Split (1)

train · 300k rows

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/agile-multi-source-free-domain-adaptation	Agile Multi-Source-Free Domain Adaptation	2403.05062	https://arxiv.org/abs/2403.05062v1	https://arxiv.org/pdf/2403.05062v1.pdf	https://github.com/tl-uestc/bi-aten	true	true	true	pytorch
https://paperswithcode.com/paper/sa-solver-stochastic-adams-solver-for-fast	SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models	2309.05019	https://arxiv.org/abs/2309.05019v2	https://arxiv.org/pdf/2309.05019v2.pdf	https://github.com/scxue/SA-Solver	true	false	true	pytorch
https://paperswithcode.com/paper/can-language-models-solve-graph-problems-in	Can Language Models Solve Graph Problems in Natural Language?	2305.10037	https://arxiv.org/abs/2305.10037v3	https://arxiv.org/pdf/2305.10037v3.pdf	https://github.com/Samyu0304/thought-propagation	false	false	true	none
https://paperswithcode.com/paper/neural-message-passing-for-quantum-chemistry	Neural Message Passing for Quantum Chemistry	1704.01212	http://arxiv.org/abs/1704.01212v2	http://arxiv.org/pdf/1704.01212v2.pdf	https://github.com/Samyu0304/thought-propagation	false	false	true	none
https://paperswithcode.com/paper/language-models-are-few-shot-learners	Language Models are Few-Shot Learners	2005.14165	https://arxiv.org/abs/2005.14165v4	https://arxiv.org/pdf/2005.14165v4.pdf	https://github.com/Samyu0304/thought-propagation	false	false	true	none
https://paperswithcode.com/paper/efficient-conditional-diffusion-model-with	Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution	2404.10688	https://arxiv.org/abs/2404.10688v1	https://arxiv.org/pdf/2404.10688v1.pdf	https://github.com/yuan-yutao/ecdp	true	true	false	pytorch
https://paperswithcode.com/paper/sensory-attenuation-develops-as-a-result-of	Emergence of sensory attenuation based upon the free-energy principle	2111.02666	https://arxiv.org/abs/2111.02666v3	https://arxiv.org/pdf/2111.02666v3.pdf	https://github.com/h-idei/pvrnn_sa	true	true	false	pytorch
https://paperswithcode.com/paper/rsmamba-remote-sensing-image-classification	RSMamba: Remote Sensing Image Classification with State Space Model	2403.19654	https://arxiv.org/abs/2403.19654v1	https://arxiv.org/pdf/2403.19654v1.pdf	https://github.com/KyanChen/RSMamba	true	true	true	pytorch
https://paperswithcode.com/paper/wavelet-based-fourier-information-interaction	Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration	2311.16845	https://arxiv.org/abs/2311.16845v1	https://arxiv.org/pdf/2311.16845v1.pdf	https://github.com/zhihefang/wf-diff	true	true	true	pytorch
https://paperswithcode.com/paper/comparative-evaluation-of-earthquake	Comparative evaluation of earthquake forecasting models: An application to Italy	2405.10712	https://arxiv.org/abs/2405.10712v1	https://arxiv.org/pdf/2405.10712v1.pdf	https://github.com/jbrehmer42/Earthquakes_Italy	true	false	true	none
https://paperswithcode.com/paper/voice-transformer-network-sequence-to	Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining	1912.06813	https://arxiv.org/abs/1912.06813v1	https://arxiv.org/pdf/1912.06813v1.pdf	https://github.com/unilight/seq2seq-vc	false	false	true	pytorch
https://paperswithcode.com/paper/pretraining-techniques-for-sequence-to	Pretraining Techniques for Sequence-to-Sequence Voice Conversion	2008.03088	https://arxiv.org/abs/2008.03088v1	https://arxiv.org/pdf/2008.03088v1.pdf	https://github.com/unilight/seq2seq-vc	false	false	true	pytorch
https://paperswithcode.com/paper/dynamic-implicit-image-function-for-efficient	Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image Representation	2306.12321	https://arxiv.org/abs/2306.12321v2	https://arxiv.org/pdf/2306.12321v2.pdf	https://github.com/hezongyao/diif	true	true	true	pytorch
