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/topical-topic-pages-automagically	TOPICAL: TOPIC Pages AutomagicaLly	2405.01796	https://arxiv.org/abs/2405.01796v1	https://arxiv.org/pdf/2405.01796v1.pdf	https://github.com/allenai/topical	true	true	true	none
https://paperswithcode.com/paper/hard-thresholding-meets-evolution-strategies	Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning	2405.01615	https://arxiv.org/abs/2405.01615v1	https://arxiv.org/pdf/2405.01615v1.pdf	https://github.com/cangcn/nes-ht	true	true	true	none
https://paperswithcode.com/paper/fast-wave-slow-wave-spectral-deferred	Fast-wave slow-wave spectral deferred correction methods applied to the compressible Euler equations	2505.15985	https://arxiv.org/abs/2505.15985v1	https://arxiv.org/pdf/2505.15985v1.pdf	https://github.com/firedrakeproject/gusto	true	true	false	none
https://paperswithcode.com/paper/balance-reward-and-safety-optimization-for	Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation	2405.01677	https://arxiv.org/abs/2405.01677v2	https://arxiv.org/pdf/2405.01677v2.pdf	https://github.com/pku-alignment/omnisafe	true	true	false	pytorch
https://paperswithcode.com/paper/reconstructions-of-jupiter-s-magnetic-field	Reconstructions of Jupiter's magnetic field using physics informed neural networks	2403.07507	https://arxiv.org/abs/2403.07507v2	https://arxiv.org/pdf/2403.07507v2.pdf	https://github.com/LeyuanWu/JunoMag_PINN_VP3	true	false	false	none
https://paperswithcode.com/paper/language-model-based-paired-variational	Language Model-Based Paired Variational Autoencoders for Robotic Language Learning	2201.06317	https://arxiv.org/abs/2201.06317v2	https://arxiv.org/pdf/2201.06317v2.pdf	https://github.com/oo222bs/PVAE-BERT	true	true	false	pytorch
https://paperswithcode.com/paper/recurrent-variational-network-a-deep-learning	Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction	2111.09639	https://arxiv.org/abs/2111.09639v2	https://arxiv.org/pdf/2111.09639v2.pdf	https://github.com/directgroup/direct	true	true	true	pytorch
https://paperswithcode.com/paper/state-of-the-art-machine-learning-mri	Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction	2012.06318	https://arxiv.org/abs/2012.06318v3	https://arxiv.org/pdf/2012.06318v3.pdf	https://github.com/directgroup/direct	true	true	true	pytorch
https://paperswithcode.com/paper/auto-encoding-variational-bayes-for-inferring	Auto-Encoding Variational Bayes for Inferring Topics and Visualization	2010.09233	https://arxiv.org/abs/2010.09233v2	https://arxiv.org/pdf/2010.09233v2.pdf	https://github.com/dangpnh2/plsv_vae	true	true	true	pytorch
https://paperswithcode.com/paper/topology-dynamics-and-control-of-an-octopus	Topology, dynamics, and control of an octopus-analog muscular hydrostat	2304.08413	https://arxiv.org/abs/2304.08413v1	https://arxiv.org/pdf/2304.08413v1.pdf	https://github.com/GazzolaLab/PyElastica	false	false	true	none
https://paperswithcode.com/paper/paif-perception-aware-infrared-visible-image	PAIF: Perception-Aware Infrared-Visible Image Fusion for Attack-Tolerant Semantic Segmentation	2308.03979	https://arxiv.org/abs/2308.03979v1	https://arxiv.org/pdf/2308.03979v1.pdf	https://github.com/LiuZhu-CV/BDLFusion	false	false	true	pytorch
https://paperswithcode.com/paper/identifying-linear-relational-concepts-in	Identifying Linear Relational Concepts in Large Language Models	2311.08968	https://arxiv.org/abs/2311.08968v2	https://arxiv.org/pdf/2311.08968v2.pdf	https://github.com/chanind/linear-relational	false	false	true	pytorch
https://paperswithcode.com/paper/supervised-multiple-kernel-learning	Supervised Multiple Kernel Learning approaches for multi-omics data integration	2403.18355	https://arxiv.org/abs/2403.18355v2	https://arxiv.org/pdf/2403.18355v2.pdf	https://github.com/gabrieletaz/mkl_mo	true	true	false	pytorch
