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

Dataset card Data Studio Files
xet
Community
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https://paperswithcode.com/paper/semisupervised-neural-proto-language
Semisupervised Neural Proto-Language Reconstruction
2406.05930
https://arxiv.org/abs/2406.05930v2
https://arxiv.org/pdf/2406.05930v2.pdf
https://github.com/cmu-llab/dpd
true
true
false
pytorch
https://paperswithcode.com/paper/band-biomedical-alert-news-dataset
BAND: Biomedical Alert News Dataset
2305.14480
https://arxiv.org/abs/2305.14480v2
https://arxiv.org/pdf/2305.14480v2.pdf
https://github.com/fuzihaofzh/band
true
true
true
pytorch
https://paperswithcode.com/paper/adding-conditional-control-to-text-to-image
Adding Conditional Control to Text-to-Image Diffusion Models
2302.05543
https://arxiv.org/abs/2302.05543v3
https://arxiv.org/pdf/2302.05543v3.pdf
https://github.com/Francis-Rings/MotionEditor
false
false
true
pytorch
https://paperswithcode.com/paper/high-resolution-image-synthesis-with-latent
High-Resolution Image Synthesis with Latent Diffusion Models
2112.10752
https://arxiv.org/abs/2112.10752v2
https://arxiv.org/pdf/2112.10752v2.pdf
https://github.com/Francis-Rings/MotionEditor
false
false
true
pytorch
https://paperswithcode.com/paper/p-winds-an-open-source-python-code-to-model
p-winds: an open-source Python code to model planetary outflows and upper atmospheres
2111.11370
https://arxiv.org/abs/2111.11370v3
https://arxiv.org/pdf/2111.11370v3.pdf
https://github.com/ladsantos/p-winds
true
true
true
none
https://paperswithcode.com/paper/3d-voxel-maps-to-2d-occupancy-maps-for
Voxel Map to Occupancy Map Conversion Using Free Space Projection for Efficient Map Representation for Aerial and Ground Robots
2406.07270
https://arxiv.org/abs/2406.07270v2
https://arxiv.org/pdf/2406.07270v2.pdf
https://github.com/ltu-rai/map-conversion-3d-voxel-map-to-2d-occupancy-map
true
true
true
none
https://paperswithcode.com/paper/eccos-efficient-capability-and-cost
OmniRouter: Budget and Performance Controllable Multi-LLM Routing
2502.20576
https://arxiv.org/abs/2502.20576v5
https://arxiv.org/pdf/2502.20576v5.pdf
https://github.com/agiresearch/aios
true
true
false
none
https://paperswithcode.com/paper/approximate-nearest-neighbor-search-with
Approximate Nearest Neighbor Search with Window Filters
2402.00943
https://arxiv.org/abs/2402.00943v2
https://arxiv.org/pdf/2402.00943v2.pdf
https://github.com/joshengels/rangefilteredann
true
true
true
none
https://paperswithcode.com/paper/an-interventional-perspective-on
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis
2311.18048
https://arxiv.org/abs/2311.18048v2
https://arxiv.org/pdf/2311.18048v2.pdf
https://github.com/meszarosanna/rule_extrapolation
false
false
true
pytorch
https://paperswithcode.com/paper/machine-learning-methods-for-postprocessing
Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison
2106.09512
https://arxiv.org/abs/2106.09512v1
https://arxiv.org/pdf/2106.09512v1.pdf
https://github.com/benediktschulz/paper_pp_wind_gusts
true
true
true
none
https://paperswithcode.com/paper/physics-informed-distillation-for-diffusion
Physics Informed Distillation for Diffusion Models
2411.08378
https://arxiv.org/abs/2411.08378v1
https://arxiv.org/pdf/2411.08378v1.pdf
https://github.com/pantheon5100/pid_diffusion
true
true
false
pytorch
https://paperswithcode.com/paper/review-of-deep-learning-models-for-crypto
Review of deep learning models for crypto price prediction: implementation and evaluation
2405.11431
https://arxiv.org/abs/2405.11431v2
https://arxiv.org/pdf/2405.11431v2.pdf
https://github.com/sydney-machine-learning/deeplearning-crypto
