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/construction-of-large-scale-english-verbal	Construction of Large-scale English Verbal Multiword Expression Annotated Corpus	null	https://aclanthology.org/L18-1396	https://aclanthology.org/L18-1396.pdf	https://github.com/naist-cl-parsing/Verbal-MWE-annotations	true	true	false	none
https://paperswithcode.com/paper/astronomaly-protege-discovery-through-human	Astronomaly Protege: Discovery Through Human-Machine Collaboration	2411.04188	https://arxiv.org/abs/2411.04188v3	https://arxiv.org/pdf/2411.04188v3.pdf	https://github.com/michellelochner/mgcls.protege	true	true	true	none
https://paperswithcode.com/paper/traffic4cast-large-scale-traffic-prediction	Traffic4cast -- Large-scale Traffic Prediction using 3DResNet and Sparse-UNet	2111.05990	https://arxiv.org/abs/2111.05990v1	https://arxiv.org/pdf/2111.05990v1.pdf	https://github.com/resuly/traffic4cast-2021	true	true	true	pytorch
https://paperswithcode.com/paper/a-deep-generative-framework-for-paraphrase	A Deep Generative Framework for Paraphrase Generation	1709.05074	http://arxiv.org/abs/1709.05074v1	http://arxiv.org/pdf/1709.05074v1.pdf	https://github.com/arvind385801/paraphrasegen	false	false	true	pytorch
https://paperswithcode.com/paper/frank-wolfe-methods-with-an-unbounded	Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning	2012.15361	https://arxiv.org/abs/2012.15361v2	https://arxiv.org/pdf/2012.15361v2.pdf	https://github.com/wanghaoyue123/frank-wolfe-with-unbounded-constraints	true	true	false	none
https://paperswithcode.com/paper/deep-reinforcement-learning-with-double-q	Deep Reinforcement Learning with Double Q-learning	1509.06461	http://arxiv.org/abs/1509.06461v3	http://arxiv.org/pdf/1509.06461v3.pdf	https://github.com/ianlimle/ItsMeMario	false	false	true	pytorch
https://paperswithcode.com/paper/a-factored-neural-network-model-for	A Factored Neural Network Model for Characterizing Online Discussions in Vector Space	null	https://aclanthology.org/D17-1243	https://aclanthology.org/D17-1243.pdf	https://github.com/hao-cheng/factored_neural	true	true	false	tf
https://paperswithcode.com/paper/implicit-neural-representations-with-periodic	Implicit Neural Representations with Periodic Activation Functions	2006.09661	https://arxiv.org/abs/2006.09661v1	https://arxiv.org/pdf/2006.09661v1.pdf	https://github.com/TalFurman/Implict_neural_representation_of_images	false	false	true	pytorch
https://paperswithcode.com/paper/what-were-they-thinking-pharmacologic-priors	What Were They Thinking? Pharmacologic priors implicit in a choice of 3+3 dose-escalation design	2012.05301	https://arxiv.org/abs/2012.05301v2	https://arxiv.org/pdf/2012.05301v2.pdf	https://github.com/dcnorris/precautionary	false	false	true	none
https://paperswithcode.com/paper/retrospective-analysis-of-a-fatal-dose	Retrospective analysis of a fatal dose-finding trial	2004.12755	http://arxiv.org/abs/2004.12755v1	http://arxiv.org/pdf/2004.12755v1.pdf	https://github.com/dcnorris/precautionary	false	false	true	none
https://paperswithcode.com/paper/need-for-speed-a-benchmark-for-higher-frame	Need for Speed: A Benchmark for Higher Frame Rate Object Tracking	1703.05884	http://arxiv.org/abs/1703.05884v2	http://arxiv.org/pdf/1703.05884v2.pdf	https://github.com/susomena/DeepSlowMotion	false	false	true	tf
https://paperswithcode.com/paper/feature-importance-aware-transferable	Feature Importance-aware Transferable Adversarial Attacks	2107.14185	https://arxiv.org/abs/2107.14185v3	https://arxiv.org/pdf/2107.14185v3.pdf	https://github.com/ZOMIN28/FIA-pytorch	false	false	false	pytorch