https://paperswithcode.com/paper/a-real-time-rescheduling-algorithm-for-multi	A Real-Time Rescheduling Algorithm for Multi-robot Plan Execution	2403.18145	https://arxiv.org/abs/2403.18145v1	https://arxiv.org/pdf/2403.18145v1.pdf	https://github.com/YinggggFeng/Switchable-Edge-Search	true	false	false	none
https://paperswithcode.com/paper/lstm-a-search-space-odyssey	LSTM: A Search Space Odyssey	1503.04069	http://arxiv.org/abs/1503.04069v2	http://arxiv.org/pdf/1503.04069v2.pdf	https://github.com/yangyucheng000/papercode-2/tree/main/lstm-gaf	false	false	false	mindspore
https://paperswithcode.com/paper/a-computational-approach-to-the-kiefer-weiss	A computational approach to the Kiefer-Weiss problem for sampling from a Bernoulli population	2110.04802	https://arxiv.org/abs/2110.04802v1	https://arxiv.org/pdf/2110.04802v1.pdf	https://github.com/tosinabase/Kiefer-Weiss	true	true	true	none
https://paperswithcode.com/paper/geocov19-a-dataset-of-hundreds-of-millions-of	GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information	2005.11177	https://arxiv.org/abs/2005.11177v1	https://arxiv.org/pdf/2005.11177v1.pdf	https://github.com/vaceslav/cuda	false	false	true	none
https://paperswithcode.com/paper/qserve-w4a8kv4-quantization-and-system-co	QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving	2405.04532	https://arxiv.org/abs/2405.04532v3	https://arxiv.org/pdf/2405.04532v3.pdf	https://github.com/mit-han-lab/omniserve	true	true	true	pytorch
https://paperswithcode.com/paper/are-llms-good-zero-shot-fallacy-classifiers	Are LLMs Good Zero-Shot Fallacy Classifiers?	2410.15050	https://arxiv.org/abs/2410.15050v1	https://arxiv.org/pdf/2410.15050v1.pdf	https://github.com/panfjcharlotte98/fallacy_detection	true	true	false	pytorch
https://paperswithcode.com/paper/the-quantified-boolean-bayesian-network	The Quantified Boolean Bayesian Network: Theory and Experiments with a Logical Graphical Model	2402.06557	https://arxiv.org/abs/2402.06557v1	https://arxiv.org/pdf/2402.06557v1.pdf	https://github.com/gregorycoppola/bayes-star	true	true	true	none
https://paperswithcode.com/paper/u-slads-unsupervised-learning-approach-for	U-SLADS: Unsupervised Learning Approach for Dynamic Dendrite Sampling	1807.02233	http://arxiv.org/abs/1807.02233v1	http://arxiv.org/pdf/1807.02233v1.pdf	https://github.com/yatagarasu50469/slads	false	false	true	tf
https://paperswithcode.com/paper/deep-learning-approach-for-dynamic-sampling	Deep Learning Approach for Dynamic Sampling for Multichannel Mass Spectrometry Imaging	2210.13415	https://arxiv.org/abs/2210.13415v1	https://arxiv.org/pdf/2210.13415v1.pdf	https://github.com/yatagarasu50469/slads	true	true	true	tf
https://paperswithcode.com/paper/safe-unlearning-a-surprisingly-effective-and	From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks	2407.02855	https://arxiv.org/abs/2407.02855v3	https://arxiv.org/pdf/2407.02855v3.pdf	https://github.com/thu-coai/safeunlearning	true	true	true	pytorch
https://paperswithcode.com/paper/robust-blockchained-federated-learning-with	Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus	2101.03300	https://arxiv.org/abs/2101.03300v1	https://arxiv.org/pdf/2101.03300v1.pdf	https://github.com/flexible-fl/flex-block	false	false	true	none
https://paperswithcode.com/paper/thoughtsculpt-reasoning-with-intermediate	THOUGHTSCULPT: Reasoning with Intermediate Revision and Search	2404.05966	https://arxiv.org/abs/2404.05966v1	https://arxiv.org/pdf/2404.05966v1.pdf	https://github.com/cyzus/thoughtsculpt	true	true	true	none