true
true
true
tf
https://paperswithcode.com/paper/fast-and-accurate-algorithms-to-calculate
On the accurate computation of expected modularity in probabilistic networks
2408.07161
https://arxiv.org/abs/2408.07161v3
https://arxiv.org/pdf/2408.07161v3.pdf
https://github.com/uuinfolab/Expected_Modularity_Calculation_in_ProbabilisticGraph
true
false
false
none
https://paperswithcode.com/paper/cumulative-differences-between-subpopulations-1
Cumulative differences between subpopulations versus body mass index in the Behavioral Risk Factor Surveillance System data
2411.07399
https://arxiv.org/abs/2411.07399v1
https://arxiv.org/pdf/2411.07399v1.pdf
https://github.com/facebookresearch/cumbiostats
true
false
false
none
https://paperswithcode.com/paper/on-the-intractability-of-chaotic-symbolic
On the Intractability of Chaotic Symbolic Walks: Toward a Non-Algebraic Post-Quantum Hardness Assumption
2505.22644
https://arxiv.org/abs/2505.22644v1
https://arxiv.org/pdf/2505.22644v1.pdf
https://github.com/drbouke/SPIP
true
false
false
none
https://paperswithcode.com/paper/gaming-tool-preferences-in-agentic-llms
Gaming Tool Preferences in Agentic LLMs
2505.18135
https://arxiv.org/abs/2505.18135v1
https://arxiv.org/pdf/2505.18135v1.pdf
https://github.com/kazemf78/Gaming-Tool-Preferences
true
false
true
none
https://paperswithcode.com/paper/spatial-temporal-cross-view-contrastive-pre
Spatial-Temporal Cross-View Contrastive Pre-training for Check-in Sequence Representation Learning
2407.15899
https://arxiv.org/abs/2407.15899v3
https://arxiv.org/pdf/2407.15899v3.pdf
https://github.com/letiangong/stccr
true
true
false
pytorch
https://paperswithcode.com/paper/a-simple-randomization-technique-for-1
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning
1910.05396
https://arxiv.org/abs/1910.05396v3
https://arxiv.org/pdf/1910.05396v3.pdf
https://github.com/1hb6s7t/Rand-conv
false
false
false
mindspore
https://paperswithcode.com/paper/wider-networks-learn-better-features
Wider Networks Learn Better Features
1909.11572
https://arxiv.org/abs/1909.11572v1
https://arxiv.org/pdf/1909.11572v1.pdf
https://github.com/iantheconway/network_width_and_transfer_learning
false
false
true
tf
https://paperswithcode.com/paper/instruction-guided-bullet-point-summarization
Instruction-Guided Bullet Point Summarization of Long Financial Earnings Call Transcripts
2405.06669
https://arxiv.org/abs/2405.06669v1
https://arxiv.org/pdf/2405.06669v1.pdf
https://github.com/subhendukhatuya/FLAN-FinBPS
true
false
false
pytorch
https://paperswithcode.com/paper/on-a-new-family-of-weighted-gaussian
On a new family of weighted Gaussian processes: an application to bat telemetry data
2405.19903
https://arxiv.org/abs/2405.19903v1
https://arxiv.org/pdf/2405.19903v1.pdf
https://github.com/joseramirezgonzalez/f-wsfBm
true
true
false
none
https://paperswithcode.com/paper/a-structured-l-bfgs-method-with-diagonal
A structured L-BFGS method with diagonal scaling and its application to image registration
2405.19834
https://arxiv.org/abs/2405.19834v3
https://arxiv.org/pdf/2405.19834v3.pdf
https://github.com/hariagr/slbfgs
true
true
false
none
https://paperswithcode.com/paper/distributed-online-planning-for-min-max
Distributed Online Planning for Min-Max Problems in Networked Markov Games
2405.19570
https://arxiv.org/abs/2405.19570v1
https://arxiv.org/pdf/2405.19570v1.pdf
https://github.com/alextzik/distr_online_maxmin_markov_game
true
true
false
none
https://paperswithcode.com/paper/lalonde-1986-after-nearly-four-decades
Comparing Experimental and Nonexperimental Methods: What Lessons Have We Learned Four Decades After LaLonde (1986)?