https://paperswithcode.com/paper/flipda-effective-and-robust-data-augmentation	FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning	2108.06332	https://arxiv.org/abs/2108.06332v2	https://arxiv.org/pdf/2108.06332v2.pdf	https://github.com/zhouj8553/flipda	true	true	false	pytorch
https://paperswithcode.com/paper/robustfill-neural-program-learning-under	RobustFill: Neural Program Learning under Noisy I/O	1703.07469	http://arxiv.org/abs/1703.07469v1	http://arxiv.org/pdf/1703.07469v1.pdf	https://github.com/amitz25/PCCoder	false	false	true	pytorch
https://paperswithcode.com/paper/overfitting-the-data-compact-neural-video	Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation	2108.08202	https://arxiv.org/abs/2108.08202v2	https://arxiv.org/pdf/2108.08202v2.pdf	https://github.com/neural-video-delivery/cafm-pytorch-iccv2021	true	true	false	pytorch
https://paperswithcode.com/paper/out-of-distribution-detection-using-outlier	Out-of-Distribution Detection Using Outlier Detection Methods	2108.08218	https://arxiv.org/abs/2108.08218v2	https://arxiv.org/pdf/2108.08218v2.pdf	https://github.com/jandiers/ood-detection	true	true	false	tf
https://paperswithcode.com/paper/offline-meta-reinforcement-learning-with-1	Offline Meta-Reinforcement Learning with Online Self-Supervision	2107.03974	https://arxiv.org/abs/2107.03974v4	https://arxiv.org/pdf/2107.03974v4.pdf	https://github.com/anair13/bullet-manipulation-affordances	false	false	true	none
https://paperswithcode.com/paper/model-change-active-learning-in-graph-based	Model-Change Active Learning in Graph-Based Semi-Supervised Learning	2110.07739	https://arxiv.org/abs/2110.07739v2	https://arxiv.org/pdf/2110.07739v2.pdf	https://github.com/millerk22/model-change-paper	true	true	false	none
https://paperswithcode.com/paper/monotonic-chunkwise-attention	Monotonic Chunkwise Attention	1712.05382	http://arxiv.org/abs/1712.05382v2	http://arxiv.org/pdf/1712.05382v2.pdf	https://github.com/craffel/mocha	true	true	true	tf
https://paperswithcode.com/paper/what-can-i-do-here-learning-new-skills-by	What Can I Do Here? Learning New Skills by Imagining Visual Affordances	2106.00671	https://arxiv.org/abs/2106.00671v2	https://arxiv.org/pdf/2106.00671v2.pdf	https://github.com/anair13/bullet-manipulation-affordances	false	false	true	none
https://paperswithcode.com/paper/keynet-keypoint-detection-by-handcrafted-and	Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters	1904.00889	https://arxiv.org/abs/1904.00889v3	https://arxiv.org/pdf/1904.00889v3.pdf	https://github.com/bluedream1121/Key.Net_PyTorch	false	false	true	pytorch
https://paperswithcode.com/paper/plan-attend-generate-character-level-neural-1	Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder	1706.05087	http://arxiv.org/abs/1706.05087v2	http://arxiv.org/pdf/1706.05087v2.pdf	https://github.com/nyu-dl/dl4mt-cdec	true	true	false	none
https://paperswithcode.com/paper/automated-coronal-hole-identification-via	Automated Coronal Hole Identification via Multi-Thermal Intensity Segmentation	1711.11476	http://arxiv.org/abs/1711.11476v1	http://arxiv.org/pdf/1711.11476v1.pdf	https://github.com/GartontT/CHIMERA	false	false	true	none
https://paperswithcode.com/paper/benchmarking-relief-based-feature-selection	Benchmarking Relief-Based Feature Selection Methods for Bioinformatics Data Mining	1711.08477	http://arxiv.org/abs/1711.08477v2	http://arxiv.org/pdf/1711.08477v2.pdf	https://github.com/EpistasisLab/ReBATE	true	true	true	none
https://paperswithcode.com/paper/readers-vs-writers-vs-texts-coping-with	Readers vs. Writers vs. Texts: Coping with Different Perspectives of Text Understanding in Emotion Annotation	null	https://aclanthology.org/W17-0801	https://aclanthology.org/W17-0801.pdf	https://github.com/JULIELab/EmoBank	true	true	false	none
