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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/gamba-marry-gaussian-splatting-with-mamba-for
Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction
2403.18795
https://arxiv.org/abs/2403.18795v3
https://arxiv.org/pdf/2403.18795v3.pdf
https://github.com/skyworkai/mvgamba
false
false
true
jax
https://paperswithcode.com/paper/deep-regression-on-manifolds-a-3d-rotation
Deep Regression on Manifolds: A 3D Rotation Case Study
2103.16317
https://arxiv.org/abs/2103.16317v2
https://arxiv.org/pdf/2103.16317v2.pdf
https://github.com/naver/roma
true
false
true
pytorch
https://paperswithcode.com/paper/tfg-flow-training-free-guidance-in-multimodal
TFG-Flow: Training-free Guidance in Multimodal Generative Flow
2501.14216
https://arxiv.org/abs/2501.14216v3
https://arxiv.org/pdf/2501.14216v3.pdf
https://github.com/linhaowei1/tfg-flow
true
true
false
pytorch
https://paperswithcode.com/paper/adacqr-enhancing-query-reformulation-for
AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment
2407.01965
https://arxiv.org/abs/2407.01965v3
https://arxiv.org/pdf/2407.01965v3.pdf
https://github.com/init0xyz/AdaCQR
true
true
true
pytorch
https://paperswithcode.com/paper/flashvtg-feature-layering-and-adaptive-score
FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal Grounding
2412.13441
https://arxiv.org/abs/2412.13441v1
https://arxiv.org/pdf/2412.13441v1.pdf
https://github.com/zhuo-cao/flashvtg
true
true
false
pytorch
https://paperswithcode.com/paper/beyond-accuracy-on-the-effects-of-fine-tuning
Beyond Accuracy: On the Effects of Fine-tuning Towards Vision-Language Model's Prediction Rationality
2412.13333
https://arxiv.org/abs/2412.13333v1
https://arxiv.org/pdf/2412.13333v1.pdf
https://github.com/deep-real/vlm-pred-rationality
true
true
false
pytorch
https://paperswithcode.com/paper/3d-registration-in-30-years-a-survey
3D Registration in 30 Years: A Survey
2412.13735
https://arxiv.org/abs/2412.13735v2
https://arxiv.org/pdf/2412.13735v2.pdf
https://github.com/amyyyy11/3d-registration-in-30-years-a-survey
true
true
false
none
https://paperswithcode.com/paper/multimodal-marvels-of-deep-learning-in
Multimodal Marvels of Deep Learning in Medical Diagnosis: A Comprehensive Review of COVID-19 Detection
2501.09506
https://arxiv.org/abs/2501.09506v2
https://arxiv.org/pdf/2501.09506v2.pdf
https://github.com/shafiq-islam-cse/multimodal-marvels-of-deep-learning-using-image-speech-and-text-review-of-covid-19-detection
true
true
false
tf
https://paperswithcode.com/paper/rwkv-reinventing-rnns-for-the-transformer-era
RWKV: Reinventing RNNs for the Transformer Era
2305.13048
https://arxiv.org/abs/2305.13048v2
https://arxiv.org/pdf/2305.13048v2.pdf
https://github.com/asuller/rwkv-musicgenerator
false
false
true
pytorch
https://paperswithcode.com/paper/diffsim-taming-diffusion-models-for
DiffSim: Taming Diffusion Models for Evaluating Visual Similarity
2412.14580
https://arxiv.org/abs/2412.14580v1
https://arxiv.org/pdf/2412.14580v1.pdf
https://github.com/showlab/diffsim
true
true
true
pytorch
https://paperswithcode.com/paper/magicanimate-temporally-consistent-human
MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model
2311.16498
https://arxiv.org/abs/2311.16498v1
https://arxiv.org/pdf/2311.16498v1.pdf
https://github.com/showlab/diffsim
false
false
true
pytorch
https://paperswithcode.com/paper/ltlf-synthesis-under-unreliable-input
LTLf Synthesis Under Unreliable Input
2412.14728
https://arxiv.org/abs/2412.14728v1
https://arxiv.org/pdf/2412.14728v1.pdf
https://github.com/whitemech/ltlf-synth-unrel-input-aaai2025
true
true
false
none
https://paperswithcode.com/paper/promptable-representation-distribution