2406.00827
https://arxiv.org/abs/2406.00827v3
https://arxiv.org/pdf/2406.00827v3.pdf
https://github.com/xuyiqing/lalonde
true
true
true
none
https://paperswithcode.com/paper/motionfollower-editing-video-motion-via
MotionFollower: Editing Video Motion via Lightweight Score-Guided Diffusion
2405.20325
https://arxiv.org/abs/2405.20325v1
https://arxiv.org/pdf/2405.20325v1.pdf
https://github.com/Francis-Rings/MotionFollower
true
false
true
pytorch
https://paperswithcode.com/paper/lmrpa-large-language-model-driven-efficient
LMRPA: Large Language Model-Driven Efficient Robotic Process Automation for OCR
2412.18063
https://arxiv.org/abs/2412.18063v2
https://arxiv.org/pdf/2412.18063v2.pdf
https://github.com/mad-sam22/erpa-ocr
true
true
false
none
https://paperswithcode.com/paper/seqmia-sequential-metric-based-membership
SeqMIA: Sequential-Metric Based Membership Inference Attack
2407.15098
https://arxiv.org/abs/2407.15098v1
https://arxiv.org/pdf/2407.15098v1.pdf
https://github.com/AIPAG/SeqMIA
true
false
true
pytorch
https://paperswithcode.com/paper/unigen-universal-domain-generalization-for
UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation
2405.01022
https://arxiv.org/abs/2405.01022v3
https://arxiv.org/pdf/2405.01022v3.pdf
https://github.com/c-juhwan/unigen
true
true
true
pytorch
https://paperswithcode.com/paper/recurrent-neural-goodness-of-fit-test-for
Recurrent Neural Goodness-of-Fit Test for Time Series
2410.13986
https://arxiv.org/abs/2410.13986v3
https://arxiv.org/pdf/2410.13986v3.pdf
https://github.com/aoranzhangmia/neural-gof-time
true
true
true
pytorch
https://paperswithcode.com/paper/softmax-attention-with-constant-cost-per
Softmax Attention with Constant Cost per Token
2404.05843
https://arxiv.org/abs/2404.05843v2
https://arxiv.org/pdf/2404.05843v2.pdf
https://github.com/glassroom/heinsen_attention
true
true
true
pytorch
https://paperswithcode.com/paper/slimer-it-zero-shot-ner-on-italian-language
SLIMER-IT: Zero-Shot NER on Italian Language
2409.15933
https://arxiv.org/abs/2409.15933v2
https://arxiv.org/pdf/2409.15933v2.pdf
https://github.com/andrewzamai/slimer_it
true
true
true
none
https://paperswithcode.com/paper/opponent-shaping-for-antibody-development
ADIOS: Antibody Development via Opponent Shaping
2409.10588
https://arxiv.org/abs/2409.10588v8
https://arxiv.org/pdf/2409.10588v8.pdf
https://github.com/olakalisz/antibody-shapers
true
true
true
jax
https://paperswithcode.com/paper/foundation-models-for-amodal-video-instance
Foundation Models for Amodal Video Instance Segmentation in Automated Driving
2409.14095
https://arxiv.org/abs/2409.14095v1
https://arxiv.org/pdf/2409.14095v1.pdf
https://github.com/ifnspaml/s-amodal
true
true
true
jax
https://paperswithcode.com/paper/fast-randomized-least-squares-solvers-can-be
Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers
2406.03468
https://arxiv.org/abs/2406.03468v2
https://arxiv.org/pdf/2406.03468v2.pdf
https://github.com/eepperly/Stable-Randomized-Least-Squares
true
true
true
none
https://paperswithcode.com/paper/accelerating-ill-conditioned-hankel-matrix
Accelerating Ill-conditioned Hankel Matrix Recovery via Structured Newton-like Descent
2406.07409
https://arxiv.org/abs/2406.07409v2
https://arxiv.org/pdf/2406.07409v2.pdf
https://github.com/caesarcai/HSNLD
true
true
true
none
https://paperswithcode.com/paper/calibrating-car-following-models-via-bayesian
Calibrating Car-Following Models via Bayesian Dynamic Regression
2307.03340
https://arxiv.org/abs/2307.03340v2
https://arxiv.org/pdf/2307.03340v2.pdf
https://github.com/chengyuan-zhang/idm_bayesian_calibration