https://paperswithcode.com/paper/the-pile-an-800gb-dataset-of-diverse-text-for	The Pile: An 800GB Dataset of Diverse Text for Language Modeling	2101.00027	https://arxiv.org/abs/2101.00027v1	https://arxiv.org/pdf/2101.00027v1.pdf	https://github.com/glassroom/heinsen_attention	false	false	true	pytorch
https://paperswithcode.com/paper/arithmetic-transformers-can-length-generalize	Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count	2410.15787	https://arxiv.org/abs/2410.15787v2	https://arxiv.org/pdf/2410.15787v2.pdf	https://github.com/hanseuljo/position-coupling	true	true	true	pytorch
https://paperswithcode.com/paper/universal-and-transferable-adversarial	Universal and Transferable Adversarial Attacks on Aligned Language Models	2307.15043	https://arxiv.org/abs/2307.15043v2	https://arxiv.org/pdf/2307.15043v2.pdf	https://github.com/thu-coai/safeunlearning	false	false	true	pytorch
https://paperswithcode.com/paper/automatic-restoration-of-diacritics-for	Automatic Restoration of Diacritics for Speech Data Sets	2311.10771	https://arxiv.org/abs/2311.10771v2	https://arxiv.org/pdf/2311.10771v2.pdf	https://github.com/sarashatnawi/diacritization	true	true	true	tf
https://paperswithcode.com/paper/flea-addressing-data-scarcity-and-label-skew	FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation	2406.09547	https://arxiv.org/abs/2406.09547v2	https://arxiv.org/pdf/2406.09547v2.pdf	https://github.com/xtxiatong/flea	true	true	false	pytorch
https://paperswithcode.com/paper/reasoning-rcnn-unifying-adaptive-global	Reasoning-RCNN: Unifying Adaptive Global Reasoning Into Large-Scale Object Detection	null	http://openaccess.thecvf.com/content_CVPR_2019/html/Xu_Reasoning-RCNN_Unifying_Adaptive_Global_Reasoning_Into_Large-Scale_Object_Detection_CVPR_2019_paper.html	http://openaccess.thecvf.com/content_CVPR_2019/papers/Xu_Reasoning-RCNN_Unifying_Adaptive_Global_Reasoning_Into_Large-Scale_Object_Detection_CVPR_2019_paper.pdf	https://github.com/chanyn/Reasoning-RCNN	true	false	false	pytorch
https://paperswithcode.com/paper/minmaxlttb-leveraging-minmax-preselection-to	MinMaxLTTB: Leveraging MinMax-Preselection to Scale LTTB	2305.00332	https://arxiv.org/abs/2305.00332v1	https://arxiv.org/pdf/2305.00332v1.pdf	https://github.com/predict-idlab/tsdownsample	true	true	true	none
https://paperswithcode.com/paper/efficient-computation-of-the-quantum-rate	Efficient Computation of the Quantum Rate-Distortion Function	2309.15919	https://arxiv.org/abs/2309.15919v3	https://arxiv.org/pdf/2309.15919v3.pdf	https://github.com/kerry-he/efficient-qrd	true	true	true	none
https://paperswithcode.com/paper/vimts-a-unified-video-and-image-text-spotter	VimTS: A Unified Video and Image Text Spotter for Enhancing the Cross-domain Generalization	2404.19652	https://arxiv.org/abs/2404.19652v4	https://arxiv.org/pdf/2404.19652v4.pdf	https://github.com/Yuliang-Liu/VimTS	true	false	true	pytorch
https://paperswithcode.com/paper/random-pareto-front-surfaces	Random Pareto front surfaces	2405.01404	https://arxiv.org/abs/2405.01404v2	https://arxiv.org/pdf/2405.01404v2.pdf	https://github.com/benmltu/scalarize	true	true	true	pytorch
https://paperswithcode.com/paper/texttt-pyresias-how-to-write-a-toy-parton	$\texttt{Pyresias}$: How To Write a Toy Parton Shower	2406.03528	https://arxiv.org/abs/2406.03528v1	https://arxiv.org/pdf/2406.03528v1.pdf	https://github.com/apapaefs/pyresias	true	true	true	none
https://paperswithcode.com/paper/benchmarking-node-outlier-detection-on-graphs	BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs	2206.10071	https://arxiv.org/abs/2206.10071v2	https://arxiv.org/pdf/2206.10071v2.pdf	https://github.com/betterzhou/AAGNN	false	false	true	pytorch
