Discovery
2502.04577
https://arxiv.org/abs/2502.04577v1
https://arxiv.org/pdf/2502.04577v1.pdf
https://github.com/technion-cs-nlp/peap
true
true
true
jax
https://paperswithcode.com/paper/coherent-local-explanations-for-mathematical
Coherent Local Explanations for Mathematical Optimization
2502.04840
https://arxiv.org/abs/2502.04840v2
https://arxiv.org/pdf/2502.04840v2.pdf
https://github.com/daanotto/clemo
true
true
false
none
https://paperswithcode.com/paper/overcoming-experimental-obstacles-in-two
Overcoming experimental obstacles in two-dimensional spectroscopy of a single molecule
2502.03924
https://arxiv.org/abs/2502.03924v1
https://arxiv.org/pdf/2502.03924v1.pdf
https://github.com/Lippitz-Lab/PLL-on-FPGA
true
false
true
none
https://paperswithcode.com/paper/breaking-bad-how-compilers-break-constant
Breaking Bad: How Compilers Break Constant-Time~Implementations
2410.13489
https://arxiv.org/abs/2410.13489v1
https://arxiv.org/pdf/2410.13489v1.pdf
https://github.com/Jumpst3r/breaking-bad-eval-infra
true
false
false
none
https://paperswithcode.com/paper/tracing-vulnerabilities-in-maven-a-study-of
Tracing Vulnerabilities in Maven: A Study of CVE lifecycles and Dependency Networks
2502.04621
https://arxiv.org/abs/2502.04621v2
https://arxiv.org/pdf/2502.04621v2.pdf
https://github.com/coreyyangsmith/msr2025
true
false
false
none
https://paperswithcode.com/paper/how-do-developers-use-code-suggestions-in
How Do Developers Use Code Suggestions in Pull Request Reviews?
2502.04835
https://arxiv.org/abs/2502.04835v1
https://arxiv.org/pdf/2502.04835v1.pdf
https://github.com/abiUni/chase25_replication-package
true
false
false
none
https://paperswithcode.com/paper/an-adaptive-weighted-qite-vqe-algorithm-for
An Adaptive Weighted QITE-VQE Algorithm for Combinatorial Optimization Problems
2504.10651
https://arxiv.org/abs/2504.10651v1
https://arxiv.org/pdf/2504.10651v1.pdf
https://github.com/ningyixie/adaptive-weighted-qite-vqe
true
true
true
pytorch
https://paperswithcode.com/paper/pseudo-reversing-and-its-application-for
Multiscale analysis via pseudo-reversing and applications to manifold-valued sequences
2305.06261
https://arxiv.org/abs/2305.06261v3
https://arxiv.org/pdf/2305.06261v3.pdf
https://github.com/waelmattar/pseudo-reversing
true
true
true
none
https://paperswithcode.com/paper/co-semdepth-fast-joint-semantic-segmentation
Co-SemDepth: Fast Joint Semantic Segmentation and Depth Estimation on Aerial Images
2503.17982
https://arxiv.org/abs/2503.17982v1
https://arxiv.org/pdf/2503.17982v1.pdf
https://github.com/malga-vision/co-semdepth
true
true
true
tf
https://paperswithcode.com/paper/hilots-high-low-temporal-sensitive
HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving
2503.17752
https://arxiv.org/abs/2503.17752v1
https://arxiv.org/pdf/2503.17752v1.pdf
https://github.com/rdlin118/hilots
true
true
true
pytorch
https://paperswithcode.com/paper/instruct-clip-improving-instruction-guided
Instruct-CLIP: Improving Instruction-Guided Image Editing with Automated Data Refinement Using Contrastive Learning
2503.18406
https://arxiv.org/abs/2503.18406v1
https://arxiv.org/pdf/2503.18406v1.pdf
https://github.com/sherryxtchen/instruct-clip