Promptable Representation Distribution Learning and Data Augmentation for Gigapixel Histopathology WSI Analysis
2412.14473
https://arxiv.org/abs/2412.14473v1
https://arxiv.org/pdf/2412.14473v1.pdf
https://github.com/lazytkm/prdl
true
true
false
pytorch
https://paperswithcode.com/paper/remoe-fully-differentiable-mixture-of-experts
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing
2412.14711
https://arxiv.org/abs/2412.14711v1
https://arxiv.org/pdf/2412.14711v1.pdf
https://github.com/thu-ml/remoe
true
true
true
pytorch
https://paperswithcode.com/paper/probing-entanglement-dynamics-and-topological
Probing entanglement dynamics and topological transitions on noisy intermediate-scale quantum computers
2406.10159
https://arxiv.org/abs/2406.10159v3
https://arxiv.org/pdf/2406.10159v3.pdf
https://github.com/qurrium/qurrium
true
true
true
none
https://paperswithcode.com/paper/transmit-what-you-need-task-adaptive-semantic
Transmit What You Need: Task-Adaptive Semantic Communications for Visual Information
2412.13646
https://arxiv.org/abs/2412.13646v1
https://arxiv.org/pdf/2412.13646v1.pdf
https://github.com/jhpark2024/jhpark.github.io
true
true
true
none
https://paperswithcode.com/paper/open-source-open-threats-investigating
Open Source, Open Threats? Investigating Security Challenges in Open-Source Software
2506.12995
https://arxiv.org/abs/2506.12995v1
https://arxiv.org/pdf/2506.12995v1.pdf
https://github.com/sa-akhavani/oss-security
true
true
false
none
https://paperswithcode.com/paper/sok-advances-and-open-problems-in-web
SoK: Advances and Open Problems in Web Tracking
2506.14057
https://arxiv.org/abs/2506.14057v1
https://arxiv.org/pdf/2506.14057v1.pdf
https://github.com/privacysandstorm/sok-advances-open-problems-web-tracking
true
true
true
none
https://paperswithcode.com/paper/tailoring-instructions-to-student-s-learning
Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation
2305.09651
https://arxiv.org/abs/2305.09651v3
https://arxiv.org/pdf/2305.09651v3.pdf
https://github.com/twinkle0331/lgtm
true
true
true
pytorch
https://paperswithcode.com/paper/a-closest-point-method-for-surface-pdes-with
A Closest Point Method for PDEs on Manifolds with Interior Boundary Conditions for Geometry Processing
2305.04711
https://arxiv.org/abs/2305.04711v2
https://arxiv.org/pdf/2305.04711v2.pdf
https://github.com/nathandking/cpm-ibc
true
true
false
none
https://paperswithcode.com/paper/resque-quantifying-estimator-to-task-and
RESQUE: Quantifying Estimator to Task and Distribution Shift for Sustainable Model Reusability
2412.15511
https://arxiv.org/abs/2412.15511v1
https://arxiv.org/pdf/2412.15511v1.pdf
https://github.com/jekimlab/aaai2025resque
true
true
true
pytorch
https://paperswithcode.com/paper/sdxl-improving-latent-diffusion-models-for
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
2307.01952
https://arxiv.org/abs/2307.01952v1
https://arxiv.org/pdf/2307.01952v1.pdf
https://github.com/andrew-miao/RPO
false
false
true
pytorch
https://paperswithcode.com/paper/anid-how-far-are-we-evaluating-the
D-Judge: How Far Are We? Evaluating the Discrepancies Between AI-synthesized Images and Natural Images through Multimodal Guidance
2412.17632
https://arxiv.org/abs/2412.17632v2
https://arxiv.org/pdf/2412.17632v2.pdf
https://github.com/ryliu68/anid
true
true
false
pytorch
https://paperswithcode.com/paper/line-graph-vietoris-rips-persistence-diagram
Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning
2412.17468
https://arxiv.org/abs/2412.17468v1
https://arxiv.org/pdf/2412.17468v1.pdf
https://github.com/samsungsds-research-papers/lgvr
true
true
false
pytorch
https://paperswithcode.com/paper/q-lime-p-a-quantum-inspired-extension-to-lime