https://paperswithcode.com/paper/privacy-preserving-diffusion-model-using	Privacy-Preserving Diffusion Model Using Homomorphic Encryption	2403.05794	https://arxiv.org/abs/2403.05794v2	https://arxiv.org/pdf/2403.05794v2.pdf	https://github.com/HE-diffusion/HE-diffusion	true	false	false	pytorch
https://paperswithcode.com/paper/towards-a-generic-compilation-approach-for	A Comparison of Quantum Compilers using a DAG-based or phase polynomial-based Intermediate Representation	2304.08814	https://arxiv.org/abs/2304.08814v2	https://arxiv.org/pdf/2304.08814v2.pdf	https://github.com/daehiff/pauliopt	false	false	true	none
https://paperswithcode.com/paper/annealing-optimisation-of-mixed-zx-phase	Annealing Optimisation of Mixed ZX Phase Circuits	2206.11839	https://arxiv.org/abs/2206.11839v2	https://arxiv.org/pdf/2206.11839v2.pdf	https://github.com/daehiff/pauliopt	false	false	true	none
https://paperswithcode.com/paper/architecture-aware-synthesis-of-stabilizer	Architecture-Aware Synthesis of Stabilizer Circuits from Clifford Tableaus	2309.08972	https://arxiv.org/abs/2309.08972v3	https://arxiv.org/pdf/2309.08972v3.pdf	https://github.com/daehiff/pauliopt	true	true	true	none
https://paperswithcode.com/paper/spectral-methods-for-neural-integral	Spectral methods for Neural Integral Equations	2312.05654	https://arxiv.org/abs/2312.05654v3	https://arxiv.org/pdf/2312.05654v3.pdf	https://github.com/emazap7/spectral_nie	true	true	true	pytorch
https://paperswithcode.com/paper/hint-healthy-influential-noise-based-training	HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks	2309.08549	https://arxiv.org/abs/2309.08549v3	https://arxiv.org/pdf/2309.08549v3.pdf	https://github.com/minhhao97vn/hint	true	true	true	pytorch
https://paperswithcode.com/paper/differentiable-all-pole-filters-for-time	Differentiable All-pole Filters for Time-varying Audio Systems	2404.07970	https://arxiv.org/abs/2404.07970v4	https://arxiv.org/pdf/2404.07970v4.pdf	https://github.com/DiffAPF/torchcomp	true	false	false	pytorch
https://paperswithcode.com/paper/iisan-efficiently-adapting-multimodal	IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT	2404.02059	https://arxiv.org/abs/2404.02059v3	https://arxiv.org/pdf/2404.02059v3.pdf	https://github.com/gair-lab/iisan	true	true	true	pytorch
https://paperswithcode.com/paper/long-term-fairness-in-sequential-multi-agent	Long-Term Fairness in Sequential Multi-Agent Selection with Positive Reinforcement	2407.07350	https://arxiv.org/abs/2407.07350v1	https://arxiv.org/pdf/2407.07350v1.pdf	https://github.com/guldoganozgur/long_term_fairness_pos_reinf	true	false	false	none
https://paperswithcode.com/paper/rade-gs-rasterizing-depth-in-gaussian	RaDe-GS: Rasterizing Depth in Gaussian Splatting	2406.01467	https://arxiv.org/abs/2406.01467v2	https://arxiv.org/pdf/2406.01467v2.pdf	https://github.com/BaowenZ/RaDe-GS	true	false	false	pytorch
https://paperswithcode.com/paper/preliminary-wmt24-ranking-of-general-mt	Preliminary WMT24 Ranking of General MT Systems and LLMs	2407.19884	https://arxiv.org/abs/2407.19884v1	https://arxiv.org/pdf/2407.19884v1.pdf	https://github.com/wmt-conference/wmt-collect-translations	true	false	false	none
https://paperswithcode.com/paper/tight-fusion-of-events-and-inertial	Tight Fusion of Events and Inertial Measurements for Direct Velocity Estimation	2401.09296	https://arxiv.org/abs/2401.09296v1	https://arxiv.org/pdf/2401.09296v1.pdf	https://github.com/uzh-rpg/event-based_vision_resources	true	true	true	pytorch
https://paperswithcode.com/paper/specter-an-instrument-concept-for-cmb	SPECTER: An Instrument Concept for CMB Spectral Distortion Measurements with Enhanced Sensitivity	2409.12188	https://arxiv.org/abs/2409.12188v1	https://arxiv.org/pdf/2409.12188v1.pdf	https://github.com/asabyr/specter_optimization	true	false	true	none