true
true
true
pytorch
https://paperswithcode.com/paper/multi-objective-optimization-using-the-r2
Multi-objective optimisation via the R2 utilities
2305.11774
https://arxiv.org/abs/2305.11774v4
https://arxiv.org/pdf/2305.11774v4.pdf
https://github.com/benmltu/scalarize
true
true
true
pytorch
https://paperswithcode.com/paper/enhancing-treatment-effect-estimation-via
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
2505.05242
https://arxiv.org/abs/2505.05242v1
https://arxiv.org/pdf/2505.05242v1.pdf
https://github.com/uqhwen2/FCCM
true
false
false
pytorch
https://paperswithcode.com/paper/hydrodynamics-of-suspensions-of-passive-and
Hydrodynamics of Suspensions of Passive and Active Rigid Particles: A Rigid Multiblob Approach
1602.02170
http://arxiv.org/abs/1602.02170v4
http://arxiv.org/pdf/1602.02170v4.pdf
https://github.com/stochasticHydroTools/RotationalDiffusion
true
true
true
none
https://paperswithcode.com/paper/brownian-dynamics-of-confined-suspensions-of
Brownian Dynamics of Confined Suspensions of Active Microrollers
1612.00474
http://arxiv.org/abs/1612.00474v3
http://arxiv.org/pdf/1612.00474v3.pdf
https://github.com/stochasticHydroTools/RotationalDiffusion
true
true
true
none
https://paperswithcode.com/paper/lumiere-a-space-time-diffusion-model-for
Lumiere: A Space-Time Diffusion Model for Video Generation
2401.12945
https://arxiv.org/abs/2401.12945v2
https://arxiv.org/pdf/2401.12945v2.pdf
https://github.com/lucidrains/lumiere-pytorch
false
false
false
pytorch
https://paperswithcode.com/paper/neural-guided-diffusion-bridges
Neural Guided Diffusion Bridges
2502.11909
https://arxiv.org/abs/2502.11909v1
https://arxiv.org/pdf/2502.11909v1.pdf
https://github.com/bookdiver/neuralbridge
true
true
true
jax
https://paperswithcode.com/paper/hierarchical-expert-prompt-for-large-language
Hierarchical Expert Prompt for Large-Language-Model: An Approach Defeat Elite AI in TextStarCraft II for the First Time
2502.11122
https://arxiv.org/abs/2502.11122v1
https://arxiv.org/pdf/2502.11122v1.pdf
https://github.com/luchang1113/hep-llm-play-starcraftii
true
true
false
none
https://paperswithcode.com/paper/cte-mlo-continuous-time-and-efficient-multi
CTE-MLO: Continuous-time and Efficient Multi-LiDAR Odometry with Localizability-aware Point Cloud Sampling
2408.04901
https://arxiv.org/abs/2408.04901v2
https://arxiv.org/pdf/2408.04901v2.pdf
https://github.com/shenhm516/cte-mlo
true
true
true
none
https://paperswithcode.com/paper/application-of-langevin-dynamics-to-advance
Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm
2409.01978
https://arxiv.org/abs/2409.01978v3
https://arxiv.org/pdf/2409.01978v3.pdf
https://github.com/borbysh/momentum-qng
true
true
true
none
https://paperswithcode.com/paper/text-driven-adaptation-of-foundation-models
Text-driven Adaptation of Foundation Models for Few-shot Surgical Workflow Analysis
2501.09555
https://arxiv.org/abs/2501.09555v2
https://arxiv.org/pdf/2501.09555v2.pdf
https://github.com/camma-public/surg-ftda
true
true
true
pytorch
https://paperswithcode.com/paper/abstract-syntax-tree-for-programming-language
Abstract Syntax Tree for Programming Language Understanding and Representation: How Far Are We?
