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/mobile-robot-path-planning-in-dynamic	Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learning	2005.05420	https://arxiv.org/abs/2005.05420v2	https://arxiv.org/pdf/2005.05420v2.pdf	https://github.com/Tushar-ml/G2RL-Path-Planning	false	false	true	tf
https://paperswithcode.com/paper/making-large-language-models-perform-better	Making Large Language Models Perform Better in Knowledge Graph Completion	2310.06671	https://arxiv.org/abs/2310.06671v2	https://arxiv.org/pdf/2310.06671v2.pdf	https://github.com/zjukg/kopa	true	true	true	pytorch
https://paperswithcode.com/paper/focalunetr-a-focal-transformer-for-boundary	FocalUNETR: A Focal Transformer for Boundary-aware Segmentation of CT Images	2210.03189	https://arxiv.org/abs/2210.03189v2	https://arxiv.org/pdf/2210.03189v2.pdf	https://github.com/chengyinlee/focalunetr	true	true	true	pytorch
https://paperswithcode.com/paper/focal-loss-for-dense-object-detection	Focal Loss for Dense Object Detection	1708.02002	http://arxiv.org/abs/1708.02002v2	http://arxiv.org/pdf/1708.02002v2.pdf	https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet152	false	false	false	mindspore
https://paperswithcode.com/paper/sight-a-large-annotated-dataset-on-student	SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts	2306.09343	https://arxiv.org/abs/2306.09343v1	https://arxiv.org/pdf/2306.09343v1.pdf	https://github.com/rosewang2008/sight	true	true	true	none
https://paperswithcode.com/paper/revealing-biases-in-the-sampling-of	Revealing biases in the sampling of ecological interaction networks	1708.01242	http://arxiv.org/abs/1708.01242v1	http://arxiv.org/pdf/1708.01242v1.pdf	https://github.com/cran/EcoNetGen	false	false	true	none
https://paperswithcode.com/paper/a-generative-machine-learning-approach-for	A Generative Machine Learning Approach for Improving Precipitation from Earth System Models	2406.15026	https://arxiv.org/abs/2406.15026v1	https://arxiv.org/pdf/2406.15026v1.pdf	https://github.com/p-hss/consistency-climate-downscaling	true	true	false	pytorch
https://paperswithcode.com/paper/clapeyron-jl-an-extensible-open-source-julia	Clapeyron.jl: An extensible, open-source fluid-thermodynamics toolkit	2201.08927	https://arxiv.org/abs/2201.08927v2	https://arxiv.org/pdf/2201.08927v2.pdf	https://github.com/ClapeyronThermo/Clapeyron.jl	false	false	true	none
https://paperswithcode.com/paper/laughter-synthesis-using-pseudo-phonetic	Laughter Synthesis using Pseudo Phonetic Tokens with a Large-scale In-the-wild Laughter Corpus	2305.12442	https://arxiv.org/abs/2305.12442v2	https://arxiv.org/pdf/2305.12442v2.pdf	https://github.com/aria-k-alethia/laughter-synthesis	true	true	true	pytorch
https://paperswithcode.com/paper/dbf-unet-a-two-stage-framework-for-carotid	DBF-UNet: A Two-Stage Framework for Carotid Artery Segmentation with Pseudo-Label Generation	2504.00908	https://arxiv.org/abs/2504.00908v1	https://arxiv.org/pdf/2504.00908v1.pdf	https://github.com/haoxuanli-thu/dbf-unet	true	true	false	pytorch
https://paperswithcode.com/paper/a-benchmark-dataset-for-understandable	Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation	2012.02420	https://arxiv.org/abs/2012.02420v2	https://arxiv.org/pdf/2012.02420v2.pdf	https://github.com/machinelearning4health/medlane	true	true	false	pytorch
https://paperswithcode.com/paper/beyond-english-centric-multilingual-machine	Beyond English-Centric Multilingual Machine Translation	2010.11125	https://arxiv.org/abs/2010.11125v1	https://arxiv.org/pdf/2010.11125v1.pdf	https://github.com/xhlulu/dl-translate	false	false	true	pytorch