https://paperswithcode.com/paper/decoupling-static-and-hierarchical-motion	Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation	2404.03645	https://arxiv.org/abs/2404.03645v1	https://arxiv.org/pdf/2404.03645v1.pdf	https://github.com/heshuting555/dshmp	true	true	true	pytorch
https://paperswithcode.com/paper/noise-robust-keyword-spotting-through-self	Noise-Robust Keyword Spotting through Self-supervised Pretraining	2403.18560	https://arxiv.org/abs/2403.18560v1	https://arxiv.org/pdf/2403.18560v1.pdf	https://github.com/aau-es-ml/ssl_noise-robust_kws	true	true	false	pytorch
https://paperswithcode.com/paper/improving-label-deficient-keyword-spotting	Improving Label-Deficient Keyword Spotting Through Self-Supervised Pretraining	2210.01703	https://arxiv.org/abs/2210.01703v3	https://arxiv.org/pdf/2210.01703v3.pdf	https://github.com/aau-es-ml/ssl_noise-robust_kws	false	false	true	pytorch
https://paperswithcode.com/paper/keyword-transformer-a-self-attention-model	Keyword Transformer: A Self-Attention Model for Keyword Spotting	2104.00769	https://arxiv.org/abs/2104.00769v3	https://arxiv.org/pdf/2104.00769v3.pdf	https://github.com/aau-es-ml/ssl_noise-robust_kws	false	false	true	pytorch
https://paperswithcode.com/paper/data2vec-a-general-framework-for-self-1	data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language	2202.03555	https://arxiv.org/abs/2202.03555v3	https://arxiv.org/pdf/2202.03555v3.pdf	https://github.com/aau-es-ml/ssl_noise-robust_kws	false	false	true	pytorch
https://paperswithcode.com/paper/estimating-aging-curves-using-multiple	Filling the Gaps: A Multiple Imputation Approach to Estimating Aging Curves in Baseball	2210.02383	https://arxiv.org/abs/2210.02383v3	https://arxiv.org/pdf/2210.02383v3.pdf	https://github.com/qntkhvn/aging	true	true	false	none
https://paperswithcode.com/paper/rho-1-not-all-tokens-are-what-you-need	Rho-1: Not All Tokens Are What You Need	2404.07965	https://arxiv.org/abs/2404.07965v4	https://arxiv.org/pdf/2404.07965v4.pdf	https://github.com/ZubinGou/rho	false	false	true	none
https://paperswithcode.com/paper/on-temporal-references-in-emergent	It's About Time: Temporal References in Emergent Communication	2310.06555	https://arxiv.org/abs/2310.06555v2	https://arxiv.org/pdf/2310.06555v2.pdf	https://github.com/olipinski/trg	true	true	false	pytorch
https://paperswithcode.com/paper/mdvit-multi-domain-vision-transformer-for	MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets	2307.02100	https://arxiv.org/abs/2307.02100v3	https://arxiv.org/pdf/2307.02100v3.pdf	https://github.com/siyi-wind/tip	false	false	true	pytorch
https://paperswithcode.com/paper/probing-for-multilingual-numerical	Probing for Multilingual Numerical Understanding in Transformer-Based Language Models	2010.06666	https://arxiv.org/abs/2010.06666v1	https://arxiv.org/pdf/2010.06666v1.pdf	https://github.com/dj1121/tlm_num_probe	true	true	false	pytorch
https://paperswithcode.com/paper/game-based-platforms-for-artificial	Games for Artificial Intelligence Research: A Review and Perspectives	2304.13269	https://arxiv.org/abs/2304.13269v4	https://arxiv.org/pdf/2304.13269v4.pdf	https://github.com/sustechgameai/gameai-platforms	true	true	false	none
https://paperswithcode.com/paper/adaptive-multi-head-contrastive-learning	Adaptive Multi-head Contrastive Learning	2310.05615	https://arxiv.org/abs/2310.05615v3	https://arxiv.org/pdf/2310.05615v3.pdf	https://github.com/leiwangr/cl	true	true	false	pytorch
https://paperswithcode.com/paper/pypots-a-python-toolbox-for-data-mining-on	PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series	2305.18811	https://arxiv.org/abs/2305.18811v1	https://arxiv.org/pdf/2305.18811v1.pdf	https://github.com/WenjieDu/PyGrinder	true	false	true	pytorch
https://paperswithcode.com/paper/mirage-model-agnostic-graph-distillation-for	Mirage: Model-Agnostic Graph Distillation for Graph Classification	2310.09486	https://arxiv.org/abs/2310.09486v4	https://arxiv.org/pdf/2310.09486v4.pdf	https://github.com/idea-iitd/mirage	true	true	false	pytorch