true
true
true
none
https://paperswithcode.com/paper/disco-might-not-be-funky-random-intelligent
DISCO Might Not Be Funky: Random Intelligent Reflective Surface Configurations That Attack
2310.00687
https://arxiv.org/abs/2310.00687v2
https://arxiv.org/pdf/2310.00687v2.pdf
https://github.com/huanhuan1799/disco-intelligent-reflecting-surfaces-active-channel-aging-for-fully-passive-jamming-attacks
true
true
false
none
https://paperswithcode.com/paper/radial-velocity-and-astrometric-evidence-for
Radial Velocity and Astrometric Evidence for a Close Companion to Betelgeuse
2409.11332
https://arxiv.org/abs/2409.11332v2
https://arxiv.org/pdf/2409.11332v2.pdf
https://github.com/morganemacleod/BetelgeuseLittleFriend
true
false
true
none
https://paperswithcode.com/paper/diagnosing-the-pattern-effect-in-the
A fluctuation-dissipation theorem perspective on radiative responses to temperature perturbations
2408.12585
https://arxiv.org/abs/2408.12585v5
https://arxiv.org/pdf/2408.12585v5.pdf
https://github.com/fabrifalasca/linear-response-and-causal-inference
true
true
true
none
https://paperswithcode.com/paper/coverage-axis-efficient-inner-point-selection
Coverage Axis++: Efficient Inner Point Selection for 3D Shape Skeletonization
2401.12946
https://arxiv.org/abs/2401.12946v7
https://arxiv.org/pdf/2401.12946v7.pdf
https://github.com/frank-zy-dou/coverage_axis
true
true
true
none
https://paperswithcode.com/paper/near-inertial-echoes-of-ageostrophic
Near-inertial echoes of ageostrophic instability in submesoscale filaments
2407.16059
https://arxiv.org/abs/2407.16059v4
https://arxiv.org/pdf/2407.16059v4.pdf
https://github.com/erin-atkinson/filament-instability
true
false
false
none
https://paperswithcode.com/paper/living-in-the-moment-can-large-language
Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?
2406.09072
https://arxiv.org/abs/2406.09072v1
https://arxiv.org/pdf/2406.09072v1.pdf
https://github.com/zhaochen0110/cotempqa
true
true
true
none
https://paperswithcode.com/paper/gaussian-plane-wave-neural-operator-for
Gaussian Plane-Wave Neural Operator for Electron Density Estimation
2402.04278
https://arxiv.org/abs/2402.04278v2
https://arxiv.org/pdf/2402.04278v2.pdf
https://github.com/seongsukim-ml/gpwno
true
true
true
pytorch
https://paperswithcode.com/paper/query-policy-misalignment-in-preference-based
Query-Policy Misalignment in Preference-Based Reinforcement Learning
2305.17400
https://arxiv.org/abs/2305.17400v3
https://arxiv.org/pdf/2305.17400v3.pdf
https://github.com/huxiao09/qpa
true
true
false
none
https://paperswithcode.com/paper/lerac-learning-rate-curriculum
Learning Rate Curriculum
2205.09180
https://arxiv.org/abs/2205.09180v4
https://arxiv.org/pdf/2205.09180v4.pdf
https://github.com/croitorualin/lerac
true
true
false
pytorch
https://paperswithcode.com/paper/chartgemma-visual-instruction-tuning-for
ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild
2407.04172
https://arxiv.org/abs/2407.04172v2
https://arxiv.org/pdf/2407.04172v2.pdf
https://github.com/vis-nlp/chartgemma
true
true
true
pytorch
https://paperswithcode.com/paper/secure-aggregation-is-not-private-against
Secure Aggregation is Not Private Against Membership Inference Attacks
2403.17775
https://arxiv.org/abs/2403.17775v3
https://arxiv.org/pdf/2403.17775v3.pdf
https://github.com/khachoang1412/SecAgg_not_private
true
true
true
none
https://paperswithcode.com/paper/scoping-review-of-active-learning-strategies
Scoping Review of Active Learning Strategies and their Evaluation Environments for Entity Recognition Tasks
2407.03895
https://arxiv.org/abs/2407.03895v1