2312.00413
https://arxiv.org/abs/2312.00413v1
https://arxiv.org/pdf/2312.00413v1.pdf
https://github.com/wssun/ast4plu
true
true
true
pytorch
https://paperswithcode.com/paper/score-based-generative-modeling-through-1
Score-Based Generative Modeling through Stochastic Differential Equations
2011.13456
https://arxiv.org/abs/2011.13456v2
https://arxiv.org/pdf/2011.13456v2.pdf
https://github.com/p-hss/consistency-climate-downscaling
false
false
true
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/p-hss/consistency-climate-downscaling
false
false
true
pytorch
https://paperswithcode.com/paper/unpaired-downscaling-of-fluid-flows-with
Unpaired Downscaling of Fluid Flows with Diffusion Bridges
2305.01822
https://arxiv.org/abs/2305.01822v1
https://arxiv.org/pdf/2305.01822v1.pdf
https://github.com/p-hss/consistency-climate-downscaling
false
false
true
pytorch
https://paperswithcode.com/paper/litecua-computer-as-mcp-server-for-computer
LiteCUA: Computer as MCP Server for Computer-Use Agent on AIOS
2505.18829
https://arxiv.org/abs/2505.18829v1
https://arxiv.org/pdf/2505.18829v1.pdf
https://github.com/agiresearch/aios
true
true
true
none
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/p-hss/consistency-climate-downscaling
false
false
true
pytorch
https://paperswithcode.com/paper/a-mem-agentic-memory-for-llm-agents
A-MEM: Agentic Memory for LLM Agents
2502.12110
https://arxiv.org/abs/2502.12110v9
https://arxiv.org/pdf/2502.12110v9.pdf
https://github.com/agiresearch/aios
false
false
true
none
https://paperswithcode.com/paper/search-is-all-you-need-for-few-shot-anomaly
Search is All You Need for Few-shot Anomaly Detection
2504.11895
https://arxiv.org/abs/2504.11895v2
https://arxiv.org/pdf/2504.11895v2.pdf
https://github.com/qiqigeww/visionad
true
true
true
none
https://paperswithcode.com/paper/the-impact-of-model-zoo-size-and-composition
The Impact of Model Zoo Size and Composition on Weight Space Learning
2504.10141
https://arxiv.org/abs/2504.10141v1
https://arxiv.org/pdf/2504.10141v1.pdf
https://github.com/hsg-aiml/multizoo-sane
true
true
true
pytorch
https://paperswithcode.com/paper/vistai-benchmarking-vision-language-models
VisTai: Benchmarking Vision-Language Models for Traditional Chinese in Taiwan
2503.10427
https://arxiv.org/abs/2503.10427v1
https://arxiv.org/pdf/2503.10427v1.pdf
https://github.com/TMMMU-Benchmark/evaluation
true
false
false
pytorch
https://paperswithcode.com/paper/mamba-time-series-forecasting-with
Mamba time series forecasting with uncertainty quantification
2503.10873
https://arxiv.org/abs/2503.10873v2
https://arxiv.org/pdf/2503.10873v2.pdf
https://github.com/pessoap/mamba-probtsf
true
true
true
pytorch
https://paperswithcode.com/paper/new-exponential-law-for-real-networks
New exponential law for real networks
2504.09978
https://arxiv.org/abs/2504.09978v1
https://arxiv.org/pdf/2504.09978v1.pdf
https://github.com/samoylo57/ksi-centrality
true
true
false
none
https://paperswithcode.com/paper/an-efficient-quantum-classifier-based-on
An Efficient Quantum Classifier Based on Hamiltonian Representations
2504.10542
https://arxiv.org/abs/2504.10542v1
https://arxiv.org/pdf/2504.10542v1.pdf
https://github.com/ukplab/arxiv2025-ham-classifier
true
true
false
pytorch
https://paperswithcode.com/paper/neural-network-libraries-a-deep-learning
Neural Network Libraries: A Deep Learning Framework Designed from Engineers' Perspectives
2102.06725
https://arxiv.org/abs/2102.06725v2
https://arxiv.org/pdf/2102.06725v2.pdf
https://github.com/sony/nnabla
false
false
true
tf
https://paperswithcode.com/paper/motion-of-ferrodark-solitons-in-harmonically
Motion of ferrodark solitons in harmonically trapped superfluids: spin corrections and emergent quartic potentials exhibiting symmetry breaking
2504.12980
https://arxiv.org/abs/2504.12980v2
https://arxiv.org/pdf/2504.12980v2.pdf
https://github.com/Xiaoquanyu/resaerch-group-on-quantum-liquid
false
false
true
none
https://paperswithcode.com/paper/album-a-framework-for-scientific-data
Album: a framework for scientific data processing with software solutions of heterogeneous tools