https://paperswithcode.com/paper/configurable-safety-tuning-of-language-models	Configurable Safety Tuning of Language Models with Synthetic Preference Data	2404.00495	https://arxiv.org/abs/2404.00495v1	https://arxiv.org/pdf/2404.00495v1.pdf	https://github.com/vicgalle/configurable-safety-tuning	true	true	true	pytorch
https://paperswithcode.com/paper/selfpose3d-self-supervised-multi-person-multi	SelfPose3d: Self-Supervised Multi-Person Multi-View 3d Pose Estimation	2404.02041	https://arxiv.org/abs/2404.02041v2	https://arxiv.org/pdf/2404.02041v2.pdf	https://github.com/camma-public/selfpose3d	true	true	true	pytorch
https://paperswithcode.com/paper/cameractrl-enabling-camera-control-for-text	CameraCtrl: Enabling Camera Control for Text-to-Video Generation	2404.02101	https://arxiv.org/abs/2404.02101v1	https://arxiv.org/pdf/2404.02101v1.pdf	https://github.com/hehao13/cameractrl	true	true	true	pytorch
https://paperswithcode.com/paper/learning-to-rank-patches-for-unbiased-image	Learning to Rank Patches for Unbiased Image Redundancy Reduction	2404.00680	https://arxiv.org/abs/2404.00680v2	https://arxiv.org/pdf/2404.00680v2.pdf	https://github.com/irslu/ltrp	true	true	false	pytorch
https://paperswithcode.com/paper/dmssn-distilled-mixed-spectral-spatial	DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object Detection	2404.00694	https://arxiv.org/abs/2404.00694v1	https://arxiv.org/pdf/2404.00694v1.pdf	https://github.com/anonymous0519/hsod-bit	true	true	false	pytorch
https://paperswithcode.com/paper/humanizing-machine-generated-content-evading	Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack	2404.01907	https://arxiv.org/abs/2404.01907v1	https://arxiv.org/pdf/2404.01907v1.pdf	https://github.com/zhouying20/hmgc	true	true	true	pytorch
https://paperswithcode.com/paper/diffusion-models-for-computational-design-at	Automating Computational Design with Generative AI	2307.02511	https://arxiv.org/abs/2307.02511v2	https://arxiv.org/pdf/2307.02511v2.pdf	https://github.com/ai4sc/bim-diffusion-models	true	true	false	none
https://paperswithcode.com/paper/a-new-benchmark-and-model-for-challenging	A New Benchmark and Model for Challenging Image Manipulation Detection	2311.14218	https://arxiv.org/abs/2311.14218v2	https://arxiv.org/pdf/2311.14218v2.pdf	https://github.com/zhenfeiz/cimd	true	true	true	none
https://paperswithcode.com/paper/a-transformer-approach-for-electricity-price	A Transformer approach for Electricity Price Forecasting	2403.16108	https://arxiv.org/abs/2403.16108v2	https://arxiv.org/pdf/2403.16108v2.pdf	https://github.com/osllogon/epf-transformers	true	true	true	pytorch
https://paperswithcode.com/paper/robust-offline-policy-evaluation-and	Robust Offline Reinforcement learning with Heavy-Tailed Rewards	2310.18715	https://arxiv.org/abs/2310.18715v2	https://arxiv.org/pdf/2310.18715v2.pdf	https://github.com/mamba413/room	true	true	true	pytorch
https://paperswithcode.com/paper/long-form-evaluation-of-model-editing	Long-form evaluation of model editing	2402.09394	https://arxiv.org/abs/2402.09394v2	https://arxiv.org/pdf/2402.09394v2.pdf	https://github.com/domenicrosati/longform-evaluation-model-editing	true	true	true	pytorch
https://paperswithcode.com/paper/cages-cost-aware-gradient-entropy-search-for	CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization	2405.07760	https://arxiv.org/abs/2405.07760v1	https://arxiv.org/pdf/2405.07760v1.pdf	https://github.com/PaulsonLab/CAGES	true	true	true	pytorch
https://paperswithcode.com/paper/enhancing-semantic-fidelity-in-text-to-image	Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models	2403.06381	https://arxiv.org/abs/2403.06381v1	https://arxiv.org/pdf/2403.06381v1.pdf	https://github.com/yangzhang-v5/attention_regulation	true	true	true	pytorch