https://paperswithcode.com/paper/client-wise-modality-selection-for-balanced	Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection	2401.00403	https://arxiv.org/abs/2401.00403v2	https://arxiv.org/pdf/2401.00403v2.pdf	https://github.com/fanyunfeng-bit/balanced-modality-selection-in-mfl	true	true	false	pytorch
https://paperswithcode.com/paper/no-language-left-behind-scaling-human-1	No Language Left Behind: Scaling Human-Centered Machine Translation	2207.04672	https://arxiv.org/abs/2207.04672v3	https://arxiv.org/pdf/2207.04672v3.pdf	https://github.com/xhlulu/dl-translate	false	false	true	pytorch
https://paperswithcode.com/paper/exposurediffusion-learning-to-expose-for-low	ExposureDiffusion: Learning to Expose for Low-light Image Enhancement	2307.07710	https://arxiv.org/abs/2307.07710v2	https://arxiv.org/pdf/2307.07710v2.pdf	https://github.com/wyf0912/ExposureDiffusion	true	true	true	pytorch
https://paperswithcode.com/paper/pyvrp-a-high-performance-vrp-solver-package	PyVRP: a high-performance VRP solver package	2403.13795	https://arxiv.org/abs/2403.13795v2	https://arxiv.org/pdf/2403.13795v2.pdf	https://github.com/informsjoc/2023.0055	true	true	false	none
https://paperswithcode.com/paper/genetic-programming-for-explainable-manifold	Genetic Programming for Explainable Manifold Learning	2403.14139	https://arxiv.org/abs/2403.14139v2	https://arxiv.org/pdf/2403.14139v2.pdf	https://github.com/cravies/gp-emal	true	true	false	none
https://paperswithcode.com/paper/audio-classification-with-dilated-convolution	Audio classification with Dilated Convolution with Learnable Spacings	2309.13972	https://arxiv.org/abs/2309.13972v2	https://arxiv.org/pdf/2309.13972v2.pdf	https://github.com/k-h-ismail/dcls-audio	true	true	true	pytorch
https://paperswithcode.com/paper/p1ac-revisiting-absolute-pose-from-a-single	P1AC: Revisiting Absolute Pose From a Single Affine Correspondence	2011.08790	https://arxiv.org/abs/2011.08790v6	https://arxiv.org/pdf/2011.08790v6.pdf	https://github.com/jonathanventura/p1ac	true	true	true	none
https://paperswithcode.com/paper/alternate-loss-functions-can-improve-the	Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks	2303.09935	https://arxiv.org/abs/2303.09935v4	https://arxiv.org/pdf/2303.09935v4.pdf	https://github.com/arindam-ds/alternate_loss_functions	true	false	true	none
https://paperswithcode.com/paper/assessing-keyness-using-permutation-tests	Assessing Keyness using Permutation Tests	2308.13383	https://arxiv.org/abs/2308.13383v1	https://arxiv.org/pdf/2308.13383v1.pdf	https://github.com/thmild/keyperm	true	true	false	none
https://paperswithcode.com/paper/towards-understanding-and-improving-knowledge	Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation	2305.08096	https://arxiv.org/abs/2305.08096v2	https://arxiv.org/pdf/2305.08096v2.pdf	https://github.com/songmzhang/nmt-kd	true	true	true	pytorch
https://paperswithcode.com/paper/a-one-stop-3d-target-reconstruction-and	A One Stop 3D Target Reconstruction and multilevel Segmentation Method	2308.06974	https://arxiv.org/abs/2308.06974v1	https://arxiv.org/pdf/2308.06974v1.pdf	https://github.com/ganlab/ostra	true	true	false	pytorch
https://paperswithcode.com/paper/fully-connected-spatial-temporal-graph-for	Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data	2309.05305	https://arxiv.org/abs/2309.05305v3	https://arxiv.org/pdf/2309.05305v3.pdf	https://github.com/Frank-Wang-oss/FCSTGNN	true	true	true	pytorch
https://paperswithcode.com/paper/unsupervised-representation-learning-with-1	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	1511.06434	http://arxiv.org/abs/1511.06434v2	http://arxiv.org/pdf/1511.06434v2.pdf	https://github.com/ahmed-alllam/Equinox/blob/main/examples/deep_convolutional_gan.ipynb	false	false	false	jax