Q-LIME $π$: A Quantum-Inspired Extension to LIME
2412.17197
https://arxiv.org/abs/2412.17197v1
https://arxiv.org/pdf/2412.17197v1.pdf
https://github.com/nelabdiel/qlime
true
true
false
none
https://paperswithcode.com/paper/patchalign-fair-and-accurate-skin-disease
PatchAlign:Fair and Accurate Skin Disease Image Classification by Alignment with Clinical Labels
2409.04975
https://arxiv.org/abs/2409.04975v1
https://arxiv.org/pdf/2409.04975v1.pdf
https://github.com/aayushmanace/patchalign24
true
true
true
pytorch
https://paperswithcode.com/paper/simlabel-consistency-guided-ood-detection
SimLabel: Consistency-Guided OOD Detection with Pretrained Vision-Language Models
2501.11485
https://arxiv.org/abs/2501.11485v1
https://arxiv.org/pdf/2501.11485v1.pdf
https://github.com/shuzou-1/simlabel
true
true
false
pytorch
https://paperswithcode.com/paper/attention-guided-version-of-2d-unet-for
Attention-Guided Version of 2D UNet for Automatic Brain Tumor Segmentation
2004.02009
https://arxiv.org/abs/2004.02009v1
https://arxiv.org/pdf/2004.02009v1.pdf
https://github.com/mehrdad-noori/brain-tumor-segmentation
false
false
false
tf
https://paperswithcode.com/paper/a-demonstration-of-over-the-air-computation
A Demonstration of Over-the-Air Computation for Federated Edge Learning
2209.09954
https://arxiv.org/abs/2209.09954v1
https://arxiv.org/pdf/2209.09954v1.pdf
https://github.com/alphansahin/FEELwithSDRs
true
false
true
pytorch
https://paperswithcode.com/paper/self-attention-recurrent-summarization
Self-Attention Recurrent Summarization Network with Reinforcement Learning for Video Summarization Task
null
https://ieeexplore.ieee.org/abstract/document/9428142
https://ieeexplore.ieee.org/abstract/document/9428142
https://github.com/phaphuang/dsr-rl
false
true
false
pytorch
https://paperswithcode.com/paper/i-srt-aligning-large-multimodal-models-for
ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO
2406.11280
https://arxiv.org/abs/2406.11280v2
https://arxiv.org/pdf/2406.11280v2.pdf
https://github.com/snumprlab/SRT
true
true
true
pytorch
https://paperswithcode.com/paper/radio-amplified-improved-baselines-for
RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models
2412.07679
https://arxiv.org/abs/2412.07679v1
https://arxiv.org/pdf/2412.07679v1.pdf
https://github.com/nvlabs/radio
true
true
true
pytorch
https://paperswithcode.com/paper/optimal-density-functions-for-weighted
Optimal Density Functions for Weighted Convolution in Learning Models
2505.24527
https://arxiv.org/abs/2505.24527v1
https://arxiv.org/pdf/2505.24527v1.pdf
https://github.com/cammarasana123/weightedconvolution2.0
false
false
true
pytorch
https://paperswithcode.com/paper/pac-confidence-sets-for-deep-neural-networks-1
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
2001.00106
https://arxiv.org/abs/2001.00106v2
https://arxiv.org/pdf/2001.00106v2.pdf
https://github.com/leoandeol/cods
false
false
true
pytorch
https://paperswithcode.com/paper/conformal-risk-control
Conformal Risk Control
2208.02814
https://arxiv.org/abs/2208.02814v4
https://arxiv.org/pdf/2208.02814v4.pdf
https://github.com/leoandeol/cods
false
false
true
pytorch
https://paperswithcode.com/paper/nuc-net-non-uniform-cylindrical-partition
NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation
2505.24634
https://arxiv.org/abs/2505.24634v2
https://arxiv.org/pdf/2505.24634v2.pdf
https://github.com/alanwxz/nuc-net
true
true
false
pytorch
https://paperswithcode.com/paper/overcoming-beam-squint-in-dual-wideband
Overcoming Beam Squint in Dual-Wideband mmWave MIMO Channel Estimation: A Bayesian Multi-Band Sparsity Approach
2306.11149
https://arxiv.org/abs/2306.11149v1
https://arxiv.org/pdf/2306.11149v1.pdf