https://paperswithcode.com/paper/crosslocate-cross-modal-large-scale-visual	CrossLocate: Cross-modal Large-scale Visual Geo-Localization in Natural Environments using Rendered Modalities	null	https://cphoto.fit.vutbr.cz/crosslocate/	https://cphoto.fit.vutbr.cz/crosslocate/data/paper/CrossLocate.pdf	https://github.com/JanTomesek/CrossLocate	false	false	false	tf
https://paperswithcode.com/paper/semi-siamese-bi-encoder-neural-ranking-model	Semi-Siamese Bi-encoder Neural Ranking Model Using Lightweight Fine-Tuning	2110.14943	https://arxiv.org/abs/2110.14943v2	https://arxiv.org/pdf/2110.14943v2.pdf	https://github.com/xlpczv/semi_siamese	true	true	true	jax
https://paperswithcode.com/paper/3dmasc-accessible-explainable-3d-point-clouds	3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar data	2401.09481	https://arxiv.org/abs/2401.09481v1	https://arxiv.org/pdf/2401.09481v1.pdf	https://github.com/Rennes-LiDAR-Platform/lidar_platform	true	false	false	none
https://paperswithcode.com/paper/ladic-are-diffusion-models-really-inferior-to	LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?	2404.10763	https://arxiv.org/abs/2404.10763v1	https://arxiv.org/pdf/2404.10763v1.pdf	https://github.com/wangyuchi369/ladic	true	true	true	jax
https://paperswithcode.com/paper/analytical-approximation-of-the-elbo-gradient	Analytical Approximation of the ELBO Gradient in the Context of the Clutter Problem	2404.10550	https://arxiv.org/abs/2404.10550v3	https://arxiv.org/pdf/2404.10550v3.pdf	https://github.com/rpopov42/elbo_gaa	true	true	true	none
https://paperswithcode.com/paper/explingo-explaining-ai-predictions-using	Explingo: Explaining AI Predictions using Large Language Models	2412.05145	https://arxiv.org/abs/2412.05145v1	https://arxiv.org/pdf/2412.05145v1.pdf	https://github.com/sibyl-dev/pyreal	true	true	false	none
https://paperswithcode.com/paper/differentially-private-sgd-without-clipping	Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach	2311.14632	https://arxiv.org/abs/2311.14632v2	https://arxiv.org/pdf/2311.14632v2.pdf	https://github.com/564612540/DiceSGD	true	false	false	pytorch
https://paperswithcode.com/paper/exploiting-inter-layer-expert-affinity-for	Exploiting Inter-Layer Expert Affinity for Accelerating Mixture-of-Experts Model Inference	2401.08383	https://arxiv.org/abs/2401.08383v2	https://arxiv.org/pdf/2401.08383v2.pdf	https://github.com/yjhmitweb/exflow	true	true	true	none
https://paperswithcode.com/paper/multimodal-machine-learning-combining-facial	GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Texts	2312.15320	https://arxiv.org/abs/2312.15320v2	https://arxiv.org/pdf/2312.15320v2.pdf	https://github.com/wglab/gestaltmml-gestaltgpt	true	true	true	pytorch
https://paperswithcode.com/paper/linear-time-one-class-classification-with	Linear-time One-Class Classification with Repeated Element-wise Folding	2408.11412	https://arxiv.org/abs/2408.11412v1	https://arxiv.org/pdf/2408.11412v1.pdf	https://github.com/jenniraitoharju/ref	true	true	false	none
https://paperswithcode.com/paper/dyport-dynamic-importance-based-hypothesis	Dyport: Dynamic Importance-based Hypothesis Generation Benchmarking Technique	2312.03303	https://arxiv.org/abs/2312.03303v1	https://arxiv.org/pdf/2312.03303v1.pdf	https://github.com/ilyatyagin/dyport	true	true	true	none
https://paperswithcode.com/paper/neural-image-compression-with-text-guided	Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity	2403.02944	https://arxiv.org/abs/2403.02944v2	https://arxiv.org/pdf/2403.02944v2.pdf	https://github.com/effl-lab/taco	true	true	true	pytorch
https://paperswithcode.com/paper/real-time-flying-object-detection-with-yolov8	Real-Time Flying Object Detection with YOLOv8	2305.09972	https://arxiv.org/abs/2305.09972v2	https://arxiv.org/pdf/2305.09972v2.pdf	https://github.com/dillonreis/real-time-flying-object-detection_with_yolov8	true	true	false	none