https://paperswithcode.com/paper/consistent-manifold-representation-for	Consistent Manifold Representation for Topological Data Analysis	1606.02353	http://arxiv.org/abs/1606.02353v2	http://arxiv.org/pdf/1606.02353v2.pdf	https://gitlab.com/datafold-dev/datafold	false	false	true	none
https://paperswithcode.com/paper/invisible-watermarking-for-audio-generation	Invisible Watermarking for Audio Generation Diffusion Models	2309.13166	https://arxiv.org/abs/2309.13166v2	https://arxiv.org/pdf/2309.13166v2.pdf	https://github.com/mikiyaxi/watermark-audio-diffusion	true	true	true	pytorch
https://paperswithcode.com/paper/3d-gres-generalized-3d-referring-expression	3D-GRES: Generalized 3D Referring Expression Segmentation	2407.20664	https://arxiv.org/abs/2407.20664v1	https://arxiv.org/pdf/2407.20664v1.pdf	https://github.com/sosppxo/3d-gres	false	true	true	none
https://paperswithcode.com/paper/ummaformer-a-universal-multimodal-adaptive-1	UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localization	2308.14395	https://arxiv.org/abs/2308.14395v1	https://arxiv.org/pdf/2308.14395v1.pdf	https://github.com/ymhzyj/UMMAFormer	true	true	true	pytorch
https://paperswithcode.com/paper/can-gnn-be-good-adapter-for-llms	Can GNN be Good Adapter for LLMs?	2402.12984	https://arxiv.org/abs/2402.12984v1	https://arxiv.org/pdf/2402.12984v1.pdf	https://github.com/hxttkl/GraphAdapter	true	false	true	pytorch
https://paperswithcode.com/paper/diffusionret-generative-text-video-retrieval	DiffusionRet: Generative Text-Video Retrieval with Diffusion Model	2303.09867	https://arxiv.org/abs/2303.09867v2	https://arxiv.org/pdf/2303.09867v2.pdf	https://github.com/jpthu17/diffusionret	true	true	true	pytorch
https://paperswithcode.com/paper/an-exhaustive-addis-principle-for-online-fwer	An exhaustive ADDIS principle for online FWER control	2308.13827	https://arxiv.org/abs/2308.13827v2	https://arxiv.org/pdf/2308.13827v2.pdf	https://github.com/fischer23/exhaustive-addis-procedures	true	true	false	none
https://paperswithcode.com/paper/link-prediction-for-wikipedia-articles-as-a	Link Prediction for Wikipedia Articles as a Natural Language Inference Task	2308.16469	https://arxiv.org/abs/2308.16469v2	https://arxiv.org/pdf/2308.16469v2.pdf	https://github.com/phanchauthang/dsaa-2023-kaggle	true	true	false	none
https://paperswithcode.com/paper/video-adverb-retrieval-with-compositional	Video-adverb retrieval with compositional adverb-action embeddings	2309.15086	https://arxiv.org/abs/2309.15086v1	https://arxiv.org/pdf/2309.15086v1.pdf	https://github.com/ExplainableML/ReGaDa	true	false	true	pytorch
https://paperswithcode.com/paper/eaglevision-object-level-attribute-multimodal	EagleVision: Object-level Attribute Multimodal LLM for Remote Sensing	2503.23330	https://arxiv.org/abs/2503.23330v1	https://arxiv.org/pdf/2503.23330v1.pdf	https://github.com/xiangtodayeatswhat/eaglevision	true	true	true	pytorch
https://paperswithcode.com/paper/mila-memory-based-instance-level-adaptation	MILA: Memory-Based Instance-Level Adaptation for Cross-Domain Object Detection	null	https://arxiv.org/abs/2309.01086v1	https://arxiv.org/pdf/2309.01086v1.pdf	https://github.com/hitachi-rd-cv/MILA	false	false	false	pytorch
https://paperswithcode.com/paper/investigating-the-interplay-between-features	Investigating the Interplay between Features and Structures in Graph Learning	2308.09570	https://arxiv.org/abs/2308.09570v1	https://arxiv.org/pdf/2308.09570v1.pdf	https://github.com/danielecastellana22/feature-structure-interplay-graph-learning	true	true	true	pytorch