https://github.com/xumaomao94/BayesianDualWideband
true
false
false
none
https://paperswithcode.com/paper/cesped-a-new-benchmark-for-supervised
CESPED: a new benchmark for supervised particle pose estimation in Cryo-EM
2311.06194
https://arxiv.org/abs/2311.06194v5
https://arxiv.org/pdf/2311.06194v5.pdf
https://github.com/rsanchezgarc/cesped
true
true
true
pytorch
https://paperswithcode.com/paper/anonymizing-speech-evaluating-and-designing
Anonymizing Speech: Evaluating and Designing Speaker Anonymization Techniques
2308.04455
https://arxiv.org/abs/2308.04455v4
https://arxiv.org/pdf/2308.04455v4.pdf
https://github.com/deep-privacy/SA-toolkit
true
true
true
pytorch
https://paperswithcode.com/paper/from-debate-to-equilibrium-belief-driven
From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium
2506.08292
https://arxiv.org/abs/2506.08292v1
https://arxiv.org/pdf/2506.08292v1.pdf
https://github.com/tmlr-group/econ
true
true
false
pytorch
https://paperswithcode.com/paper/2506-08249
RADAR: Benchmarking Language Models on Imperfect Tabular Data
2506.08249
https://arxiv.org/abs/2506.08249v1
https://arxiv.org/pdf/2506.08249v1.pdf
https://github.com/kenqgu/radar
true
true
true
none
https://paperswithcode.com/paper/rnn-transducer-based-losses-for-speech
RNN-Transducer-based Losses for Speech Recognition on Noisy Targets
2504.06963
https://arxiv.org/abs/2504.06963v1
https://arxiv.org/pdf/2504.06963v1.pdf
https://github.com/artbataev/uol_final
true
true
false
pytorch
https://paperswithcode.com/paper/building-semi-supervised-decision-trees-with
Building semi-supervised decision trees with semi-cart algorithm
null
https://link.springer.com/article/10.1007/s13042-024-02161-z
https://link.springer.com/content/pdf/10.1007/s13042-024-02161-z.pdf
https://github.com/WeightedAI/semicart
false
false
false
none
https://paperswithcode.com/paper/reference-trustable-decoding-a-training-free
Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models
2409.20181
https://arxiv.org/abs/2409.20181v2
https://arxiv.org/pdf/2409.20181v2.pdf
https://github.com/shiluohe/referencetrustabledecoding
true
true
false
pytorch
https://paperswithcode.com/paper/the-hashed-fractal-key-recovery-hfkr-problem
The Hashed Fractal Key Recovery (HFKR) Problem: From Symbolic Path Inversion to Post-Quantum Cryptographic Keys
2506.04383
https://arxiv.org/abs/2506.04383v1
https://arxiv.org/pdf/2506.04383v1.pdf
https://github.com/drbouke/SPIP
true
true
false
none
https://paperswithcode.com/paper/open-quantum-assembly-language
Open Quantum Assembly Language
1707.03429
http://arxiv.org/abs/1707.03429v2
http://arxiv.org/pdf/1707.03429v2.pdf
https://github.com/pnnl/qasmtrans
false
false
true
none
https://paperswithcode.com/paper/agentic-reward-modeling-integrating-human
Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems
2502.19328
https://arxiv.org/abs/2502.19328v1
https://arxiv.org/pdf/2502.19328v1.pdf
https://github.com/thu-keg/agentic-reward-modeling
true
true
true
none
https://paperswithcode.com/paper/dynamical-streams-in-the-local-stellar-halo
Dynamical streams in the local stellar halo
2503.02926
https://arxiv.org/abs/2503.02926v1
https://arxiv.org/pdf/2503.02926v1.pdf
https://github.com/adllmr/resonances
true
false
false
none
https://paperswithcode.com/paper/analyzing-the-safety-of-japanese-large
Analyzing the Safety of Japanese Large Language Models in Stereotype-Triggering Prompts
2503.01947
https://arxiv.org/abs/2503.01947v2
https://arxiv.org/pdf/2503.01947v2.pdf
https://github.com/momijiro/stereotype_japanese_llm
true
false
false
none
https://paperswithcode.com/paper/2503-00332
Investigating the contribution of terrain-following coordinates and conservation schemes in AI-driven precipitation forecasts