https://arxiv.org/pdf/2407.03895v1.pdf
https://github.com/philipp-kohl/scoping-review-active-learning-er
true
false
false
none
https://paperswithcode.com/paper/a-detailed-study-of-recurrent-neural-networks
Exploring weight initialization, diversity of solutions, and degradation in recurrent neural networks trained for temporal and decision-making tasks
1906.01094
https://arxiv.org/abs/1906.01094v6
https://arxiv.org/pdf/1906.01094v6.pdf
https://github.com/katejarne/RNN_study_with_keras
true
true
true
tf
https://paperswithcode.com/paper/affectgpt-dataset-and-framework-for
AffectGPT: Dataset and Framework for Explainable Multimodal Emotion Recognition
2407.07653
https://arxiv.org/abs/2407.07653v1
https://arxiv.org/pdf/2407.07653v1.pdf
https://github.com/zeroqiaoba/affectgpt
true
true
false
pytorch
https://paperswithcode.com/paper/hstpromo-internal-proper-motion-kinematics-of
HSTPROMO Internal Proper Motion Kinematics of Dwarf Spheroidal Galaxies: I. Velocity Anisotropy and Dark Matter Cusp Slope of Draco
2407.07769
https://arxiv.org/abs/2407.07769v1
https://arxiv.org/pdf/2407.07769v1.pdf
https://gitlab.com/eduardo-vitral/scalefree
true
true
false
none
https://paperswithcode.com/paper/automated-medical-report-generation-for-ecg
Automated Medical Report Generation for ECG Data: Bridging Medical Text and Signal Processing with Deep Learning
2412.04067
https://arxiv.org/abs/2412.04067v1
https://arxiv.org/pdf/2412.04067v1.pdf
https://git.zib.de/ableich/ecg-comment-generation-public
false
false
false
none
https://paperswithcode.com/paper/deep-domain-adaptation-for-ordinal-regression
Deep Domain Adaptation for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labelled Videos
2008.06392
https://arxiv.org/abs/2008.06392v3
https://arxiv.org/pdf/2008.06392v3.pdf
https://github.com/praveena2j/wsdaor
true
true
false
pytorch
https://paperswithcode.com/paper/video-recap-recursive-captioning-of-hour-long
Video ReCap: Recursive Captioning of Hour-Long Videos
2402.13250
https://arxiv.org/abs/2402.13250v6
https://arxiv.org/pdf/2402.13250v6.pdf
https://github.com/md-mohaiminul/VideoRecap
true
false
true
pytorch
https://paperswithcode.com/paper/feature-characterization-for-profile-surface
Feature Characterization for Profile Surface Texture
2406.06381
https://arxiv.org/abs/2406.06381v4
https://arxiv.org/pdf/2406.06381v4.pdf
https://github.com/mts-public/feature-characterization-for-profile-surface-texture
true
false
true
none
https://paperswithcode.com/paper/on-the-robustness-of-global-feature-effect
On the Robustness of Global Feature Effect Explanations
2406.09069
https://arxiv.org/abs/2406.09069v1
https://arxiv.org/pdf/2406.09069v1.pdf
https://github.com/hbaniecki/robust-feature-effects
true
true
true
pytorch
https://paperswithcode.com/paper/tofu-a-task-of-fictitious-unlearning-for-llms
TOFU: A Task of Fictitious Unlearning for LLMs
2401.06121
https://arxiv.org/abs/2401.06121v1
https://arxiv.org/pdf/2401.06121v1.pdf
https://github.com/ucsb-nlp-chang/uld
false
false
true
pytorch
https://paperswithcode.com/paper/differentiable-programming-for-differential
Differentiable Programming for Differential Equations: A Review
2406.09699
https://arxiv.org/abs/2406.09699v1
https://arxiv.org/pdf/2406.09699v1.pdf
https://github.com/ODINN-SciML/DiffEqSensitivity-Review
true
false
true
jax
https://paperswithcode.com/paper/cryptoformaleval-integrating-llms-and-formal
CryptoFormalEval: Integrating LLMs and Formal Verification for Automated Cryptographic Protocol Vulnerability Detection
2411.13627
https://arxiv.org/abs/2411.13627v1
https://arxiv.org/pdf/2411.13627v1.pdf