https://paperswithcode.com/paper/masked-motion-predictors-are-strong-3d-action	Masked Motion Predictors are Strong 3D Action Representation Learners	2308.07092	https://arxiv.org/abs/2308.07092v1	https://arxiv.org/pdf/2308.07092v1.pdf	https://github.com/maoyunyao/mamp	true	true	true	pytorch
https://paperswithcode.com/paper/advancing-vision-transformers-with-group-mix	Advancing Vision Transformers with Group-Mix Attention	2311.15157	https://arxiv.org/abs/2311.15157v1	https://arxiv.org/pdf/2311.15157v1.pdf	https://github.com/ailab-cvc/groupmixformer	true	true	false	pytorch
https://paperswithcode.com/paper/a-contrastive-knowledge-transfer-framework	A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning	2303.07599	https://arxiv.org/abs/2303.07599v1	https://arxiv.org/pdf/2303.07599v1.pdf	https://github.com/kaiqi123/cktf	true	true	true	pytorch
https://paperswithcode.com/paper/measuring-complex-refractive-index-through	Measuring complex refractive index through deeplearning-enabled optical reflectometry	null	https://iopscience.iop.org/article/10.1088/2053-1583/acc59b	https://scholar.google.com/scholar_url?url=https://iopscience.iop.org/article/10.1088/2053-1583/acc59b/pdf%3Fcasa_token%3DJFntSMpPW5YAAAAA:00qHoX_1d3Ut8J9SVbIlQ0-TlyOCIw5ZNmAIWhhw1Ypdj1v3MMxbZUzoLn-OAt2smr3hHUuZDCPrbCbuiVykoPIZrRJC&hl=en&sa=T&oi=ucasa&ct=ucasa&ei=v3kqZsDlCe2R6rQPt66KqAQ&scisig=AFWwaeY3pnqlcMbnZM64FtFG_Hzv	https://github.com/tigerwang3133/ReflectoNet	true	false	false	pytorch
https://paperswithcode.com/paper/ask-me-in-english-instead-cross-lingual	Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queries	2310.13132	https://arxiv.org/abs/2310.13132v2	https://arxiv.org/pdf/2310.13132v2.pdf	https://github.com/claws-lab/XLingEval	true	true	true	none
https://paperswithcode.com/paper/pixels-progressive-image-xemplar-based	PIXELS: Progressive Image Xemplar-based Editing with Latent Surgery	2501.09826	https://arxiv.org/abs/2501.09826v1	https://arxiv.org/pdf/2501.09826v1.pdf	https://github.com/amazon-science/pixels	true	true	false	pytorch
https://paperswithcode.com/paper/methods-for-systematic-study-of-nuclear	Methods for systematic study of nuclear structure in high-energy collisions	2302.14026	https://arxiv.org/abs/2302.14026v1	https://arxiv.org/pdf/2302.14026v1.pdf	https://github.com/mluzum/isobar-sampler	false	false	true	none
https://paperswithcode.com/paper/a-quic-implementation-for-ns-3	A QUIC Implementation for ns-3	1902.06121	https://arxiv.org/abs/1902.06121v2	https://arxiv.org/pdf/1902.06121v2.pdf	https://github.com/signetlabdei/quic	true	false	true	none
https://paperswithcode.com/paper/studying-short-range-nuclear-correlations	Studying short-range nuclear correlations using relativistic heavy-ion collisions	2312.10129	https://arxiv.org/abs/2312.10129v1	https://arxiv.org/pdf/2312.10129v1.pdf	https://github.com/mluzum/isobar-sampler	true	true	true	none
https://paperswithcode.com/paper/reusing-convolutional-neural-network-models	Reusing Convolutional Neural Network Models through Modularization and Composition	2311.04438	https://arxiv.org/abs/2311.04438v1	https://arxiv.org/pdf/2311.04438v1.pdf	https://github.com/qibinhang/cnnsplitter	true	true	false	pytorch
https://paperswithcode.com/paper/conformal-prediction-interval-for-dynamic	Conformal prediction interval for dynamic time-series	2010.09107	https://arxiv.org/abs/2010.09107v9	https://arxiv.org/pdf/2010.09107v9.pdf	https://github.com/hamrel-cxu/EnbPI	true	true	true	pytorch