https://paperswithcode.com/paper/generating-causal-explanations-of-vehicular	Generating Causal Explanations of Vehicular Agent Behavioural Interactions with Learnt Reward Profiles	2503.14557	https://arxiv.org/abs/2503.14557v1	https://arxiv.org/pdf/2503.14557v1.pdf	https://github.com/cognitive-robots/gce_vbai_lrp_paper_resources	true	false	false	none
https://paperswithcode.com/paper/exact-information-bottleneck-with-invertible	Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification	2001.06448	https://arxiv.org/abs/2001.06448v5	https://arxiv.org/pdf/2001.06448v5.pdf	https://github.com/VLL-HD/FrEIA	true	true	true	pytorch
https://paperswithcode.com/paper/fer-yolo-mamba-facial-expression-detection	FER-YOLO-Mamba: Facial Expression Detection and Classification Based on Selective State Space	2405.01828	https://arxiv.org/abs/2405.01828v3	https://arxiv.org/pdf/2405.01828v3.pdf	https://github.com/swjtuma/fer-yolo-mamba	true	true	true	pytorch
https://paperswithcode.com/paper/reshuffling-resampling-splits-can-improve	Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization	2405.15393	https://arxiv.org/abs/2405.15393v2	https://arxiv.org/pdf/2405.15393v2.pdf	https://github.com/sumny/reshuffling	true	false	true	none
https://paperswithcode.com/paper/venomancer-towards-imperceptible-and-target	Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning	2407.03144	https://arxiv.org/abs/2407.03144v2	https://arxiv.org/pdf/2407.03144v2.pdf	https://github.com/nguyenhongson1902/venomancer	true	true	false	pytorch
https://paperswithcode.com/paper/gradient-boosting-reinforcement-learning	Gradient Boosting Reinforcement Learning	2407.08250	https://arxiv.org/abs/2407.08250v1	https://arxiv.org/pdf/2407.08250v1.pdf	https://github.com/nvlabs/gbrl	true	true	true	pytorch
https://paperswithcode.com/paper/a-network-based-measure-of-cosponsorship	A Network-Based Measure of Cosponsorship Influence on Bill Passing in the United States House of Representatives	2406.19554	https://arxiv.org/abs/2406.19554v1	https://arxiv.org/pdf/2406.19554v1.pdf	https://github.com/sarahsotoudeh/LegislativeInfluence	true	true	false	none
https://paperswithcode.com/paper/improving-cross-domain-few-shot	Improving Cross-domain Few-shot Classification with Multilayer Perceptron	2312.09589	https://arxiv.org/abs/2312.09589v1	https://arxiv.org/pdf/2312.09589v1.pdf	https://github.com/BaiShuanghao/CDFSC-MLP	true	false	true	pytorch
https://paperswithcode.com/paper/jup2kub-algorithms-and-a-system-to-translate	Jup2Kub: algorithms and a system to translate a Jupyter Notebook pipeline to a fault tolerant distributed Kubernetes deployment	2311.12308	https://arxiv.org/abs/2311.12308v1	https://arxiv.org/pdf/2311.12308v1.pdf	https://github.com/shirou10086/scientificworkflow	true	true	true	none
https://paperswithcode.com/paper/energy-based-sliced-wasserstein-distance-1	Energy-Based Sliced Wasserstein Distance	2304.13586	https://arxiv.org/abs/2304.13586v3	https://arxiv.org/pdf/2304.13586v3.pdf	https://github.com/khainb/ebsw	true	true	true	pytorch
https://paperswithcode.com/paper/poker-hand-history-file-format-specification	Recording and Describing Poker Hands	2312.11753	https://arxiv.org/abs/2312.11753v5	https://arxiv.org/pdf/2312.11753v5.pdf	https://github.com/uoftcprg/phh-std	true	true	false	none
https://paperswithcode.com/paper/scalable-cross-entropy-loss-for-sequential	Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs	2409.18721	https://arxiv.org/abs/2409.18721v2	https://arxiv.org/pdf/2409.18721v2.pdf	https://github.com/AIRI-Institute/Scalable-SASRec	true	false	true	pytorch