https://paperswithcode.com/paper/automating-the-search-for-a-patents-prior-art	Automating the search for a patent's prior art with a full text similarity search	1901.03136	http://arxiv.org/abs/1901.03136v2	http://arxiv.org/pdf/1901.03136v2.pdf	https://github.com/helmersl/patent_similarity_search	true	true	false	tf
https://paperswithcode.com/paper/continuous-cutting-plane-algorithms-in	Continuous cutting plane algorithms in integer programming	2204.09122	https://arxiv.org/abs/2204.09122v3	https://arxiv.org/pdf/2204.09122v3.pdf	https://github.com/dchetelat/subadditive	true	true	false	pytorch
https://paperswithcode.com/paper/adaptive-convolution-kernel-for-artificial	Adaptive Convolution Kernel for Artificial Neural Networks	2009.06385	https://arxiv.org/abs/2009.06385v1	https://arxiv.org/pdf/2009.06385v1.pdf	https://github.com/btekgit/AdaptiveCNN	true	true	true	tf
https://paperswithcode.com/paper/shield-fast-practical-defense-and-vaccination	Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression	1802.06816	http://arxiv.org/abs/1802.06816v1	http://arxiv.org/pdf/1802.06816v1.pdf	https://github.com/Yuxin33/unmask	false	false	true	pytorch
https://paperswithcode.com/paper/unmask-adversarial-detection-and-defense	UnMask: Adversarial Detection and Defense Through Robust Feature Alignment	2002.09576	https://arxiv.org/abs/2002.09576v2	https://arxiv.org/pdf/2002.09576v2.pdf	https://github.com/Yuxin33/unmask	false	false	true	pytorch
https://paperswithcode.com/paper/the-numerics-of-gans	The Numerics of GANs	1705.10461	http://arxiv.org/abs/1705.10461v3	http://arxiv.org/pdf/1705.10461v3.pdf	https://github.com/nhynes/abc	false	false	true	pytorch
https://paperswithcode.com/paper/convolutional-neural-networks-for-sentence	Convolutional Neural Networks for Sentence Classification	1408.5882	http://arxiv.org/abs/1408.5882v2	http://arxiv.org/pdf/1408.5882v2.pdf	https://github.com/ddajing/multilayer-cnn-text-classification	false	false	true	tf
https://paperswithcode.com/paper/task-aware-information-routing-from-common	Task-Aware Information Routing from Common Representation Space in Lifelong Learning	2302.11346	https://arxiv.org/abs/2302.11346v1	https://arxiv.org/pdf/2302.11346v1.pdf	https://github.com/neurai-lab/tamil	true	true	false	pytorch
https://paperswithcode.com/paper/efficientvit-enhanced-linear-attention-for	EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction	2205.14756	https://arxiv.org/abs/2205.14756v6	https://arxiv.org/pdf/2205.14756v6.pdf	https://github.com/2023-MindSpore-4/Code10/tree/main/Efficientnet	false	false	false	mindspore
https://paperswithcode.com/paper/developing-a-unified-pipeline-for-large-scale-2	Developing a unified pipeline for large-scale structure data analysis with angular power spectra -- III. Implementing the multi-tracer technique to constrain neutrino masses	2009.05584	http://arxiv.org/abs/2009.05584v2	http://arxiv.org/pdf/2009.05584v2.pdf	https://github.com/ktanidis/Modified_CosmoSIS_for_galaxy_number_count_angular_power_spectra	true	true	true	none
https://paperswithcode.com/paper/plato-xl-exploring-the-large-scale-pre	PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation	2109.09519	https://arxiv.org/abs/2109.09519v2	https://arxiv.org/pdf/2109.09519v2.pdf	https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/plato-xl	false	false	false	paddle
https://paperswithcode.com/paper/an-upper-bound-for-the-number-of-chess	An upper bound for the number of chess diagrams without promotion	2112.09386	https://arxiv.org/abs/2112.09386v2	https://arxiv.org/pdf/2112.09386v2.pdf	https://github.com/DanielGourion/ChessDiagrams	true	false	false	none