https://github.com/cristian-curaba/cryptoformaleval
true
true
false
none
https://paperswithcode.com/paper/negative-yields-positive-unified-dual-path
Enhancing Vision-Language Few-Shot Adaptation with Negative Learning
2403.12964
https://arxiv.org/abs/2403.12964v2
https://arxiv.org/pdf/2403.12964v2.pdf
https://github.com/zhangce01/simnl
true
true
true
pytorch
https://paperswithcode.com/paper/swin-smt-global-sequential-modeling-in-3d
Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation
2407.07514
https://arxiv.org/abs/2407.07514v1
https://arxiv.org/pdf/2407.07514v1.pdf
https://github.com/mi2datalab/swinsmt
true
true
true
pytorch
https://paperswithcode.com/paper/compressed-multi-task-embeddings-for-data
Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling
2403.17886
https://arxiv.org/abs/2403.17886v5
https://arxiv.org/pdf/2403.17886v5.pdf
https://github.com/ibm/neural-embedding-compression
true
true
true
pytorch
https://paperswithcode.com/paper/recursive-visual-programming
Recursive Visual Programming
2312.02249
https://arxiv.org/abs/2312.02249v2
https://arxiv.org/pdf/2312.02249v2.pdf
https://github.com/para-lost/rvp
true
true
true
pytorch
https://paperswithcode.com/paper/mapx-an-explainable-model-agnostic-framework
MAPX: An explainable model-agnostic framework for the detection of false information on social media networks
2409.08522
https://arxiv.org/abs/2409.08522v1
https://arxiv.org/pdf/2409.08522v1.pdf
https://github.com/scondran/mapx_framework
true
true
false
none
https://paperswithcode.com/paper/crosspyramid-neural-ordinary-differential
SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series
2212.03560
https://arxiv.org/abs/2212.03560v3
https://arxiv.org/pdf/2212.03560v3.pdf
https://github.com/ftoonabushaqra/seqlink
true
true
false
pytorch
https://paperswithcode.com/paper/protosam-one-shot-medical-image-segmentation
ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models
2407.07042
https://arxiv.org/abs/2407.07042v2
https://arxiv.org/pdf/2407.07042v2.pdf
https://github.com/levayz/protosam
true
true
true
pytorch
https://paperswithcode.com/paper/attention-is-all-you-need
Attention Is All You Need
1706.03762
https://arxiv.org/abs/1706.03762v7
https://arxiv.org/pdf/1706.03762v7.pdf
https://github.com/pwc-1/Paper-9/tree/main/4/Translation-Invariant/model
false
false
false
mindspore
https://paperswithcode.com/paper/self-recognition-in-language-models
Self-Recognition in Language Models
2407.06946
https://arxiv.org/abs/2407.06946v2
https://arxiv.org/pdf/2407.06946v2.pdf
https://github.com/trdavidson/self-recognition
true
true
true
none
https://paperswithcode.com/paper/benchmarking-deep-learning-and-vision
Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation
2506.21444
https://arxiv.org/abs/2506.21444v1
https://arxiv.org/pdf/2506.21444v1.pdf
https://github.com/deepmicroscopy/ami-br_benchmark
true
true
true
pytorch
https://paperswithcode.com/paper/redesigning-graph-filter-based-gnns-to-relax
Redesigning graph filter-based GNNs to relax the homophily assumption
2409.08676
https://arxiv.org/abs/2409.08676v1
https://arxiv.org/pdf/2409.08676v1.pdf
https://github.com/reysam93/adaptive_agg_gcn
true
false
true
pytorch
https://paperswithcode.com/paper/tiktag-breaking-arm-s-memory-tagging
TikTag: Breaking ARM's Memory Tagging Extension with Speculative Execution
2406.08719
https://arxiv.org/abs/2406.08719v1
https://arxiv.org/pdf/2406.08719v1.pdf
https://github.com/compsec-snu/tiktag
true
true
true
none
https://paperswithcode.com/paper/defect-spectrum-a-granular-look-of-large
Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics
2310.17316
https://arxiv.org/abs/2310.17316v5
https://arxiv.org/pdf/2310.17316v5.pdf
https://github.com/EnVision-Research/Defect_Spectrum
true
false
true
pytorch
https://paperswithcode.com/paper/mgtbench-benchmarking-machine-generated-text
MGTBench: Benchmarking Machine-Generated Text Detection
2303.14822
https://arxiv.org/abs/2303.14822v3
https://arxiv.org/pdf/2303.14822v3.pdf
https://github.com/kinit-sk/imgtb
false
false
true
pytorch
https://paperswithcode.com/paper/inverse-scene-text-removal
Inverse Scene Text Removal
2506.21002
https://arxiv.org/abs/2506.21002v1
https://arxiv.org/pdf/2506.21002v1.pdf
https://github.com/takumi-yoshimatsu/istr
true
true
false
none
https://paperswithcode.com/paper/neural-collapse-in-multi-label-learning-with
Neural Collapse in Multi-label Learning with Pick-all-label Loss
2310.15903
https://arxiv.org/abs/2310.15903v4
https://arxiv.org/pdf/2310.15903v4.pdf
https://github.com/heimine/nc_mlab
true
true
true
pytorch
https://paperswithcode.com/paper/live-video-captioning
Live Video Captioning
2406.14206
https://arxiv.org/abs/2406.14206v1
https://arxiv.org/pdf/2406.14206v1.pdf
https://github.com/gramuah/lvc
true
true
true
none
https://paperswithcode.com/paper/definition-generation-for-lexical-semantic
Definition generation for lexical semantic change detection
2406.14167
https://arxiv.org/abs/2406.14167v2
https://arxiv.org/pdf/2406.14167v2.pdf
https://github.com/ltgoslo/Definition-generation-for-LSCD
true
true
true
none
https://paperswithcode.com/paper/self-explainable-temporal-graph-networks
Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck
2406.13214
https://arxiv.org/abs/2406.13214v1
https://arxiv.org/pdf/2406.13214v1.pdf
https://github.com/sang-woo-seo/TGIB
true
false
false
pytorch
https://paperswithcode.com/paper/ensembles-of-probabilistic-regression-trees
Ensembles of Probabilistic Regression Trees
2406.14033
https://arxiv.org/abs/2406.14033v1
https://arxiv.org/pdf/2406.14033v1.pdf
https://gitlab.com/sami.kh/pr-tree
true
false
false
none
https://paperswithcode.com/paper/sub2full-split-spectrum-to-boost-oct
Sub2Full: split spectrum to boost OCT despeckling without clean data
2401.10128
https://arxiv.org/abs/2401.10128v1
https://arxiv.org/pdf/2401.10128v1.pdf
https://github.com/MindSpore-scientific/code-2/tree/main/Sub2Full-OCT-Denoising
false
false
false
mindspore
https://paperswithcode.com/paper/real-time-single-image-and-video-super
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
1609.05158
http://arxiv.org/abs/1609.05158v2
http://arxiv.org/pdf/1609.05158v2.pdf
https://github.com/pwc-1/Paper-9/tree/main/7/pixelshuffle1d
false
false
false
mindspore
https://paperswithcode.com/paper/diffo-single-step-diffusion-for-image
DiffO: Single-step Diffusion for Image Compression at Ultra-Low Bitrates
2506.16572
https://arxiv.org/abs/2506.16572v1
https://arxiv.org/pdf/2506.16572v1.pdf
https://github.com/freemasti/diffo
true
true
false
none
https://paperswithcode.com/paper/incoder-a-generative-model-for-code-infilling
InCoder: A Generative Model for Code Infilling and Synthesis
2204.05999
https://arxiv.org/abs/2204.05999v3
https://arxiv.org/pdf/2204.05999v3.pdf
https://github.com/eth-sri/sven
false
false
true
none
https://paperswithcode.com/paper/santacoder-don-t-reach-for-the-stars
SantaCoder: don't reach for the stars!
2301.03988
https://arxiv.org/abs/2301.03988v2
https://arxiv.org/pdf/2301.03988v2.pdf
https://github.com/eth-sri/sven
false
false
true
none
https://paperswithcode.com/paper/tokenlearner-what-can-8-learned-tokens-do-for
TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?