2110.00601
https://arxiv.org/abs/2110.00601v1
https://arxiv.org/pdf/2110.00601v1.pdf
https://gitlab.com/album-app/album
false
false
true
none
https://paperswithcode.com/paper/foundir-unleashing-million-scale-training
FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration
2412.01427
https://arxiv.org/abs/2412.01427v1
https://arxiv.org/pdf/2412.01427v1.pdf
https://github.com/House-Leo/FoundIR
false
false
true
pytorch
https://paperswithcode.com/paper/spatial-and-temporal-mutual-promotion-for
Spatial and Temporal Mutual Promotion for Video-based Person Re-identification
1812.10305
http://arxiv.org/abs/1812.10305v1
http://arxiv.org/pdf/1812.10305v1.pdf
https://github.com/MindSpore-scientific/code-14/tree/main/Spatial%20and%20Temporal%20Mutual%20Promotion%20for%20Video-based%20Person%20Re-identification
false
false
false
mindspore
https://paperswithcode.com/paper/labtop-a-unified-model-for-lab-test-outcome
LabTOP: A Unified Model for Lab Test Outcome Prediction on Electronic Health Records
2502.14259
https://arxiv.org/abs/2502.14259v3
https://arxiv.org/pdf/2502.14259v3.pdf
https://github.com/sujeongim/labtop
true
true
false
pytorch
https://paperswithcode.com/paper/decoupled-weight-decay-regularization
Decoupled Weight Decay Regularization
1711.05101
http://arxiv.org/abs/1711.05101v3
http://arxiv.org/pdf/1711.05101v3.pdf
https://github.com/bojone/tiger
false
false
true
tf
https://paperswithcode.com/paper/signsgd-compressed-optimisation-for-non
signSGD: Compressed Optimisation for Non-Convex Problems
1802.04434
http://arxiv.org/abs/1802.04434v3
http://arxiv.org/pdf/1802.04434v3.pdf
https://github.com/bojone/tiger
false
false
true
tf
https://paperswithcode.com/paper/reinforcement-learning-based-heuristics-to
Reinforcement Learning-based Heuristics to Guide Domain-Independent Dynamic Programming
2503.16371
https://arxiv.org/abs/2503.16371v2
https://arxiv.org/pdf/2503.16371v2.pdf
https://github.com/minori5214/rl-guided-didp
true
true
true
pytorch
https://paperswithcode.com/paper/open-vocabulary-multimodal-emotion
OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
2410.01495
https://arxiv.org/abs/2410.01495v3
https://arxiv.org/pdf/2410.01495v3.pdf
https://github.com/zeroqiaoba/affectgpt
true
true
true
pytorch
https://paperswithcode.com/paper/affectgpt-a-new-dataset-model-and-benchmark
AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
2501.16566
https://arxiv.org/abs/2501.16566v2
https://arxiv.org/pdf/2501.16566v2.pdf
https://github.com/zeroqiaoba/affectgpt
true
true
true
pytorch
https://paperswithcode.com/paper/affectgpt-a-new-dataset-model-and-benchmark
AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
2501.16566
https://arxiv.org/abs/2501.16566v2
https://arxiv.org/pdf/2501.16566v2.pdf
https://github.com/zeroqiaoba/explainable-multimodal-emotion-reasoning
false
false
true
pytorch
https://paperswithcode.com/paper/spatial-temporal-identity-a-simple-yet
Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting
2208.05233
https://arxiv.org/abs/2208.05233v2
https://arxiv.org/pdf/2208.05233v2.pdf
https://github.com/GestaltCogTeam/STID
false
false
true
pytorch
https://paperswithcode.com/paper/deep-dive-into-probabilistic-delta-debugging
Toward a Better Understanding of Probabilistic Delta Debugging
2408.04735
https://arxiv.org/abs/2408.04735v4
https://arxiv.org/pdf/2408.04735v4.pdf
https://github.com/uw-pluverse/perses
true
true
false
none
https://paperswithcode.com/paper/deepseek-prover-v2-advancing-formal
DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition
2504.21801
https://arxiv.org/abs/2504.21801v1
https://arxiv.org/pdf/2504.21801v1.pdf
https://github.com/deepseek-ai/deepseek-prover-v2
true
true
false
pytorch
https://paperswithcode.com/paper/rad-a-metric-for-medical-image-distribution
Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets
2412.01496
https://arxiv.org/abs/2412.01496v2
https://arxiv.org/pdf/2412.01496v2.pdf
https://github.com/richardobi/frd-score
true
true
true
none
https://paperswithcode.com/paper/towards-learning-contrast-kinetics-with-multi