https://paperswithcode.com/paper/conformal-anomaly-detection-on-spatio	Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data	2105.11886	https://arxiv.org/abs/2105.11886v2	https://arxiv.org/pdf/2105.11886v2.pdf	https://github.com/hamrel-cxu/EnbPI	false	false	true	pytorch
https://paperswithcode.com/paper/slowfast-networks-for-video-recognition	SlowFast Networks for Video Recognition	1812.03982	https://arxiv.org/abs/1812.03982v3	https://arxiv.org/pdf/1812.03982v3.pdf	https://github.com/tianfr/semantic-flow	false	false	true	pytorch
https://paperswithcode.com/paper/well-tempered-teleparallel-horndeski	Well-tempered teleparallel Horndeski cosmology: a teleparallel variation to the cosmological constant problem	2107.08762	https://arxiv.org/abs/2107.08762v3	https://arxiv.org/pdf/2107.08762v3.pdf	https://github.com/reggiebernardo/notebooks	true	true	true	none
https://paperswithcode.com/paper/stealth-black-hole-perturbations-in-kinetic	Stealth black hole perturbations in kinetic gravity braiding	2007.06006	https://arxiv.org/abs/2007.06006v4	https://arxiv.org/pdf/2007.06006v4.pdf	https://github.com/reggiebernardo/notebooks	true	true	true	none
https://paperswithcode.com/paper/policy-optimization-in-a-noisy-neighborhood-1	Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control	2309.14597	https://arxiv.org/abs/2309.14597v3	https://arxiv.org/pdf/2309.14597v3.pdf	https://github.com/nathanrahn/return-landscapes	true	true	false	jax
https://paperswithcode.com/paper/gated-attention-coding-for-training-high	Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks	2308.06582	https://arxiv.org/abs/2308.06582v2	https://arxiv.org/pdf/2308.06582v2.pdf	https://github.com/bollossom/GAC	true	true	true	pytorch
https://paperswithcode.com/paper/a-zero-few-shot-anomaly-classification-and	APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD	2305.17382	https://arxiv.org/abs/2305.17382v3	https://arxiv.org/pdf/2305.17382v3.pdf	https://github.com/hq-deng/AnoVL	false	false	true	pytorch
https://paperswithcode.com/paper/grad-cam-visual-explanations-from-deep	Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization	1610.02391	https://arxiv.org/abs/1610.02391v4	https://arxiv.org/pdf/1610.02391v4.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/learning-important-features-through	Learning Important Features Through Propagating Activation Differences	1704.02685	https://arxiv.org/abs/1704.02685v2	https://arxiv.org/pdf/1704.02685v2.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/captum-a-unified-and-generic-model	Captum: A unified and generic model interpretability library for PyTorch	2009.07896	https://arxiv.org/abs/2009.07896v1	https://arxiv.org/pdf/2009.07896v1.pdf	https://github.com/pytorch/captum	true	false	true	pytorch
https://paperswithcode.com/paper/axiomatic-attribution-for-deep-networks	Axiomatic Attribution for Deep Networks	1703.01365	http://arxiv.org/abs/1703.01365v2	http://arxiv.org/pdf/1703.01365v2.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/visualizing-and-understanding-convolutional	Visualizing and Understanding Convolutional Networks	1311.2901	http://arxiv.org/abs/1311.2901v3	http://arxiv.org/pdf/1311.2901v3.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/smoothgrad-removing-noise-by-adding-noise	SmoothGrad: removing noise by adding noise	1706.03825	http://arxiv.org/abs/1706.03825v1	http://arxiv.org/pdf/1706.03825v1.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/how-important-is-a-neuron	How Important Is a Neuron?	1805.12233	http://arxiv.org/abs/1805.12233v1	http://arxiv.org/pdf/1805.12233v1.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/computationally-efficient-measures-of	Computationally Efficient Measures of Internal Neuron Importance	1807.09946	http://arxiv.org/abs/1807.09946v1	http://arxiv.org/pdf/1807.09946v1.