https://paperswithcode.com/paper/eye-gaze-guided-multi-modal-alignment	Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning	2403.12416	https://arxiv.org/abs/2403.12416v3	https://arxiv.org/pdf/2403.12416v3.pdf	https://github.com/momarky/egma	true	true	true	pytorch
https://paperswithcode.com/paper/burstattention-an-efficient-distributed	BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences	2403.09347	https://arxiv.org/abs/2403.09347v4	https://arxiv.org/pdf/2403.09347v4.pdf	https://github.com/MayDomine/Burst-Attention	true	false	true	pytorch
https://paperswithcode.com/paper/lucid-llm-generated-utterances-for-complex	LUCID: LLM-Generated Utterances for Complex and Interesting Dialogues	2403.00462	https://arxiv.org/abs/2403.00462v2	https://arxiv.org/pdf/2403.00462v2.pdf	https://github.com/apple/ml-lucid-datagen	true	true	true	none
https://paperswithcode.com/paper/learning-dynamic-graphs-from-all-contextual	Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting	2306.15927	https://arxiv.org/abs/2306.15927v2	https://arxiv.org/pdf/2306.15927v2.pdf	https://github.com/USC-InfoLab/busyness-graph-neural-network	true	false	false	pytorch
https://paperswithcode.com/paper/syren-new-precise-formulae-for-the-linear-and	syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy	2410.14623	https://arxiv.org/abs/2410.14623v1	https://arxiv.org/pdf/2410.14623v1.pdf	https://github.com/deaglanbartlett/symbolic_pofk	true	false	true	pytorch
https://paperswithcode.com/paper/beyond-autoregression-discrete-diffusion-for	Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning	2410.14157	https://arxiv.org/abs/2410.14157v1	https://arxiv.org/pdf/2410.14157v1.pdf	https://github.com/HKUNLP/diffusion-vs-ar	true	false	true	pytorch
https://paperswithcode.com/paper/the-why-in-business-processes-discovery-of	The WHY in Business Processes: Discovery of Causal Execution Dependencies	2310.14975	https://arxiv.org/abs/2310.14975v3	https://arxiv.org/pdf/2310.14975v3.pdf	https://github.com/ibm/sax4bpm	false	false	true	none
https://paperswithcode.com/paper/how-well-can-large-language-models-explain	How well can a large language model explain business processes as perceived by users?	2401.12846	https://arxiv.org/abs/2401.12846v4	https://arxiv.org/pdf/2401.12846v4.pdf	https://github.com/ibm/sax4bpm	true	true	true	none
https://paperswithcode.com/paper/geot-tensor-centric-library-for-graph-neural	GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU	2404.03019	https://arxiv.org/abs/2404.03019v2	https://arxiv.org/pdf/2404.03019v2.pdf	https://github.com/fishmingyu/geot	true	true	false	pytorch
https://paperswithcode.com/paper/lampilot-an-open-benchmark-dataset-for	LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs	2312.04372	https://arxiv.org/abs/2312.04372v2	https://arxiv.org/pdf/2312.04372v2.pdf	https://github.com/purduedigitaltwin/lampilot	true	true	true	none
https://paperswithcode.com/paper/sok-unintended-interactions-among-machine	SoK: Unintended Interactions among Machine Learning Defenses and Risks	2312.04542	https://arxiv.org/abs/2312.04542v2	https://arxiv.org/pdf/2312.04542v2.pdf	https://github.com/ssg-research/sok-unintended-interactions	true	true	false	pytorch
https://paperswithcode.com/paper/differentiable-instruction-optimization-for	Differentiable Instruction Optimization for Cross-Task Generalization	2306.10098	https://arxiv.org/abs/2306.10098v1	https://arxiv.org/pdf/2306.10098v1.pdf	https://github.com/misonuma/instopt	true	true	false	pytorch
https://paperswithcode.com/paper/bcamirs-at-semeval-2024-task-4-beyond-words-a	BCAmirs at SemEval-2024 Task 4: Beyond Words: A Multimodal and Multilingual Exploration of Persuasion in Memes	2404.03022	https://arxiv.org/abs/2404.03022v2	https://arxiv.org/pdf/2404.03022v2.pdf	https://github.com/amirabaskohi/beyond-words-a-multimodal-exploration-of-persuasion-in-memes	true	true	true	pytorch