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models
2403.13890
https://arxiv.org/abs/2403.13890v3
https://arxiv.org/pdf/2403.13890v3.pdf
https://github.com/richardobi/frd-score
false
false
true
none
https://paperswithcode.com/paper/atmosmj-revisiting-gating-mechanism-for-ai
AtmosMJ: Revisiting Gating Mechanism for AI Weather Forecasting Beyond the Year Scale
2506.09733
https://arxiv.org/abs/2506.09733v1
https://arxiv.org/pdf/2506.09733v1.pdf
https://github.com/jmj2316/AtmosMJ/blob/main/README.md
true
false
false
none
https://paperswithcode.com/paper/proximal-policy-optimization-algorithms
Proximal Policy Optimization Algorithms
1707.06347
http://arxiv.org/abs/1707.06347v2
http://arxiv.org/pdf/1707.06347v2.pdf
https://github.com/jongornet14/HyperController
false
false
true
pytorch
https://paperswithcode.com/paper/2305-14516
Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
2305.14516
https://arxiv.org/abs/2305.14516v2
https://arxiv.org/pdf/2305.14516v2.pdf
https://github.com/mlcommons/chakra
false
false
true
none
https://paperswithcode.com/paper/uniworld-v1-high-resolution-semantic-encoders
UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
2506.03147
https://arxiv.org/abs/2506.03147v3
https://arxiv.org/pdf/2506.03147v3.pdf
https://github.com/pku-yuangroup/imgedit
false
false
true
pytorch
https://paperswithcode.com/paper/sudden-drops-in-the-loss-syntax-acquisition
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
2309.07311
https://arxiv.org/abs/2309.07311v6
https://arxiv.org/pdf/2309.07311v6.pdf
https://github.com/angie-chen55/sudden-drops-in-the-loss
true
true
false
pytorch
https://paperswithcode.com/paper/the-gray-graph-is-pseudo-2-factor-isomorphic
The Gray graph is pseudo 2-factor isomorphic
2504.12095
https://arxiv.org/abs/2504.12095v1
https://arxiv.org/pdf/2504.12095v1.pdf
https://github.com/tiboat/2factorparitychecker
true
true
false
none
https://paperswithcode.com/paper/open-vocabulary-multimodal-emotion
OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
2410.01495
https://arxiv.org/abs/2410.01495v3
https://arxiv.org/pdf/2410.01495v3.pdf
https://github.com/zeroqiaoba/explainable-multimodal-emotion-reasoning
false
false
true
pytorch
https://paperswithcode.com/paper/xy-cut-advanced-layout-ordering-via
XY-Cut++: Advanced Layout Ordering via Hierarchical Mask Mechanism on a Novel Benchmark
2504.10258
https://arxiv.org/abs/2504.10258v1
https://arxiv.org/pdf/2504.10258v1.pdf
https://github.com/liushuai35/PaddleXrc
true
false
false
paddle
https://paperswithcode.com/paper/a-benchmark-for-incremental-micro-expression
A Benchmark for Incremental Micro-expression Recognition
2501.19111
https://arxiv.org/abs/2501.19111v2
https://arxiv.org/pdf/2501.19111v2.pdf
https://github.com/zhengqinlai/imer-benchmark
true
true
false
pytorch
https://paperswithcode.com/paper/freepca-integrating-consistency-information
FreePCA: Integrating Consistency Information across Long-short Frames in Training-free Long Video Generation via Principal Component Analysis
2505.01172
https://arxiv.org/abs/2505.01172v1
https://arxiv.org/pdf/2505.01172v1.pdf
https://github.com/josephtitan/freepca
true
true
true
pytorch
https://paperswithcode.com/paper/adaptive-rkhs-fourier-features-for
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
2407.01856
https://arxiv.org/abs/2407.01856v2
https://arxiv.org/pdf/2407.01856v2.pdf
https://github.com/shixinxing/lfm-vff
true
true
false
pytorch
https://paperswithcode.com/paper/real-time-small-area-estimation-of-food
Real-time small area estimation of food security in Zimbabwe: integrating mobile-phone and face-to-face surveys using joint multilevel regression and poststratification
2505.03517
https://arxiv.org/abs/2505.03517v1
https://arxiv.org/pdf/2505.03517v1.pdf
https://github.com/mlglobalhealth/realtime-sae-zimbabwe
true
true
true
none
https://paperswithcode.com/paper/an-empirical-study-of-conjugate-gradient
An Empirical Study of Conjugate Gradient Preconditioners for Solving Symmetric Positive Definite Systems of Linear Equations
2505.20696