https://paperswithcode.com/paper/learning-to-diversify-for-single-domain	Learning to Diversify for Single Domain Generalization	2108.11726	https://arxiv.org/abs/2108.11726v3	https://arxiv.org/pdf/2108.11726v3.pdf	https://github.com/busername/learning_to_diversify	true	true	true	pytorch
https://paperswithcode.com/paper/njoy-ncrystal-an-open-source-tool-for	NJOY+NCrystal: an open-source tool for creating thermal neutron scattering libraries	2108.11737	https://arxiv.org/abs/2108.11737v2	https://arxiv.org/pdf/2108.11737v2.pdf	https://github.com/highness-eu/njoy-ncrystal-library	true	true	false	none
https://paperswithcode.com/paper/fully-convolutional-networks-for-semantic	Fully Convolutional Networks for Semantic Segmentation	1605.06211	http://arxiv.org/abs/1605.06211v1	http://arxiv.org/pdf/1605.06211v1.pdf	https://github.com/2023-MindSpore-4/Code10/tree/main/FCN8s	false	false	false	mindspore
https://paperswithcode.com/paper/micromechanical-fatigue-experiments-for	Micromechanical fatigue experiments for validation of microstructure-sensitive fatigue simulation models	2112.04342	https://arxiv.org/abs/2112.04342v1	https://arxiv.org/pdf/2112.04342v1.pdf	https://github.com/boschresearch/vitemi	true	true	false	none
https://paperswithcode.com/paper/lyra-a-benchmark-for-turducken-style-code	Lyra: A Benchmark for Turducken-Style Code Generation	2108.12144	https://arxiv.org/abs/2108.12144v3	https://arxiv.org/pdf/2108.12144v3.pdf	https://github.com/liangqingyuan/lyra	true	true	true	pytorch
https://paperswithcode.com/paper/exploiting-anticommutation-in-hamiltonian	Exploiting anticommutation in Hamiltonian simulation	2103.07988	https://arxiv.org/abs/2103.07988v2	https://arxiv.org/pdf/2103.07988v2.pdf	https://github.com/zhaoqthu/anticommuHamiltonian	true	false	false	none
https://paperswithcode.com/paper/an-efficient-lstm-neural-network-based	An Efficient LSTM Neural Network-Based Framework for Vessel Location Forecasting	null	https://doi.org/10.1109/TITS.2023.3247993	https://scholar.google.com/scholar_url?url=https://ieeexplore.ieee.org/iel7/6979/4358928/10073952.pdf%3Fcasa_token%3Dn7JSzcTZI-YAAAAA:tfrTPUg5tvRJlwMG3EvMTr_TsZw-QlE71AFzpGLJcTU3E5gavmIam3ei0d3vwT7SbbfIW8Rd5Q&hl=el&sa=T&oi=ucasa&ct=ucasa&ei=cT8xZKqfF_6Sy9YPxfKx8A0&scisig=AJ9-iYufiQelQanCZCKIqoqoN2fr	https://github.com/eva-chon/VLF_VRF	false	false	false	tf
https://paperswithcode.com/paper/emotion-prediction-oriented-method-with	Emotion Prediction Oriented method with Multiple Supervisions for Emotion-Cause Pair Extraction	2302.12417	https://arxiv.org/abs/2302.12417v1	https://arxiv.org/pdf/2302.12417v1.pdf	https://github.com/lemei/epo-ecpe	true	true	true	pytorch
https://paperswithcode.com/paper/mlp-mixer-an-all-mlp-architecture-for-vision	MLP-Mixer: An all-MLP Architecture for Vision	2105.01601	https://arxiv.org/abs/2105.01601v4	https://arxiv.org/pdf/2105.01601v4.pdf	https://github.com/BR-IDL/PaddleViT/blob/main/image_classification/MLP-Mixer	false	false	false	paddle
https://paperswithcode.com/paper/a-new-procedure-for-selective-inference-with	SIGLE: a valid procedure for Selective Inference with the Generalized Linear Lasso	2203.15348	https://arxiv.org/abs/2203.15348v3	https://arxiv.org/pdf/2203.15348v3.pdf	https://github.com/quentin-duchemin/sigle	true	true	false	none
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/Bhavnicksm/vanilla-transformer-jax	false	false	true	jax
https://paperswithcode.com/paper/topic-aware-abstractive-text-summarization	Topic-Guided Abstractive Text Summarization: a Joint Learning Approach	2010.10323	https://arxiv.org/abs/2010.10323v2	https://arxiv.org/pdf/2010.10323v2.pdf	https://github.com/chz816/tas	true	true	false	pytorch