https://paperswithcode.com/paper/uncertainty-estimation-for-path-loss-and	Uncertainty Estimation for Path Loss and Radio Metric Models	2501.06308	https://arxiv.org/abs/2501.06308v1	https://arxiv.org/pdf/2501.06308v1.pdf	https://github.com/ic-crc/uncertainty-estimation	true	true	true	none
https://paperswithcode.com/paper/increase-inductive-graph-representation	INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging	2302.02738	https://arxiv.org/abs/2302.02738v1	https://arxiv.org/pdf/2302.02738v1.pdf	https://github.com/Aminsheykh98/INCREASE-pytorch	false	false	false	pytorch
https://paperswithcode.com/paper/visualizing-the-loss-landscape-of-neural-nets	Visualizing the Loss Landscape of Neural Nets	1712.09913	http://arxiv.org/abs/1712.09913v3	http://arxiv.org/pdf/1712.09913v3.pdf	https://github.com/StephenThacker/Visualiation-of-Loss-Function	false	false	true	tf
https://paperswithcode.com/paper/multiple-environment-self-adaptive-network	Multiple-environment Self-adaptive Network for Aerial-view Geo-localization	2204.08381	https://arxiv.org/abs/2204.08381v2	https://arxiv.org/pdf/2204.08381v2.pdf	https://github.com/wtyhub/MuseNet	true	false	true	pytorch
https://paperswithcode.com/paper/challenges-for-reinforcement-learning-in-1	Challenges for Reinforcement Learning in Quantum Circuit Design	2312.11337	https://arxiv.org/abs/2312.11337v3	https://arxiv.org/pdf/2312.11337v3.pdf	https://github.com/philippaltmann/qcd	true	true	true	none
https://paperswithcode.com/paper/on-the-trustworthiness-of-generative	On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective	2502.14296	https://arxiv.org/abs/2502.14296v3	https://arxiv.org/pdf/2502.14296v3.pdf	https://github.com/thuccslab/figstep	false	false	true	none
https://paperswithcode.com/paper/large-language-models-for-in-context-student	Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming	2310.10690	https://arxiv.org/abs/2310.10690v3	https://arxiv.org/pdf/2310.10690v3.pdf	https://github.com/machine-teaching-group/edm2024-llm-student-modeling	true	false	false	none
https://paperswithcode.com/paper/multi-objective-transmission-expansion-an	Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study	2311.09563	https://arxiv.org/abs/2311.09563v3	https://arxiv.org/pdf/2311.09563v3.pdf	https://github.com/sarojkhanal/motep-osw	true	true	true	none
https://paperswithcode.com/paper/antiferromagnetic-and-bond-order-wave-phases	Antiferromagnetic and bond-order-wave phases in the half-filled two-dimensional optical Su-Schrieffer-Heeger-Hubbard model	2502.14196	https://arxiv.org/abs/2502.14196v1	https://arxiv.org/pdf/2502.14196v1.pdf	https://github.com/smoqysuite/smoqydqmc.jl	true	false	false	none
https://paperswithcode.com/paper/deep-reinforcement-learning-for-personalized-1	Deep Reinforcement Learning for Personalized Diagnostic Decision Pathways Using Electronic Health Records: A Comparative Study on Anemia and Systemic Lupus Erythematosus	2404.05913	https://arxiv.org/abs/2404.05913v1	https://arxiv.org/pdf/2404.05913v1.pdf	https://github.com/lilly-muyama/deep_rl_diagnosis_pathways	true	true	false	tf
https://paperswithcode.com/paper/classification-of-breast-cancer	Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method	2405.03642	https://arxiv.org/abs/2405.03642v2	https://arxiv.org/pdf/2405.03642v2.pdf	https://github.com/matinamehdizadeh/Breast-Cancer-Detection	true	true	false	pytorch
https://paperswithcode.com/paper/consistent-point-orientation-for-manifold	Consistent Point Orientation for Manifold Surfaces via Boundary Integration	2407.03165	https://arxiv.org/abs/2407.03165v1	https://arxiv.org/pdf/2407.03165v1.pdf	https://github.com/liuweizhou319/bim	true	true	false	none
https://paperswithcode.com/paper/a-high-order-conservative-cut-finite-element	A High-Order Conservative Cut Finite Element Method for Problems in Time-Dependent Domains	2404.10756	https://arxiv.org/abs/2404.10756v3	https://arxiv.org/pdf/2404.10756v3.pdf	https://github.com/cutfem/cutfem-library	true	true	false	none