https://arxiv.org/abs/2505.20696v1
https://arxiv.org/pdf/2505.20696v1.pdf
https://github.com/tunnellm/CAPPABenchmarkTools
true
false
true
none
https://paperswithcode.com/paper/fast-not-fancy-rethinking-g2p-with-rich-data
Fast, Not Fancy: Rethinking G2P with Rich Data and Rule-Based Models
2505.12973
https://arxiv.org/abs/2505.12973v1
https://arxiv.org/pdf/2505.12973v1.pdf
https://github.com/MahtaFetrat/Homo-GE2PE-Persian
true
true
true
pytorch
https://paperswithcode.com/paper/llm-based-query-expansion-fails-for
LLM-based Query Expansion Fails for Unfamiliar and Ambiguous Queries
2505.12694
https://arxiv.org/abs/2505.12694v1
https://arxiv.org/pdf/2505.12694v1.pdf
https://github.com/aken12/LLM-based-QE-fails
true
true
false
none
https://paperswithcode.com/paper/globally-optimal-contrast-maximisation-for
Globally Optimal Contrast Maximisation for Event-based Motion Estimation
2002.10686
https://arxiv.org/abs/2002.10686v3
https://arxiv.org/pdf/2002.10686v3.pdf
https://github.com/uzh-rpg/event-based_vision_resources
true
true
true
pytorch
https://paperswithcode.com/paper/from-single-to-multi-how-llms-hallucinate-in
From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization
2410.13961
https://arxiv.org/abs/2410.13961v1
https://arxiv.org/pdf/2410.13961v1.pdf
https://github.com/megagonlabs/hallucination_mds
true
true
true
none
https://paperswithcode.com/paper/frog-soup-zero-shot-in-context-and-sample
Frog Soup: Zero-Shot, In-Context, and Sample-Efficient Frogger Agents
2505.03947
https://arxiv.org/abs/2505.03947v1
https://arxiv.org/pdf/2505.03947v1.pdf
https://github.com/alienkevin/frogger
true
true
false
none
https://paperswithcode.com/paper/comparing-restricted-mean-survival-times-in
Comparing restricted mean survival times in small sample clinical trials using pseudo-observations
2408.15607
https://arxiv.org/abs/2408.15607v1
https://arxiv.org/pdf/2408.15607v1.pdf
https://github.com/DavidJesse21/rmst-small-samples
true
false
true
none
https://paperswithcode.com/paper/on-the-generalizability-of-foundation-models
On the Generalizability of Foundation Models for Crop Type Mapping
2409.09451
https://arxiv.org/abs/2409.09451v4
https://arxiv.org/pdf/2409.09451v4.pdf
https://github.com/yichiac/crop-type-transfer-learning
true
true
true
none
https://paperswithcode.com/paper/benchmarking-graph-conformal-prediction
Conformal Prediction: A Theoretical Note and Benchmarking Transductive Node Classification in Graphs
2409.18332
https://arxiv.org/abs/2409.18332v2
https://arxiv.org/pdf/2409.18332v2.pdf
https://github.com/pranavmaneriker/graphconformal-code
true
true
false
pytorch
https://paperswithcode.com/paper/tensor-cspnet-a-novel-geometric-deep-learning
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification
2202.02472
https://arxiv.org/abs/2202.02472v3
https://arxiv.org/pdf/2202.02472v3.pdf
https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet
true
false
true
pytorch
https://paperswithcode.com/paper/hierarchical-neurosymbolic-approach-for
Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality Assessment
2403.13798
https://arxiv.org/abs/2403.13798v2
https://arxiv.org/pdf/2403.13798v2.pdf
https://github.com/ParitoshParmar/Fitness-AQA
false
false
true
pytorch
https://paperswithcode.com/paper/fl-defender-combating-targeted-attacks-in
FL-Defender: Combating Targeted Attacks in Federated Learning
2207.00872
https://arxiv.org/abs/2207.00872v1
https://arxiv.org/pdf/2207.00872v1.pdf
https://github.com/anonymized30/fl-defender
true
true
true
pytorch
https://paperswithcode.com/paper/spd-learning-for-covariance-based
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges
2504.18882
https://arxiv.org/abs/2504.18882v1
https://arxiv.org/pdf/2504.18882v1.pdf
https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet
true
false
true
pytorch
https://paperswithcode.com/paper/on-the-similarities-of-embeddings-in
On the Similarities of Embeddings in Contrastive Learning
2506.09781
https://arxiv.org/abs/2506.09781v1
https://arxiv.org/pdf/2506.09781v1.pdf
https://github.com/leechungpa/embedding-similarity-cl
true
true