https://paperswithcode.com/paper/federated-reconnaissance-efficient	Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning	2109.00150	https://arxiv.org/abs/2109.00150v1	https://arxiv.org/pdf/2109.00150v1.pdf	https://github.com/ml4ai/fed-recon	true	true	true	pytorch
https://paperswithcode.com/paper/improving-multimodal-fusion-with-hierarchical	Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis	2109.00412	https://arxiv.org/abs/2109.00412v2	https://arxiv.org/pdf/2109.00412v2.pdf	https://github.com/declare-lab/multimodal-infomax	true	true	true	pytorch
https://paperswithcode.com/paper/torchaudio-building-blocks-for-audio-and	TorchAudio: Building Blocks for Audio and Speech Processing	2110.15018	https://arxiv.org/abs/2110.15018v2	https://arxiv.org/pdf/2110.15018v2.pdf	https://github.com/pytorch/audio	true	true	false	pytorch
https://paperswithcode.com/paper/modular-retrieval-for-generalization-and	Modular Retrieval for Generalization and Interpretation	2303.13419	https://arxiv.org/abs/2303.13419v1	https://arxiv.org/pdf/2303.13419v1.pdf	https://github.com/freedomintelligence/remop	true	true	true	pytorch
https://paperswithcode.com/paper/creative-diversity-patterns-in-the-creative	Creative Diversity: Patterns in the Creative Habits of ~10,000 People	2108.12759	https://arxiv.org/abs/2108.12759v2	https://arxiv.org/pdf/2108.12759v2.pdf	https://github.com/ericberlow/creative-diversity	true	false	false	none
https://paperswithcode.com/paper/have-i-done-enough-planning-or-should-i-plan	Have I done enough planning or should I plan more?	2201.00764	https://arxiv.org/abs/2201.00764v1	https://arxiv.org/pdf/2201.00764v1.pdf	https://github.com/reeche/planningamount	true	true	false	none
https://paperswithcode.com/paper/when-does-classical-chinese-help-quantifying	When Does Classical Chinese Help? Quantifying Cross-Lingual Transfer in Hanja and Kanbun	2411.04822	https://arxiv.org/abs/2411.04822v1	https://arxiv.org/pdf/2411.04822v1.pdf	https://github.com/seyoungsong/classical-chinese-transfer	true	false	true	none
https://paperswithcode.com/paper/the-newspaper-navigator-dataset-extracting	The Newspaper Navigator Dataset: Extracting And Analyzing Visual Content from 16 Million Historic Newspaper Pages in Chronicling America	2005.01583	https://arxiv.org/abs/2005.01583v1	https://arxiv.org/pdf/2005.01583v1.pdf	https://github.com/parthasarathy-ss/newspaper-navigator	false	false	true	pytorch
https://paperswithcode.com/paper/online-generalized-method-of-moments-for-time	Online Generalized Method of Moments for Time Series	2502.00751	https://arxiv.org/abs/2502.00751v1	https://arxiv.org/pdf/2502.00751v1.pdf	https://github.com/hemanlmf/gmwm	true	true	false	none
https://paperswithcode.com/paper/bert-assisted-semantic-annotation-correction	BERT-Assisted Semantic Annotation Correction for Emotion-Related Questions	2204.00916	https://arxiv.org/abs/2204.00916v1	https://arxiv.org/pdf/2204.00916v1.pdf	https://github.com/abecode/emo20q	true	true	false	none
https://paperswithcode.com/paper/scalable-feature-matching-across-large-data	Scalable Feature Matching Across Large Data Collections	2101.02035	https://arxiv.org/abs/2101.02035v1	https://arxiv.org/pdf/2101.02035v1.pdf	https://github.com/ddegras/matchFeat	true	true	true	none
https://paperswithcode.com/paper/learning-phrase-representations-using-rnn	Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation	1406.1078	http://arxiv.org/abs/1406.1078v3	http://arxiv.org/pdf/1406.1078v3.pdf	https://github.com/mindspore-ai/models/tree/master/official/nlp/gru	false	false	false	mindspore