2503.00332
https://arxiv.org/abs/2503.00332v2
https://arxiv.org/pdf/2503.00332v2.pdf
https://github.com/yingkaisha/CREDIT-sigma-run
true
false
true
pytorch
https://paperswithcode.com/paper/query-expansion-by-prompting-large-language
Query Expansion by Prompting Large Language Models
2305.03653
https://arxiv.org/abs/2305.03653v1
https://arxiv.org/pdf/2305.03653v1.pdf
https://github.com/aken12/LLM-based-QE-fails
false
false
true
none
https://paperswithcode.com/paper/fundamental-limitations-of-high-contrast
Fundamental limitations of high contrast imaging set by small sample statistics
1407.2247
https://arxiv.org/abs/1407.2247v1
https://arxiv.org/pdf/1407.2247v1.pdf
https://github.com/markusbonse/applefy
false
false
true
none
https://paperswithcode.com/paper/chexworld-exploring-image-world-modeling-for
CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning
2504.13820
https://arxiv.org/abs/2504.13820v1
https://arxiv.org/pdf/2504.13820v1.pdf
https://github.com/LeapLabTHU/CheXWorld
true
true
true
pytorch
https://paperswithcode.com/paper/an-overview-of-the-data-loader-landscape
An Overview of the Data-Loader Landscape: Comparative Performance Analysis
2209.13705
https://arxiv.org/abs/2209.13705v1
https://arxiv.org/pdf/2209.13705v1.pdf
https://github.com/smartnets/dataloader-benchmarks
true
true
false
pytorch
https://paperswithcode.com/paper/fast-multichannel-source-separation-based-on
Fast Multichannel Source Separation Based on Jointly Diagonalizable Spatial Covariance Matrices
1903.03237
http://arxiv.org/abs/1903.03237v1
http://arxiv.org/pdf/1903.03237v1.pdf
https://github.com/tky823/ssspy
false
false
true
none
https://paperswithcode.com/paper/channel-attentive-graph-neural-networks
Channel-Attentive Graph Neural Networks
2503.00578
https://arxiv.org/abs/2503.00578v1
https://arxiv.org/pdf/2503.00578v1.pdf
https://github.com/allab-boun/chat-gnn
true
true
false
pytorch
https://paperswithcode.com/paper/an-aspect-performance-aware-hypergraph-neural
An Aspect Performance-aware Hypergraph Neural Network for Review-based Recommendation
2501.15429
https://arxiv.org/abs/2501.15429v1
https://arxiv.org/pdf/2501.15429v1.pdf
https://github.com/dianziliu/aph
true
true
false
pytorch
https://paperswithcode.com/paper/measurement-of-llm-s-philosophies-of-human
Measurement of LLM's Philosophies of Human Nature
2504.02304
https://arxiv.org/abs/2504.02304v1
https://arxiv.org/pdf/2504.02304v1.pdf
https://github.com/kodenii/m-phns
true
true
true
none
https://paperswithcode.com/paper/framework-to-automatically-determine-the
Framework to Automatically Determine the Quality of Open Data Catalogs
2307.15464
https://arxiv.org/abs/2307.15464v7
https://arxiv.org/pdf/2307.15464v7.pdf
https://github.com/jorge-martinez-gil/dataq
true
true
true
none
https://paperswithcode.com/paper/informed-greedy-algorithm-for-scalable
Informed Greedy Algorithm for Scalable Bayesian Network Fusion via Minimum Cut Analysis
2504.00467
https://arxiv.org/abs/2504.00467v1
https://arxiv.org/pdf/2504.00467v1.pdf
https://github.com/ptorrijos99/bayesfl
false
false
true
none
https://paperswithcode.com/paper/cross-species-data-integration-for-enhanced
Cross-Species Data Integration for Enhanced Layer Segmentation in Kidney Pathology
2408.09278
https://arxiv.org/abs/2408.09278v2
https://arxiv.org/pdf/2408.09278v2.pdf
https://github.com/hrlblab/layer_segmentation
true
true
false
pytorch
https://paperswithcode.com/paper/testing-early-physics-solutions-to-the-hubble
A flexible parameterization to test early physics solutions to the Hubble tension with future CMB data
2410.16185
https://arxiv.org/abs/2410.16185v2