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/influence-directed-explanations-for-deep	Influence-Directed Explanations for Deep Convolutional Networks	1802.03788	http://arxiv.org/abs/1802.03788v2	http://arxiv.org/pdf/1802.03788v2.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/how-sensitive-are-sensitivity-based	On the (In)fidelity and Sensitivity for Explanations	1901.09392	https://arxiv.org/abs/1901.09392v4	https://arxiv.org/pdf/1901.09392v4.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/feature-dropout-revisiting-the-role-of	Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning	null	https://openreview.net/forum?id=M7hijAPA4B	https://openreview.net/pdf?id=M7hijAPA4B	https://github.com/xiluohe/feature-dropout	true	true	false	pytorch
https://paperswithcode.com/paper/estimating-training-data-influence-by	Estimating Training Data Influence by Tracing Gradient Descent	2002.08484	https://arxiv.org/abs/2002.08484v3	https://arxiv.org/pdf/2002.08484v3.pdf	https://github.com/pytorch/captum	false	false	true	pytorch
https://paperswithcode.com/paper/improving-online-continual-learning	Improving Online Continual Learning Performance and Stability with Temporal Ensembles	2306.16817	https://arxiv.org/abs/2306.16817v2	https://arxiv.org/pdf/2306.16817v2.pdf	https://github.com/albinsou/online_ema	true	true	true	pytorch
https://paperswithcode.com/paper/reading-between-the-lines-modeling-user	Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming	2210.14306	https://arxiv.org/abs/2210.14306v5	https://arxiv.org/pdf/2210.14306v5.pdf	https://github.com/microsoft/coderec_programming_states	true	true	true	none
https://paperswithcode.com/paper/self-similarity-based-and-novelty-based-loss	Self-Similarity-Based and Novelty-based loss for music structure analysis	2309.02243	https://arxiv.org/abs/2309.02243v1	https://arxiv.org/pdf/2309.02243v1.pdf	https://github.com/geoffroypeeters/ssmnet_ISMIR2023	true	true	true	pytorch
https://paperswithcode.com/paper/enhancing-joint-multiple-intent-detection-and	Enhancing Joint Multiple Intent Detection and Slot Filling with Global Intent-Slot Co-occurrence	null	https://aclanthology.org/2022.emnlp-main.543/	https://aclanthology.org/2022.emnlp-main.543.pdf	https://github.com/smxiao/GISCo	false	true	false	pytorch
https://paperswithcode.com/paper/task-oriented-communication-for-edge-video	Task-Oriented Communication for Edge Video Analytics	2211.14049	https://arxiv.org/abs/2211.14049v3	https://arxiv.org/pdf/2211.14049v3.pdf	https://github.com/shaojiawei07/tocom-tem	true	true	true	pytorch
https://paperswithcode.com/paper/task-oriented-communication-for-multi-device	Task-Oriented Communication for Multi-Device Cooperative Edge Inference	2109.00172	https://arxiv.org/abs/2109.00172v3	https://arxiv.org/pdf/2109.00172v3.pdf	https://github.com/shaojiawei07/tocom-tem	false	false	true	pytorch
https://paperswithcode.com/paper/few-shot-medical-image-segmentation-via-a	Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer	2309.04825	https://arxiv.org/abs/2309.04825v1	https://arxiv.org/pdf/2309.04825v1.pdf	https://github.com/yazhouzhu19/rpt	true	true	false	pytorch
https://paperswithcode.com/paper/parameter-efficient-language-model-tuning	Parameter-Efficient Language Model Tuning with Active Learning in Low-Resource Settings	2305.14576	https://arxiv.org/abs/2305.14576v2	https://arxiv.org/pdf/2305.14576v2.pdf	https://github.com/josipjukic/adapter-al	true	true	false	pytorch