https://paperswithcode.com/paper/wenet-production-first-and-production-ready	WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkit	2102.01547	https://arxiv.org/abs/2102.01547v5	https://arxiv.org/pdf/2102.01547v5.pdf	https://github.com/wenet-e2e/wenet	true	true	false	pytorch
https://paperswithcode.com/paper/timetraveler-reinforcement-learning-for	TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting	2109.04101	https://arxiv.org/abs/2109.04101v1	https://arxiv.org/pdf/2109.04101v1.pdf	https://github.com/jhl-hust/titer	true	true	false	pytorch
https://paperswithcode.com/paper/sampling-in-dirichlet-process-mixture-models	Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data	2202.13312	https://arxiv.org/abs/2202.13312v1	https://arxiv.org/pdf/2202.13312v1.pdf	https://github.com/bgu-cs-vil/dpmmsubclustersstreaming.jl	true	true	false	none
https://paperswithcode.com/paper/consensus-learning-from-heterogeneous	Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering	2202.13140	https://arxiv.org/abs/2202.13140v1	https://arxiv.org/pdf/2202.13140v1.pdf	https://github.com/seongku-kang/concf_www22	true	true	false	pytorch
https://paperswithcode.com/paper/voxel-transformer-for-3d-object-detection	Voxel Transformer for 3D Object Detection	2109.02497	https://arxiv.org/abs/2109.02497v2	https://arxiv.org/pdf/2109.02497v2.pdf	https://github.com/PointsCoder/VOTR	false	false	false	pytorch
https://paperswithcode.com/paper/transreid-transformer-based-object-re	TransReID: Transformer-based Object Re-Identification	2102.04378	https://arxiv.org/abs/2102.04378v2	https://arxiv.org/pdf/2102.04378v2.pdf	https://github.com/darrishabh/coviprox	false	false	true	pytorch
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-large	Very Deep Convolutional Networks for Large-Scale Image Recognition	1409.1556	http://arxiv.org/abs/1409.1556v6	http://arxiv.org/pdf/1409.1556v6.pdf	https://github.com/darrishabh/coviprox	false	false	true	pytorch
https://paperswithcode.com/paper/improved-latent-tree-induction-with-distant	Improved Latent Tree Induction with Distant Supervision via Span Constraints	2109.05112	https://arxiv.org/abs/2109.05112v2	https://arxiv.org/pdf/2109.05112v2.pdf	https://github.com/iesl/distantly-supervised-diora	true	true	false	pytorch
https://paperswithcode.com/paper/exploring-the-role-of-bert-token	Exploring the Role of BERT Token Representations to Explain Sentence Probing Results	2104.01477	https://arxiv.org/abs/2104.01477v2	https://arxiv.org/pdf/2104.01477v2.pdf	https://github.com/hmohebbi/explain-probing-results	true	true	true	none
https://paperswithcode.com/paper/total-recall-a-customized-continual-learning	Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers	2109.05186	https://arxiv.org/abs/2109.05186v2	https://arxiv.org/pdf/2109.05186v2.pdf	https://github.com/zhuang-li/cl_nsp	true	true	true	pytorch
https://paperswithcode.com/paper/squeezed-very-deep-convolutional-neural	Squeezed Very Deep Convolutional Neural Networks for Text Classification	1901.09821	http://arxiv.org/abs/1901.09821v1	http://arxiv.org/pdf/1901.09821v1.pdf	https://github.com/lazarotm/SVDCNN	false	true	false	pytorch
https://paperswithcode.com/paper/on-multi-layer-basis-pursuit-efficient	On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks	1806.00701	http://arxiv.org/abs/1806.00701v5	http://arxiv.org/pdf/1806.00701v5.pdf	https://github.com/Sulam-Group/ml-ista	false	false	true	pytorch
https://paperswithcode.com/paper/federated-learning-from-big-data-over	Federated Learning From Big Data Over Networks	2010.14159	https://arxiv.org/abs/2010.14159v1	https://arxiv.org/pdf/2010.14159v1.pdf	https://github.com/sahelyiyi/FederatedLearning	true	false	true	pytorch