true
pytorch
https://paperswithcode.com/paper/llmail-inject-a-dataset-from-a-realistic
LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection Challenge
2506.09956
https://arxiv.org/abs/2506.09956v1
https://arxiv.org/pdf/2506.09956v1.pdf
https://github.com/microsoft/llmail-inject-challenge
true
true
true
none
https://paperswithcode.com/paper/situated-bayes-feminist-and-pluriversal
Situated Bayes -- Feminist and Pluriversal Perspectives on Bayesian Knowledge
2506.09472
https://arxiv.org/abs/2506.09472v1
https://arxiv.org/pdf/2506.09472v1.pdf
https://github.com/juni-schindler/situated-bayes
true
true
false
none
https://paperswithcode.com/paper/2506-10558
StepProof: Step-by-step verification of natural language mathematical proofs
2506.10558
https://arxiv.org/abs/2506.10558v1
https://arxiv.org/pdf/2506.10558v1.pdf
https://github.com/r1niga/step-proof
true
true
false
pytorch
https://paperswithcode.com/paper/neural-stochastic-partial-differential
Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics
2110.10249
https://arxiv.org/abs/2110.10249v8
https://arxiv.org/pdf/2110.10249v8.pdf
https://github.com/crispitagorico/torchspde
false
false
true
pytorch
https://paperswithcode.com/paper/noloco-no-all-reduce-low-communication
NoLoCo: No-all-reduce Low Communication Training Method for Large Models
2506.10911
https://arxiv.org/abs/2506.10911v1
https://arxiv.org/pdf/2506.10911v1.pdf
https://github.com/gensyn-ai/noloco
true
true
true
pytorch
https://paperswithcode.com/paper/robustly-improving-llm-fairness-in-realistic
Robustly Improving LLM Fairness in Realistic Settings via Interpretability
2506.10922
https://arxiv.org/abs/2506.10922v1
https://arxiv.org/pdf/2506.10922v1.pdf
https://github.com/adamkarvonen/llm_bias
true
true
true
jax
https://paperswithcode.com/paper/language-models-represent-beliefs-of-self-and
Language Models Represent Beliefs of Self and Others
2402.18496
https://arxiv.org/abs/2402.18496v3
https://arxiv.org/pdf/2402.18496v3.pdf
https://github.com/walter0807/repbelief
false
false
true
pytorch
https://paperswithcode.com/paper/scalable-importance-sampling-in-high
Scalable Importance Sampling in High Dimensions with Low-Rank Mixture Proposals
2505.13335
https://arxiv.org/abs/2505.13335v1
https://arxiv.org/pdf/2505.13335v1.pdf
https://github.com/sisl/MPPCAImportanceSampling
true
true
false
jax
https://paperswithcode.com/paper/benchmarking-the-myopic-trap-positional-bias
Benchmarking the Myopic Trap: Positional Bias in Information Retrieval
2505.13950
https://arxiv.org/abs/2505.13950v1
https://arxiv.org/pdf/2505.13950v1.pdf
https://github.com/novasearch-team/rag-retrieval
true
true
false
pytorch
https://paperswithcode.com/paper/rainbow-combining-improvements-in-deep
Rainbow: Combining Improvements in Deep Reinforcement Learning
1710.02298
http://arxiv.org/abs/1710.02298v1
http://arxiv.org/pdf/1710.02298v1.pdf
https://github.com/jacobkooi/hadamax
false
false
true
jax
https://paperswithcode.com/paper/discrete-markov-bridge
Discrete Markov Bridge
2505.19752
https://arxiv.org/abs/2505.19752v1
https://arxiv.org/pdf/2505.19752v1.pdf
https://github.com/henry839/discrete-markov-bridge
true
true
true
pytorch
https://paperswithcode.com/paper/confidence-weighted-boundary-aware-learning
Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation
2502.15152
https://arxiv.org/abs/2502.15152v1
https://arxiv.org/pdf/2502.15152v1.pdf
https://github.com/psychofict/CW-BASS
true
false
false
pytorch
https://paperswithcode.com/paper/sageattention2-a-more-efficient
SageAttention2++: A More Efficient Implementation of SageAttention2
2505.21136
https://arxiv.org/abs/2505.21136v3
https://arxiv.org/pdf/2505.21136v3.pdf
https://github.com/thu-ml/spargeattn
false
false
true
pytorch
https://paperswithcode.com/paper/fast-molmer-sorensen-gates-in-trapped-ion
Fast Mølmer-Sørensen gates in trapped-ion quantum processors with compensated carrier transition
2501.02387
https://arxiv.org/abs/2501.02387v2
https://arxiv.org/pdf/2501.02387v2.pdf
https://github.com/evganikin/fast_molmer_sorensen_w_carrier
false
false
true
none