https://paperswithcode.com/paper/two-stages-domain-invariant-representation	Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains	2412.04682	https://arxiv.org/abs/2412.04682v1	https://arxiv.org/pdf/2412.04682v1.pdf	https://github.com/oh-yu/domain-invariant-learning	true	false	true	pytorch
https://paperswithcode.com/paper/bertweet-a-pre-trained-language-model-for	BERTweet: A pre-trained language model for English Tweets	2005.10200	https://arxiv.org/abs/2005.10200v2	https://arxiv.org/pdf/2005.10200v2.pdf	https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/bertweet	false	false	false	mindspore
https://paperswithcode.com/paper/when-do-prompting-and-prefix-tuning-work-a	When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations	2310.19698	https://arxiv.org/abs/2310.19698v2	https://arxiv.org/pdf/2310.19698v2.pdf	https://github.com/aleksandarpetrov/prefix-tuning-theory	true	true	true	pytorch
https://paperswithcode.com/paper/raffesdg-random-frequency-filtering-enabled	RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation	2405.01228	https://arxiv.org/abs/2405.01228v2	https://arxiv.org/pdf/2405.01228v2.pdf	https://github.com/liamheng/non-iid_medical_image_segmentation	true	true	true	pytorch
https://paperswithcode.com/paper/hypothesis-testing-using-causal-and-causal	Causal Structural Hypothesis Testing and Data Generation Models	2210.11275	https://arxiv.org/abs/2210.11275v2	https://arxiv.org/pdf/2210.11275v2.pdf	https://github.com/sunaybhat1/causal-structural-hypothesis-testing	true	true	true	pytorch
https://paperswithcode.com/paper/q8bert-quantized-8bit-bert	Q8BERT: Quantized 8Bit BERT	1910.06188	https://arxiv.org/abs/1910.06188v2	https://arxiv.org/pdf/1910.06188v2.pdf	https://github.com/iabd/QuantizedNMT	false	false	true	pytorch
https://paperswithcode.com/paper/medoid-silhouette-clustering-with-automatic	Medoid Silhouette clustering with automatic cluster number selection	2309.03751	https://arxiv.org/abs/2309.03751v1	https://arxiv.org/pdf/2309.03751v1.pdf	https://github.com/kno10/python-kmedoids	false	false	true	none
https://paperswithcode.com/paper/learning-based-video-motion-magnification	Learning-based Video Motion Magnification	1804.02684	http://arxiv.org/abs/1804.02684v3	http://arxiv.org/pdf/1804.02684v3.pdf	https://github.com/ZhengPeng7/motion_magnification_learning-based	false	false	true	pytorch
https://paperswithcode.com/paper/harnessing-data-and-physics-for-deep-learning	Deep learning phase recovery: data-driven, physics-driven, or combining both?	2404.01360	https://arxiv.org/abs/2404.01360v2	https://arxiv.org/pdf/2404.01360v2.pdf	https://github.com/kqwang/DLPR	true	true	true	pytorch
https://paperswithcode.com/paper/symmetric-observations-without-symmetric	Symmetric observations without symmetric causal explanations	2502.14950	https://arxiv.org/abs/2502.14950v1	https://arxiv.org/pdf/2502.14950v1.pdf	https://github.com/apozas/symmetric-causal	true	true	true	none
https://paperswithcode.com/paper/sea-land-cloud-segmentation-in-satellite	Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning	2310.16210	https://arxiv.org/abs/2310.16210v4	https://arxiv.org/pdf/2310.16210v4.pdf	https://github.com/ntnu-smallsat-lab/s_l_c_segm_hyp_img	true	true	true	tf
https://paperswithcode.com/paper/when-big-data-actually-are-low-rank-or	When big data actually are low-rank, or entrywise approximation of certain function-generated matrices	2407.03250	https://arxiv.org/abs/2407.03250v4	https://arxiv.org/pdf/2407.03250v4.pdf	https://github.com/sbudzinskiy/low-rank-big-data	true	true	true	none
https://paperswithcode.com/paper/ampic-adaptive-model-predictive-ising	Traffic signal optimization in large-scale urban road networks: an adaptive-predictive controller using Ising models	2406.03690	https://arxiv.org/abs/2406.03690v2	https://arxiv.org/pdf/2406.03690v2.pdf	https://github.com/toyotacrdl/ampic	true	true	false	none