https://paperswithcode.com/paper/fonbund-a-library-for-combining-cross-lingual	FonBund: A Library for Combining Cross-lingual Phonological Segment Data	null	https://aclanthology.org/L18-1353	https://aclanthology.org/L18-1353.pdf	https://github.com/googlei18n/language-resources	true	true	false	none
https://paperswithcode.com/paper/duluth-urop-at-semeval-2018-task-2	Duluth UROP at SemEval-2018 Task 2: Multilingual Emoji Prediction with Ensemble Learning and Oversampling	1805.10267	http://arxiv.org/abs/1805.10267v1	http://arxiv.org/pdf/1805.10267v1.pdf	https://github.com/shuningjin/SemEval2018-Task2-EmojiDetection	true	true	true	none
https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical	U-Net: Convolutional Networks for Biomedical Image Segmentation	1505.04597	http://arxiv.org/abs/1505.04597v1	http://arxiv.org/pdf/1505.04597v1.pdf	https://github.com/adityarajsahu/UNet-Implementation	false	false	true	tf
https://paperswithcode.com/paper/hdr-image-reconstruction-from-a-single	HDR image reconstruction from a single exposure using deep CNNs	1710.07480	http://arxiv.org/abs/1710.07480v1	http://arxiv.org/pdf/1710.07480v1.pdf	https://github.com/mantiuk/pwcmp	true	true	false	none
https://paperswithcode.com/paper/voxelwise-nonlinear-regression-toolbox-for	Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling	1612.00667	http://arxiv.org/abs/1612.00667v3	http://arxiv.org/pdf/1612.00667v3.pdf	https://github.com/imatge-upc/VNeAT	true	true	false	none
https://paperswithcode.com/paper/deriving-consensus-for-multi-parallel-corpora	Deriving Consensus for Multi-Parallel Corpora: an English Bible Study	null	https://aclanthology.org/I17-2076	https://aclanthology.org/I17-2076.pdf	https://github.com/pitrack/monolign	true	true	false	none
https://paperswithcode.com/paper/a-general-optimization-framework-for-multi	A General Optimization Framework for Multi-Document Summarization Using Genetic Algorithms and Swarm Intelligence	null	https://aclanthology.org/C16-1024	https://aclanthology.org/C16-1024.pdf	https://github.com/UKPLab/coling2016-genetic-swarm-MDS	true	true	false	none
https://paperswithcode.com/paper/improving-low-resource-neural-machine	Improving Low-Resource Neural Machine Translation with Filtered Pseudo-Parallel Corpus	null	https://aclanthology.org/W17-5704	https://aclanthology.org/W17-5704.pdf	https://github.com/aizhanti/filtered-pseudo-parallel-corpora	true	true	false	none
https://paperswithcode.com/paper/resnet-with-one-neuron-hidden-layers-is-a	ResNet with one-neuron hidden layers is a Universal Approximator	1806.10909	http://arxiv.org/abs/1806.10909v2	http://arxiv.org/pdf/1806.10909v2.pdf	https://github.com/sivakon/resnet-approximator	false	false	true	none
https://paperswithcode.com/paper/fourier-pca-and-robust-tensor-decomposition	Fourier PCA and Robust Tensor Decomposition	1306.5825	http://arxiv.org/abs/1306.5825v5	http://arxiv.org/pdf/1306.5825v5.pdf	https://github.com/yingusxiaous/libFPCA	false	false	true	none
https://paperswithcode.com/paper/non-convex-global-minimization-and-false	Non-convex Global Minimization and False Discovery Rate Control for the TREX	1604.06815	http://arxiv.org/abs/1604.06815v2	http://arxiv.org/pdf/1604.06815v2.pdf	https://github.com/muellsen/TREX	true	true	false	none
https://paperswithcode.com/paper/pruning-convolutional-neural-networks-for	Pruning Convolutional Neural Networks for Resource Efficient Inference	1611.06440	http://arxiv.org/abs/1611.06440v2	http://arxiv.org/pdf/1611.06440v2.pdf	https://github.com/dongkwan-kim/Adaptive-Forgetting	false	false	true	tf
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/GitHberChen/FCN-Pytorch	false	false	true	pytorch