https://paperswithcode.com/paper/llm4plc-harnessing-large-language-models-for	LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems	2401.05443	https://arxiv.org/abs/2401.05443v1	https://arxiv.org/pdf/2401.05443v1.pdf	https://github.com/AICPS/LLM_4_PLC	true	false	false	none
https://paperswithcode.com/paper/multiview-detection-with-feature-perspective	Multiview Detection with Feature Perspective Transformation	2007.07247	https://arxiv.org/abs/2007.07247v2	https://arxiv.org/pdf/2007.07247v2.pdf	https://github.com/shaojiawei07/tocom-tem	false	false	true	pytorch
https://paperswithcode.com/paper/controlling-large-language-models-to-generate	Large Language Models for Code: Security Hardening and Adversarial Testing	2302.05319	https://arxiv.org/abs/2302.05319v5	https://arxiv.org/pdf/2302.05319v5.pdf	https://github.com/eth-sri/sven	true	true	true	none
https://paperswithcode.com/paper/a-conversational-paradigm-for-program	CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis	2203.13474	https://arxiv.org/abs/2203.13474v5	https://arxiv.org/pdf/2203.13474v5.pdf	https://github.com/eth-sri/sven	false	false	true	none
https://paperswithcode.com/paper/event-stream-based-visual-object-tracking-a	Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline	2309.14611	https://arxiv.org/abs/2309.14611v1	https://arxiv.org/pdf/2309.14611v1.pdf	https://github.com/event-ahu/coesot	true	true	true	pytorch
https://paperswithcode.com/paper/treating-motion-as-option-with-output	Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation	2309.14786	https://arxiv.org/abs/2309.14786v1	https://arxiv.org/pdf/2309.14786v1.pdf	https://github.com/suhwan-cho/tmo	true	true	true	pytorch
https://paperswithcode.com/paper/formalmath-benchmarking-formal-mathematical	FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models	2505.02735	https://arxiv.org/abs/2505.02735v1	https://arxiv.org/pdf/2505.02735v1.pdf	https://github.com/sphere-ai-lab/formalmath-bench	true	true	true	pytorch
https://paperswithcode.com/paper/catch-me-if-you-search-when-contextual-web	Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations	2504.01153	https://arxiv.org/abs/2504.01153v3	https://arxiv.org/pdf/2504.01153v3.pdf	https://github.com/MahjabinNahar/CatchMeIfYouSearch	true	true	true	none
https://paperswithcode.com/paper/llama-open-and-efficient-foundation-language-1	LLaMA: Open and Efficient Foundation Language Models	2302.13971	https://arxiv.org/abs/2302.13971v1	https://arxiv.org/pdf/2302.13971v1.pdf	https://github.com/xzhang97666/alpacare	false	false	true	none
https://paperswithcode.com/paper/llama-2-open-foundation-and-fine-tuned-chat	Llama 2: Open Foundation and Fine-Tuned Chat Models	2307.09288	https://arxiv.org/abs/2307.09288v2	https://arxiv.org/pdf/2307.09288v2.pdf	https://github.com/xzhang97666/alpacare	false	false	true	none
https://paperswithcode.com/paper/efficiently-modeling-long-sequences-with-1	Efficiently Modeling Long Sequences with Structured State Spaces	2111.00396	https://arxiv.org/abs/2111.00396v3	https://arxiv.org/pdf/2111.00396v3.pdf	https://github.com/nicolaszucchet/minimal-lru	false	false	true	jax
https://paperswithcode.com/paper/resurrecting-recurrent-neural-networks-for	Resurrecting Recurrent Neural Networks for Long Sequences	2303.06349	https://arxiv.org/abs/2303.06349v1	https://arxiv.org/pdf/2303.06349v1.pdf	https://github.com/nicolaszucchet/minimal-lru	false	false	true	jax
https://paperswithcode.com/paper/classification-of-influenza-hemagglutinin	Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks	2108.04240	https://arxiv.org/abs/2108.04240v1	https://arxiv.org/pdf/2108.04240v1.pdf	https://gitlab.com/charalambos.chrysostomou/embc21_influenza	true	false	false	tf