https://paperswithcode.com/paper/identification-of-snps-in-genomes-using	GRAMEP: an alignment-free method based on the Maximum Entropy Principle for identifying SNPs	2405.01715	https://arxiv.org/abs/2405.01715v2	https://arxiv.org/pdf/2405.01715v2.pdf	https://github.com/omatheuspimenta/gramep	true	true	false	none
https://paperswithcode.com/paper/machine-learning-predictions-from	Machine learning predictions from unpredictable chaos	2503.14956	https://arxiv.org/abs/2503.14956v1	https://arxiv.org/pdf/2503.14956v1.pdf	https://github.com/kelu0124/TEPC	true	false	false	none
https://paperswithcode.com/paper/mistral-7b	Mistral 7B	2310.06825	https://arxiv.org/abs/2310.06825v1	https://arxiv.org/pdf/2310.06825v1.pdf	https://github.com/mgmalek/efficient_cross_entropy	false	false	true	pytorch
https://paperswithcode.com/paper/can-modifying-data-address-graph-domain	Can Modifying Data Address Graph Domain Adaptation?	2407.19311	https://arxiv.org/abs/2407.19311v1	https://arxiv.org/pdf/2407.19311v1.pdf	https://github.com/zjunet/GraphAlign	true	false	false	pytorch
https://paperswithcode.com/paper/attention-guided-cosine-margin-for-overcoming	Attention Guided Cosine Margin For Overcoming Class-Imbalance in Few-Shot Road Object Detection	2111.06639	https://arxiv.org/abs/2111.06639v1	https://arxiv.org/pdf/2111.06639v1.pdf	https://github.com/amajee11us/smile-fsod	false	false	true	pytorch
https://paperswithcode.com/paper/generating-realistic-3d-brain-mris-using-a	Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model	2212.08034	https://arxiv.org/abs/2212.08034v2	https://arxiv.org/pdf/2212.08034v2.pdf	https://github.com/jiaqiw01/MRIAnatEval	false	false	true	pytorch
https://paperswithcode.com/paper/large-scale-multi-domain-recommendation-an	Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework	2404.08361	https://arxiv.org/abs/2404.08361v2	https://arxiv.org/pdf/2404.08361v2.pdf	https://github.com/xidongbo/dfei	true	true	false	tf
https://paperswithcode.com/paper/fastspell-the-langid-magic-spell	FastSpell: the LangId Magic Spell	2404.08345	https://arxiv.org/abs/2404.08345v1	https://arxiv.org/pdf/2404.08345v1.pdf	https://github.com/mbanon/fastspell	true	true	false	none
https://paperswithcode.com/paper/a-classification-benchmark-for-artificial	A Classification Benchmark for Artificial Intelligence Detection of Laryngeal Cancer from Patient Voice	2412.16267	https://arxiv.org/abs/2412.16267v2	https://arxiv.org/pdf/2412.16267v2.pdf	https://github.com/mary-paterson/laryngealcancerclassificationbenchmark	true	true	false	none
https://paperswithcode.com/paper/instructpix2pix-learning-to-follow-image	InstructPix2Pix: Learning to Follow Image Editing Instructions	2211.09800	https://arxiv.org/abs/2211.09800v2	https://arxiv.org/pdf/2211.09800v2.pdf	https://github.com/lsl001006/zone	false	false	true	pytorch
https://paperswithcode.com/paper/zone-zero-shot-instruction-guided-local	ZONE: Zero-Shot Instruction-Guided Local Editing	2312.16794	https://arxiv.org/abs/2312.16794v2	https://arxiv.org/pdf/2312.16794v2.pdf	https://github.com/lsl001006/zone	true	true	true	pytorch
https://paperswithcode.com/paper/empowering-clinicians-and-democratizing-data	Large Language Models Streamline Automated Machine Learning for Clinical Studies	2308.14120	https://arxiv.org/abs/2308.14120v5	https://arxiv.org/pdf/2308.14120v5.pdf	https://github.com/tayebiarasteh/llmmed	true	true	true	none
https://paperswithcode.com/paper/a-benchmark-suite-for-systematically	A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts	2406.10368	https://arxiv.org/abs/2406.10368v2	https://arxiv.org/pdf/2406.10368v2.pdf	https://github.com/unitn-sml/rsbench-code	true	false	true	pytorch