https://paperswithcode.com/paper/automatic-skin-lesion-segmentation-on	Automatic skin lesion segmentation on dermoscopic images by the means of superpixel merging	1808.06759	http://arxiv.org/abs/1808.06759v1	http://arxiv.org/pdf/1808.06759v1.pdf	https://github.com/dipaco/mole-classification	true	true	false	none
https://paperswithcode.com/paper/detecting-gang-involved-escalation-on-social	Detecting Gang-Involved Escalation on Social Media Using Context	1809.03632	http://arxiv.org/abs/1809.03632v1	http://arxiv.org/pdf/1809.03632v1.pdf	https://github.com/serinachang5/contextifier	true	true	false	none
https://paperswithcode.com/paper/180602449	Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning	1806.02449	http://arxiv.org/abs/1806.02449v2	http://arxiv.org/pdf/1806.02449v2.pdf	https://github.com/roamiri/pa_intf_RL	false	false	true	none
https://paperswithcode.com/paper/dimspan-transactional-frequent-subgraph	DIMSpan - Transactional Frequent Subgraph Mining with Distributed In-Memory Dataflow Systems	1703.01910	http://arxiv.org/abs/1703.01910v1	http://arxiv.org/pdf/1703.01910v1.pdf	https://github.com/fuboertech/gradoop	false	false	true	none
https://paperswithcode.com/paper/rand-walk-a-latent-variable-model-approach-to	A Latent Variable Model Approach to PMI-based Word Embeddings	1502.03520	https://arxiv.org/abs/1502.03520v8	https://arxiv.org/pdf/1502.03520v8.pdf	https://github.com/LivNLP/Relational-Walk-for-Knowledge-Graphs	false	false	true	tf
https://paperswithcode.com/paper/proximal-policy-optimization-algorithms	Proximal Policy Optimization Algorithms	1707.06347	http://arxiv.org/abs/1707.06347v2	http://arxiv.org/pdf/1707.06347v2.pdf	https://github.com/sc2crazy/StarCrackRL	false	false	true	tf
https://paperswithcode.com/paper/fast-neural-architecture-search-of-compact	Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells	1810.10804	https://arxiv.org/abs/1810.10804v3	https://arxiv.org/pdf/1810.10804v3.pdf	https://github.com/drsleep/nas-segm-pytorch	true	true	true	pytorch
https://paperswithcode.com/paper/east-an-efficient-and-accurate-scene-text	EAST: An Efficient and Accurate Scene Text Detector	1704.03155	http://arxiv.org/abs/1704.03155v2	http://arxiv.org/pdf/1704.03155v2.pdf	https://github.com/BruceChanJianLe/Image-Text-Recognition	false	false	true	none
https://paperswithcode.com/paper/visual-interpretability-for-deep-learning-a	Visual Interpretability for Deep Learning: a Survey	1802.00614	http://arxiv.org/abs/1802.00614v2	http://arxiv.org/pdf/1802.00614v2.pdf	https://github.com/JepsonWong/CNN_Visualization	false	false	true	none
https://paperswithcode.com/paper/perturbative-gan-gan-with-perturbation-layers	Perturbative GAN: GAN with Perturbation Layers	1902.01514	http://arxiv.org/abs/1902.01514v1	http://arxiv.org/pdf/1902.01514v1.pdf	https://github.com/obake2ai/Obake-GAN	false	false	true	pytorch
https://paperswithcode.com/paper/ranger-a-fast-implementation-of-random	ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R	1508.04409	http://arxiv.org/abs/1508.04409v2	http://arxiv.org/pdf/1508.04409v2.pdf	https://github.com/mayer79/missRanger	false	false	true	none
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition	Deep Residual Learning for Image Recognition	1512.03385	http://arxiv.org/abs/1512.03385v1	http://arxiv.org/pdf/1512.03385v1.pdf	https://github.com/alililia/ms_extend/tree/main/gpu_resnet	false	false	false	mindspore
https://paperswithcode.com/paper/paying-attention-to-descriptions-generated-by	Paying Attention to Descriptions Generated by Image Captioning Models	1704.07434	http://arxiv.org/abs/1704.07434v3	http://arxiv.org/pdf/1704.07434v3.pdf	https://github.com/rakshithShetty/captionGAN	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.