2106.11297
https://arxiv.org/abs/2106.11297v4
https://arxiv.org/pdf/2106.11297v4.pdf
https://github.com/pwc-1/Paper-9/tree/main/7/token_learner
false
false
false
mindspore
https://paperswithcode.com/paper/enhancing-split-computing-and-early-exit
Enhancing Split Computing and Early Exit Applications through Predefined Sparsity
2407.11763
https://arxiv.org/abs/2407.11763v1
https://arxiv.org/pdf/2407.11763v1.pdf
https://github.com/intelligolabs/sparsity_sc_ee
true
true
true
none
https://paperswithcode.com/paper/coho-context-sensitive-city-scale
COHO: Context-Sensitive City-Scale Hierarchical Urban Layout Generation
2407.11294
https://arxiv.org/abs/2407.11294v1
https://arxiv.org/pdf/2407.11294v1.pdf
https://github.com/arking1995/coho
true
true
false
none
https://paperswithcode.com/paper/wavecrn-an-efficient-convolutional-recurrent
WaveCRN: An Efficient Convolutional Recurrent Neural Network for End-to-end Speech Enhancement
2004.04098
https://arxiv.org/abs/2004.04098v3
https://arxiv.org/pdf/2004.04098v3.pdf
https://github.com/MindSpore-scientific/code-2/tree/main/WaveCRN-master
false
false
false
mindspore
https://paperswithcode.com/paper/ddfm-denoising-diffusion-model-for-multi
DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion
2303.06840
https://arxiv.org/abs/2303.06840v2
https://arxiv.org/pdf/2303.06840v2.pdf
https://github.com/zhaozixiang1228/mmif-ddfm
true
true
true
pytorch
https://paperswithcode.com/paper/equivariant-multi-modality-image-fusion
Equivariant Multi-Modality Image Fusion
2305.11443
https://arxiv.org/abs/2305.11443v2
https://arxiv.org/pdf/2305.11443v2.pdf
https://github.com/zhaozixiang1228/mmif-ddfm
false
false
true
pytorch
https://paperswithcode.com/paper/development-and-benchmarking-of-multilingual
Development and Benchmarking of Multilingual Code Clone Detector
2409.06176
https://arxiv.org/abs/2409.06176v2
https://arxiv.org/pdf/2409.06176v2.pdf
https://github.com/zhuwq585/MCCD_Benckmarking
true
false
false
none
https://paperswithcode.com/paper/sample-efficiency-matters-a-benchmark-for
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization
2206.12411
https://arxiv.org/abs/2206.12411v2
https://arxiv.org/pdf/2206.12411v2.pdf
https://github.com/yerevann/chemlactica
false
false
true
pytorch
https://paperswithcode.com/paper/genetic-guided-gflownets-advancing-in
Genetic-guided GFlowNets for Sample Efficient Molecular Optimization
2402.05961
https://arxiv.org/abs/2402.05961v4
https://arxiv.org/pdf/2402.05961v4.pdf
https://github.com/yerevann/chemlactica
false
false
true
pytorch
https://paperswithcode.com/paper/beam-enumeration-probabilistic-explainability
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
2309.13957
https://arxiv.org/abs/2309.13957v2
https://arxiv.org/pdf/2309.13957v2.pdf
https://github.com/yerevann/chemlactica
false
false
true
pytorch
https://paperswithcode.com/paper/retrieval-based-controllable-molecule
Retrieval-based Controllable Molecule Generation
2208.11126
https://arxiv.org/abs/2208.11126v3
https://arxiv.org/pdf/2208.11126v3.pdf
https://github.com/yerevann/chemlactica
false
false
true
pytorch
https://paperswithcode.com/paper/small-molecule-optimization-with-large
Small Molecule Optimization with Large Language Models
2407.18897
https://arxiv.org/abs/2407.18897v1
https://arxiv.org/pdf/2407.18897v1.pdf
https://github.com/yerevann/chemlactica
true
true
false
pytorch
https://paperswithcode.com/paper/reshape-dimensions-network-for-speaker-1
Reshape Dimensions Network for Speaker Recognition
2407.18223
https://arxiv.org/abs/2407.18223v2
https://arxiv.org/pdf/2407.18223v2.pdf
https://github.com/IDRnD/ReDimNet
true
false
true
pytorch
https://paperswithcode.com/paper/bayesian-spatiotemporal-wombling
Bayesian Spatiotemporal Wombling
2407.17804
https://arxiv.org/abs/2407.17804v1
https://arxiv.org/pdf/2407.17804v1.pdf
https://github.com/arh926/sptwombling
true
true
true
none
https://paperswithcode.com/paper/a-preprocessing-and-evaluation-toolbox-for
Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets
2405.00604
https://arxiv.org/abs/2405.00604v4
https://arxiv.org/pdf/2405.00604v4.pdf
https://github.com/westny/dronalize
true
true
true
pytorch
https://paperswithcode.com/paper/the-ind-dataset-a-drone-dataset-of
The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections
1911.07602
https://arxiv.org/abs/1911.07602v1
https://arxiv.org/pdf/1911.07602v1.pdf
https://github.com/westny/dronalize
false
false
true
pytorch