https://paperswithcode.com/paper/a-simple-latent-diffusion-approach-for	A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting	2401.10227	https://arxiv.org/abs/2401.10227v2	https://arxiv.org/pdf/2401.10227v2.pdf	https://github.com/segments-ai/latent-diffusion-segmentation	true	true	true	pytorch
https://paperswithcode.com/paper/counterfactual-prediction-under-selective	Counterfactual Prediction Under Selective Confounding	2310.14064	https://arxiv.org/abs/2310.14064v1	https://arxiv.org/pdf/2310.14064v1.pdf	https://github.com/sohaib730/causalml	true	true	false	none
https://paperswithcode.com/paper/svdd-2024-the-inaugural-singing-voice	SVDD 2024: The Inaugural Singing Voice Deepfake Detection Challenge	2408.16132	https://arxiv.org/abs/2408.16132v2	https://arxiv.org/pdf/2408.16132v2.pdf	https://github.com/svddchallenge/ctrsvdd2024_baseline	true	true	true	pytorch
https://paperswithcode.com/paper/from-chebnet-to-chebgibbsnet-1	From ChebNet to ChebGibbsNet	2412.01789	https://arxiv.org/abs/2412.01789v1	https://arxiv.org/pdf/2412.01789v1.pdf	https://github.com/hazdzz/ChebGibbsNet	true	false	true	pytorch
https://paperswithcode.com/paper/attention-guided-residual-u-net-with-se	Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy Images	null	https://doi.org/10.1089/cmb.2023.0446	https://doi.org/10.1089/cmb.2023.0446	https://github.com/jovialniyo93/cell-segmentation	false	false	false	tf
https://paperswithcode.com/paper/how-large-language-models-are-transforming	How Large Language Models are Transforming Machine-Paraphrased Plagiarism	2210.03568	https://arxiv.org/abs/2210.03568v3	https://arxiv.org/pdf/2210.03568v3.pdf	https://github.com/jpwahle/emnlp23-paraphrase-types	false	false	true	pytorch
https://paperswithcode.com/paper/ssd-single-shot-multibox-detector	SSD: Single Shot MultiBox Detector	1512.02325	http://arxiv.org/abs/1512.02325v5	http://arxiv.org/pdf/1512.02325v5.pdf	https://github.com/lufficc/SSD	false	false	true	pytorch
https://paperswithcode.com/paper/colmap-pcd-an-open-source-tool-for-fine-image	Colmap-PCD: An Open-source Tool for Fine Image-to-point cloud Registration	2310.05504	https://arxiv.org/abs/2310.05504v1	https://arxiv.org/pdf/2310.05504v1.pdf	https://github.com/xiaobaiiiiii/colmap-pcd	true	true	true	none
https://paperswithcode.com/paper/commander-s-intent-a-dataset-and-modeling	A Computational Interface to Translate Strategic Intent from Unstructured Language in a Low-Data Setting	2208.08374	https://arxiv.org/abs/2208.08374v2	https://arxiv.org/pdf/2208.08374v2.pdf	https://github.com/anonymousturtle433/anonymized-code	true	true	false	pytorch
https://paperswithcode.com/paper/an-interpretable-clustering-approach-to	An interpretable clustering approach to safety climate analysis: examining driver group distinction in safety climate perceptions	2310.19841	https://arxiv.org/abs/2310.19841v1	https://arxiv.org/pdf/2310.19841v1.pdf	https://github.com/nus-dbe/truck-driver-safety-climate	true	true	false	none
https://paperswithcode.com/paper/self-supervised-one-shot-learning-for	Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images	2303.05639	https://arxiv.org/abs/2303.05639v3	https://arxiv.org/pdf/2303.05639v3.pdf	https://github.com/avm-debatr/ganecdotes	true	true	true	pytorch
https://paperswithcode.com/paper/self-instruct-aligning-language-model-with	Self-Instruct: Aligning Language Models with Self-Generated Instructions	2212.10560	https://arxiv.org/abs/2212.10560v2	https://arxiv.org/pdf/2212.10560v2.pdf	https://github.com/xzhang97666/alpacare	false	false	true	none

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.