https://arxiv.org/pdf/2410.16185v2.pdf
https://github.com/raphkou/camb
true
true
true
none
https://paperswithcode.com/paper/hubble-constant-by-natural-selection
Hubble constant by natural selection: Evolution chips in the Hubble tension
2212.02203
https://arxiv.org/abs/2212.02203v3
https://arxiv.org/pdf/2212.02203v3.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/dark-energy-by-natural-evolution-constraining
Dark energy by natural evolution: Constraining dark energy using Approximate Bayesian Computation
2211.05482
https://arxiv.org/abs/2211.05482v3
https://arxiv.org/pdf/2211.05482v3.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/tadpole-cosmology-self-tuning-without
Tadpole Cosmology: Self Tuning Without Degeneracy
2202.08672
https://arxiv.org/abs/2202.08672v2
https://arxiv.org/pdf/2202.08672v2.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/dressed-black-holes-in-the-new-tensor-vector
Dressed black holes in the new tensor-vector-scalar theory
2202.08460
https://arxiv.org/abs/2202.08460v3
https://arxiv.org/pdf/2202.08460v3.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/parametric-and-nonparametric-methods-hint
Parametric and nonparametric methods hint dark energy evolution
2111.08289
https://arxiv.org/abs/2111.08289v3
https://arxiv.org/pdf/2111.08289v3.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/inflationary-quantum-dynamics-and
Inflationary quantum dynamics and backreaction using a classical-quantum correspondence
2109.08508
https://arxiv.org/abs/2109.08508v2
https://arxiv.org/pdf/2109.08508v2.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/gravitational-wave-signatures-from-dark
Gravitational wave signatures from dark sector interactions
2103.02311
https://arxiv.org/abs/2103.02311v2
https://arxiv.org/pdf/2103.02311v2.pdf
https://github.com/reggiebernardo/notebooks
true
true
true
none
https://paperswithcode.com/paper/flex-net-sim-a-lightly-manual
Flex Net Sim: A Lightly Manual
2105.02762
https://arxiv.org/abs/2105.02762v1
https://arxiv.org/pdf/2105.02762v1.pdf
https://gitlab.com/DaniloBorquez/flex-net-sim
true
true
true
none
https://paperswithcode.com/paper/gaussian-rank-verification
Gaussian Rank Verification
2501.14142
https://arxiv.org/abs/2501.14142v2
https://arxiv.org/pdf/2501.14142v2.pdf
https://github.com/jeremy-goldwasser/gaussian-rankings
true
true
false
none
https://paperswithcode.com/paper/estimating-or-propagating-gradients-through-1
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
1308.3432
http://arxiv.org/abs/1308.3432v1
http://arxiv.org/pdf/1308.3432v1.pdf
https://github.com/mcmahon-lab/Single-Photon-Detection-Neural-Networks
false
false
true
pytorch
https://paperswithcode.com/paper/quantum-noise-limited-optical-neural-networks
Quantum-limited stochastic optical neural networks operating at a few quanta per activation
2307.15712
https://arxiv.org/abs/2307.15712v2
https://arxiv.org/pdf/2307.15712v2.pdf
https://github.com/mcmahon-lab/Single-Photon-Detection-Neural-Networks
true
false
true
pytorch
https://paperswithcode.com/paper/evorl-a-gpu-accelerated-framework-for
EvoRL: A GPU-accelerated Framework for Evolutionary Reinforcement Learning
2501.15129
https://arxiv.org/abs/2501.15129v2
https://arxiv.org/pdf/2501.15129v2.pdf
https://github.com/emi-group/evorl
true
true
true
jax
https://paperswithcode.com/paper/learning-transferable-visual-models-from
Learning Transferable Visual Models From Natural Language Supervision
2103.00020
https://arxiv.org/abs/2103.00020v1
https://arxiv.org/pdf/2103.00020v1.pdf
https://github.com/taited/clip-score
false
false
true
pytorch
https://paperswithcode.com/paper/autoagent-a-fully-automated-and-zero-code
AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents
2502.05957
https://arxiv.org/abs/2502.05957v2
https://arxiv.org/pdf/2502.05957v2.pdf
https://github.com/hkuds/auto-deep-research
false
false
true
none
https://paperswithcode.com/paper/gen3c-3d-informed-world-consistent-video
GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control
2503.03751
https://arxiv.org/abs/2503.03751v1
https://arxiv.org/pdf/2503.03751v1.pdf
https://github.com/nv-tlabs/GEN3C
true
false
true
pytorch
https://paperswithcode.com/paper/the-dynamics-of-inducible-genetic-circuits
The Dynamics of Inducible Genetic Circuits
2505.07053
https://arxiv.org/abs/2505.07053v1
https://arxiv.org/pdf/2505.07053v1.pdf
https://github.com/RPGroup-PBoC/2025_inducers
true
false
false
none
https://paperswithcode.com/paper/slow-transition-to-low-dimensional-chaos-in
Slow Transition to Low-Dimensional Chaos in Heavy-Tailed Recurrent Neural Networks
2505.09816
https://arxiv.org/abs/2505.09816v1
https://arxiv.org/pdf/2505.09816v1.pdf
https://github.com/alleninstitute/heavyrnn_public
true
true
true
jax
https://paperswithcode.com/paper/simbev-a-synthetic-multi-task-multi-sensor
SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset
2502.01894
https://arxiv.org/abs/2502.01894v2
https://arxiv.org/pdf/2502.01894v2.pdf
https://github.com/goodarzmehr/simbev
true
true
true
pytorch
https://paperswithcode.com/paper/one-diffusion-step-to-real-world-super
One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation
2502.01993
https://arxiv.org/abs/2502.01993v1
https://arxiv.org/pdf/2502.01993v1.pdf
https://github.com/jianzeli-114/fluxsr
true
true
true
none
https://paperswithcode.com/paper/dynamic-markov-blanket-detection-for
Dynamic Markov Blanket Detection for Macroscopic Physics Discovery
2502.21217
https://arxiv.org/abs/2502.21217v1
https://arxiv.org/pdf/2502.21217v1.pdf
https://github.com/bayesianempirimancer/pyDMBD
true
false
false
pytorch
https://paperswithcode.com/paper/mline-vins-robust-monocular-visual-inertial
MLINE-VINS: Robust Monocular Visual-Inertial SLAM With Flow Manhattan and Line Features
2503.01571
https://arxiv.org/abs/2503.01571v1
https://arxiv.org/pdf/2503.01571v1.pdf
https://github.com/lihaoy-ux/mline-vins
true
true
false
none
https://paperswithcode.com/paper/don-t-shake-the-wheel-momentum-aware-planning
Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Driving
2503.03125
https://arxiv.org/abs/2503.03125v3
https://arxiv.org/pdf/2503.03125v3.pdf
https://github.com/adept-thu/momad
true
true
true
pytorch
https://paperswithcode.com/paper/bottom-up-generation-of-verilog-designs-for
Bottom-Up Generation of Verilog Designs for Testing EDA Tools
2504.06295
https://arxiv.org/abs/2504.06295v1
https://arxiv.org/pdf/2504.06295v1.pdf
https://github.com/lac-dcc/chimera
true
true
true
none
https://paperswithcode.com/paper/when-heterophily-meets-heterogeneous-graphs
When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning
2409.00687
https://arxiv.org/abs/2409.00687v1
https://arxiv.org/pdf/2409.00687v1.pdf
https://github.com/zxlearningdeep/latgrl
true
true
true
pytorch
https://paperswithcode.com/paper/automatic-database-description-generation-for
Automatic database description generation for Text-to-SQL
2502.20657
https://arxiv.org/abs/2502.20657v1
https://arxiv.org/pdf/2502.20657v1.pdf
https://github.com/xgenerationlab/xiyan-dbdescgen
true
true
true
none
https://paperswithcode.com/paper/union-of-experts-adapting-hierarchical
Union of Experts: Adapting Hierarchical Routing to Equivalently Decomposed Transformer
2503.02495
https://arxiv.org/abs/2503.02495v1
https://arxiv.org/pdf/2503.02495v1.pdf
https://github.com/yujiaoyang-work/uoe
true
true
true
pytorch