https://paperswithcode.com/paper/autonomous-llm-driven-research-from-data-to	Autonomous LLM-driven research from data to human-verifiable research papers	2404.17605	https://arxiv.org/abs/2404.17605v1	https://arxiv.org/pdf/2404.17605v1.pdf	https://github.com/technion-kishony-lab/data-to-paper	true	true	true	none
https://paperswithcode.com/paper/deslib-a-dynamic-ensemble-selection-library	DESlib: A Dynamic ensemble selection library in Python	1802.04967	http://arxiv.org/abs/1802.04967v3	http://arxiv.org/pdf/1802.04967v3.pdf	https://github.com/scikit-learn-contrib/DESlib	true	true	true	none
https://paperswithcode.com/paper/an-open-world-lottery-ticket-for-out-of	The Open-World Lottery Ticket Hypothesis for OOD Intent Classification	2210.07071	https://arxiv.org/abs/2210.07071v3	https://arxiv.org/pdf/2210.07071v3.pdf	https://github.com/zyh190507/open-world-lottery	true	true	false	pytorch
https://paperswithcode.com/paper/factuality-enhanced-language-models-for-open	Factuality Enhanced Language Models for Open-Ended Text Generation	2206.04624	https://arxiv.org/abs/2206.04624v3	https://arxiv.org/pdf/2206.04624v3.pdf	https://github.com/ranggihwang/pregated_moe	false	false	true	pytorch
https://paperswithcode.com/paper/global-local-collaborative-inference-with-llm	Global-Local Collaborative Inference with LLM for Lidar-Based Open-Vocabulary Detection	2407.08931	https://arxiv.org/abs/2407.08931v1	https://arxiv.org/pdf/2407.08931v1.pdf	https://github.com/gradiustwinbee/glis	true	true	false	none
https://paperswithcode.com/paper/elucidating-the-theoretical-underpinnings-of	Elucidating the theoretical underpinnings of surrogate gradient learning in spiking neural networks	2404.14964	https://arxiv.org/abs/2404.14964v3	https://arxiv.org/pdf/2404.14964v3.pdf	https://github.com/fmi-basel/surrogate-gradient-theory	true	true	true	jax
https://paperswithcode.com/paper/astropop-the-astronomical-polarimetry-and	ASTROPOP: the ASTROnomical POlarimetry and Photometry pipeline	1811.01408	https://arxiv.org/abs/1811.01408v1	https://arxiv.org/pdf/1811.01408v1.pdf	https://github.com/juliotux/astropop	true	true	true	none
https://paperswithcode.com/paper/deep-learning-in-medical-image-registration-1	Deep Learning in Medical Image Registration: Magic or Mirage?	2408.05839	https://arxiv.org/abs/2408.05839v2	https://arxiv.org/pdf/2408.05839v2.pdf	https://github.com/rohitrango/Magic-or-Mirage	true	false	false	pytorch

Subsets and Splits

Framework Repo Connectivity Analysis

Reveals the number of official and unofficial repositories and papers associated with different frameworks, highlighting the most connected ones.

Deduplicated Paper-Code Links

This query provides a detailed and organized list of repositories linked to single papers, highlighting official status and mention sources, which is useful for understanding the relationship between papers and their corresponding repositories.

Paper Repo Counts & Distribution

Provides detailed statistics on the distribution of papers across different numbers of repositories, highlighting the percentage of papers with multiple repositories.

Quantum Papers with Code Links

Lists quantum-related papers with their titles, arXiv IDs, frameworks, and code repository links, providing a valuable resource for researchers interested in quantum computing.

Financial Stock Price Prediction

Finds papers related to stock prices, financial markets, and predictions, providing a focused subset for further analysis.

SQL Console for pwc-archive/links-between-paper-and-code

Retrieves specific details about a single paper by its arXiv ID, providing limited insight into the dataset.

Search for YOLO Links

Retrieves a limited set of records related to YOLO, providing basic information about papers and repositories but without deeper analysis.

Prompt Optimization and Personalization

Retrieves a limited set of papers with titles containing specific keywords related to prompt optimization and personalization, providing basic filtering of the dataset.