https://paperswithcode.com/paper/free-surgs-sfm-free-3d-gaussian-splatting-for	Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstruction	2407.02918	https://arxiv.org/abs/2407.02918v1	https://arxiv.org/pdf/2407.02918v1.pdf	https://github.com/wrld/free-surgs	true	true	true	jax
https://paperswithcode.com/paper/growing-artificial-neural-networks-for	Growing Artificial Neural Networks for Control: the Role of Neuronal Diversity	2405.08510	https://arxiv.org/abs/2405.08510v1	https://arxiv.org/pdf/2405.08510v1.pdf	https://github.com/eleninisioti/GrowNeuralNets	true	true	false	jax
https://paperswithcode.com/paper/secml-a-python-library-for-secure-and	secml: A Python Library for Secure and Explainable Machine Learning	1912.10013	https://arxiv.org/abs/1912.10013v2	https://arxiv.org/pdf/1912.10013v2.pdf	https://github.com/pralab/secml	true	true	true	pytorch
https://paperswithcode.com/paper/image-coding-for-machines-with-edge	Image Coding for Machines with Edge Information Learning Using Segment Anything	2403.04173	https://arxiv.org/abs/2403.04173v3	https://arxiv.org/pdf/2403.04173v3.pdf	https://github.com/final-0/sa-icm	true	true	true	pytorch
https://paperswithcode.com/paper/p-bench-a-multi-level-privacy-evaluation	PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models	2311.04044	https://arxiv.org/abs/2311.04044v3	https://arxiv.org/pdf/2311.04044v3.pdf	https://github.com/hkust-knowcomp/privlm-bench	true	true	false	pytorch
https://paperswithcode.com/paper/denseseg-joint-learning-for-semantic	DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape Representation	2405.19746	https://arxiv.org/abs/2405.19746v2	https://arxiv.org/pdf/2405.19746v2.pdf	https://github.com/MDL-UzL/DenseSeg	true	true	false	pytorch
https://paperswithcode.com/paper/elastic-feature-consolidation-for-cold-start	Elastic Feature Consolidation for Cold Start Exemplar-Free Incremental Learning	2402.03917	https://arxiv.org/abs/2402.03917v3	https://arxiv.org/pdf/2402.03917v3.pdf	https://github.com/simomagi/elastic_feature_consolidation	true	true	true	pytorch
https://paperswithcode.com/paper/cpsycoun-a-report-based-multi-turn-dialogue	CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling	2405.16433	https://arxiv.org/abs/2405.16433v3	https://arxiv.org/pdf/2405.16433v3.pdf	https://github.com/cas-siat-xinhai/cpsycoun	true	true	true	none
https://paperswithcode.com/paper/improved-techniques-for-training-score-based	Improved Techniques for Training Score-Based Generative Models	2006.09011	https://arxiv.org/abs/2006.09011v2	https://arxiv.org/pdf/2006.09011v2.pdf	https://github.com/tpresser570/Lambert-Diffusion	false	false	true	pytorch
https://paperswithcode.com/paper/folded-spectrum-vqe-a-quantum-computing	Folded Spectrum VQE : A quantum computing method for the calculation of molecular excited states	2305.04783	https://arxiv.org/abs/2305.04783v2	https://arxiv.org/pdf/2305.04783v2.pdf	https://github.com/ichen17/Qhack2024-project	false	false	true	none
https://paperswithcode.com/paper/dormant-defending-against-pose-driven-human	Dormant: Defending against Pose-driven Human Image Animation	2409.14424	https://arxiv.org/abs/2409.14424v2	https://arxiv.org/pdf/2409.14424v2.pdf	https://github.com/Manu21JC/Dormant	true	false	false	pytorch
https://paperswithcode.com/paper/tart-an-open-source-tool-augmented-framework	TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning	2409.11724	https://arxiv.org/abs/2409.11724v2	https://arxiv.org/pdf/2409.11724v2.pdf	https://github.com/xinyuanlu00/tart	true	true	true	none
https://paperswithcode.com/paper/chibench-a-benchmark-suite-for-testing	ChiBench: a Benchmark Suite for Testing Electronic Design Automation Tools	2406.06550	https://arxiv.org/abs/2406.06550v1	https://arxiv.org/pdf/2406.06550v1.pdf	https://github.com/lac-dcc/chimera	true	true	true	none