https://paperswithcode.com/paper/masa-sr-matching-acceleration-and-spatial
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution
2106.02299
https://arxiv.org/abs/2106.02299v1
https://arxiv.org/pdf/2106.02299v1.pdf
https://github.com/xuefusiji/badrefsr
false
false
true
pytorch
https://paperswithcode.com/paper/learning-texture-transformer-network-for-1
Learning Texture Transformer Network for Image Super-Resolution
2006.04139
https://arxiv.org/abs/2006.04139v2
https://arxiv.org/pdf/2006.04139v2.pdf
https://github.com/xuefusiji/badrefsr
false
false
true
pytorch
https://paperswithcode.com/paper/a-foundation-model-for-human-ai-collaboration
A foundation model for human-AI collaboration in medical literature mining
2501.16255
https://arxiv.org/abs/2501.16255v1
https://arxiv.org/pdf/2501.16255v1.pdf
https://github.com/pat-jj/deepretrieval
false
false
true
pytorch
https://paperswithcode.com/paper/finding-good-views-of-electrocardiogram
Finding "Good Views" of Electrocardiogram Signals for Inferring Abnormalities in Cardiac Condition
2411.17702
https://arxiv.org/abs/2411.17702v1
https://arxiv.org/pdf/2411.17702v1.pdf
https://github.com/mandiehyewon/goodviews_ecg
true
true
true
pytorch
https://paperswithcode.com/paper/clocs-contrastive-learning-of-cardiac-signals
CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients
2005.13249
https://arxiv.org/abs/2005.13249v3
https://arxiv.org/pdf/2005.13249v3.pdf
https://github.com/mandiehyewon/goodviews_ecg
false
false
true
pytorch
https://paperswithcode.com/paper/co-evolving-llm-coder-and-unit-tester-via
Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning
2506.03136
https://arxiv.org/abs/2506.03136v1
https://arxiv.org/pdf/2506.03136v1.pdf
https://github.com/gen-verse/cure
true
true
true
pytorch
https://paperswithcode.com/paper/metaspatial-reinforcing-3d-spatial-reasoning
MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse
2503.18470
https://arxiv.org/abs/2503.18470v1
https://arxiv.org/pdf/2503.18470v1.pdf
https://github.com/pzyseere/metaspatial
true
true
true
pytorch
https://paperswithcode.com/paper/transma-an-explainable-multi-modal-deep
TransMA: an explainable multi-modal deep learning model for predicting properties of ionizable lipid nanoparticles in mRNA delivery
2407.05736
https://arxiv.org/abs/2407.05736v1
https://arxiv.org/pdf/2407.05736v1.pdf
https://github.com/wklix/transma
true
true
false
pytorch
https://paperswithcode.com/paper/error-span-annotation-a-balanced-approach-for
Error Span Annotation: A Balanced Approach for Human Evaluation of Machine Translation
2406.11580
https://arxiv.org/abs/2406.11580v2
https://arxiv.org/pdf/2406.11580v2.pdf
https://github.com/appraisedev/appraise
false
false
true
none
https://paperswithcode.com/paper/paragraph-antibody-paratope-prediction-using
Paragraph—antibody paratope prediction using graph neural networks with minimal feature vectors
null
https://academic.oup.com/bioinformatics/article/39/1/btac732/6825310
https://academic.oup.com/bioinformatics/article-pdf/39/1/btac732/48448850/btac732.pdf
https://github.com/oxpig/Paragraph
false
true
false
pytorch
https://paperswithcode.com/paper/heterogeneity-in-sectoral-production-and-the
Heterogeneity in Sectoral Production and the Macro Effect of Sectoral Shocks
2502.07896
https://arxiv.org/abs/2502.07896v2
https://arxiv.org/pdf/2502.07896v2.pdf
https://github.com/jacobgosselin/HeterogeousSectoralProduction
true
false
true
none
https://paperswithcode.com/paper/symmcd-symmetry-preserving-crystal-generation
SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models
2502.03638
https://arxiv.org/abs/2502.03638v3
https://arxiv.org/pdf/2502.03638v3.pdf
https://github.com/sibasmarak/SymmCD
true
false
false
pytorch