https://paperswithcode.com/paper/federated-learning-you-may-communicate-less	Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!	2306.05862	https://arxiv.org/abs/2306.05862v2	https://arxiv.org/pdf/2306.05862v2.pdf	https://github.com/romainchor/generalization_fl_icml2024	true	true	true	pytorch
https://paperswithcode.com/paper/a-deep-dive-into-the-distribution-function	A Deep Dive into the Distribution Function: Understanding Phase Space Dynamics with Continuum Vlasov-Maxwell Simulations	2005.13539	https://arxiv.org/abs/2005.13539v1	https://arxiv.org/pdf/2005.13539v1.pdf	https://github.com/ammarhakim/gkyl-paper-inp	true	true	true	none
https://paperswithcode.com/paper/occ-vo-dense-mapping-via-3d-occupancy-based	OCC-VO: Dense Mapping via 3D Occupancy-Based Visual Odometry for Autonomous Driving	2309.11011	https://arxiv.org/abs/2309.11011v2	https://arxiv.org/pdf/2309.11011v2.pdf	https://github.com/ustclh/occ-vo	true	true	true	pytorch
https://paperswithcode.com/paper/mammalps-a-multi-view-video-behavior	MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps	2503.18223	https://arxiv.org/abs/2503.18223v2	https://arxiv.org/pdf/2503.18223v2.pdf	https://github.com/eceo-epfl/mammalps	true	true	false	none
https://paperswithcode.com/paper/learning-to-iteratively-solve-routing	Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer	2110.02544	https://arxiv.org/abs/2110.02544v3	https://arxiv.org/pdf/2110.02544v3.pdf	https://github.com/yining043/VRP-DACT	true	true	true	pytorch
https://paperswithcode.com/paper/fair-classification-with-partial-feedback-an	Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach	2402.11338	https://arxiv.org/abs/2402.11338v2	https://arxiv.org/pdf/2402.11338v2.pdf	https://github.com/vijaykeswani/fair-classification-with-partial-feedback	true	true	true	none
https://paperswithcode.com/paper/nfi-2-learning-noise-free-illuminance	Advancing Unsupervised Low-light Image Enhancement: Noise Estimation, Illumination Interpolation, and Self-Regulation	2305.10223	https://arxiv.org/abs/2305.10223v4	https://arxiv.org/pdf/2305.10223v4.pdf	https://github.com/googolplexgoodenough/noise_estimate	true	true	false	none
https://paperswithcode.com/paper/mad-multi-alignment-meg-to-text-decoding	MAD: Multi-Alignment MEG-to-Text Decoding	2406.01512	https://arxiv.org/abs/2406.01512v1	https://arxiv.org/pdf/2406.01512v1.pdf	https://github.com/neuspeech/mad-meg2text	true	true	true	pytorch
https://paperswithcode.com/paper/nerf-supervised-feature-point-detection-and	NeRF-Supervised Feature Point Detection and Description	2403.08156	https://arxiv.org/abs/2403.08156v3	https://arxiv.org/pdf/2403.08156v3.pdf	https://github.com/AliYoussef97/SuperPoint-PrP	true	false	true	pytorch
https://paperswithcode.com/paper/learning-adaptive-fusion-bank-for-multi-modal	Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection	2406.01127	https://arxiv.org/abs/2406.01127v1	https://arxiv.org/pdf/2406.01127v1.pdf	https://github.com/angknpng/lafb	true	true	true	pytorch
https://paperswithcode.com/paper/odgs-3d-scene-reconstruction-from	ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings	2410.20686	https://arxiv.org/abs/2410.20686v1	https://arxiv.org/pdf/2410.20686v1.pdf	https://github.com/esw0116/odgs	true	true	true	none
https://paperswithcode.com/paper/neural-topic-models-with-survival-supervision	Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate	2007.07796	https://arxiv.org/abs/2007.07796v2	https://arxiv.org/pdf/2007.07796v2.pdf	https://github.com/georgehc/survival-topics	true	true	true	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.