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/evaluating-uncertainty-in-deep-gaussian	Evaluating Uncertainty in Deep Gaussian Processes	2504.17719	https://arxiv.org/abs/2504.17719v1	https://arxiv.org/pdf/2504.17719v1.pdf	https://github.com/matthjs/xai-gp	true	true	true	pytorch
https://paperswithcode.com/paper/to-match-or-not-to-match-revisiting-image	To Match or Not to Match: Revisiting Image Matching for Reliable Visual Place Recognition	2504.06116	https://arxiv.org/abs/2504.06116v1	https://arxiv.org/pdf/2504.06116v1.pdf	https://github.com/FarInHeight/To-Match-or-Not-to-Match	true	false	true	pytorch
https://paperswithcode.com/paper/comparison-of-path-planning-algorithms-for	Comparison of Path Planning Algorithms for Autonomous Vehicle Navigation Using Satellite and Airborne LiDAR Data	2507.05884	https://arxiv.org/abs/2507.05884v1	https://arxiv.org/pdf/2507.05884v1.pdf	https://github.com/kuma990122/comparison-of-path-planning-algorithm-for-autonomous-vehicle-using-satellite-and-airborne-lidar-data	true	true	false	pytorch
https://paperswithcode.com/paper/computing-the-unitary-best-approximant-to-the	Computing the unitary best approximant to the exponential function	2504.10062	https://arxiv.org/abs/2504.10062v1	https://arxiv.org/pdf/2504.10062v1.pdf	https://github.com/newbisi/rexpi	true	true	true	none
https://paperswithcode.com/paper/unitary-rational-best-approximations-to-the	Unitary rational best approximations to the exponential function	2312.13809	https://arxiv.org/abs/2312.13809v1	https://arxiv.org/pdf/2312.13809v1.pdf	https://github.com/newbisi/rexpi	false	false	true	none
https://paperswithcode.com/paper/weakly-supervised-contrastive-learning-with	Weakly-supervised Contrastive Learning with Quantity Prompts for Moving Infrared Small Target Detection	2507.02454	https://arxiv.org/abs/2507.02454v1	https://arxiv.org/pdf/2507.02454v1.pdf	https://github.com/uestc-nnlab/wecol	true	true	false	pytorch
https://paperswithcode.com/paper/dnlut-ultra-efficient-color-image-denoising	DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup Tables	2503.15931	https://arxiv.org/abs/2503.15931v1	https://arxiv.org/pdf/2503.15931v1.pdf	https://github.com/stephen0808/dnlut	true	true	true	pytorch
https://paperswithcode.com/paper/lifelongpr-lifelong-knowledge-fusion-for	LifelongPR: Lifelong knowledge fusion for point cloud place recognition based on replay and prompt learning	2507.10034	https://arxiv.org/abs/2507.10034v1	https://arxiv.org/pdf/2507.10034v1.pdf	https://github.com/zouxianghong/LifelongPR	true	true	false	pytorch
https://paperswithcode.com/paper/unirag-universal-retrieval-augmentation-for	UniRAG: Universal Retrieval Augmentation for Large Vision Language Models	2405.10311	https://arxiv.org/abs/2405.10311v3	https://arxiv.org/pdf/2405.10311v3.pdf	https://github.com/castorini/unirag	true	true	true	pytorch
https://paperswithcode.com/paper/restormer-efficient-transformer-for-high	Restormer: Efficient Transformer for High-Resolution Image Restoration	2111.09881	https://arxiv.org/abs/2111.09881v2	https://arxiv.org/pdf/2111.09881v2.pdf	https://github.com/stephen0808/dnlut	false	false	true	pytorch
https://paperswithcode.com/paper/optimal-flock-formation-induced-by-agent	Optimal flock formation induced by agent heterogeneity	2504.12297	https://arxiv.org/abs/2504.12297v1	https://arxiv.org/pdf/2504.12297v1.pdf	https://github.com/montanariarthur/optflock	true	true	false	none
https://paperswithcode.com/paper/lemur-log-parsing-with-entropy-sampling-and	Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging	2402.18205	https://arxiv.org/abs/2402.18205v5	https://arxiv.org/pdf/2402.18205v5.pdf	https://github.com/knediny/lemur	true	true	true	none
https://paperswithcode.com/paper/lcpr-a-multi-scale-attention-based-lidar	LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place Recognition	2311.03198	https://arxiv.org/abs/2311.03198v2	https://arxiv.org/pdf/2311.03198v2.pdf	https://github.com/ZhouZijie77/LCPR	true	true	true	pytorch
https://paperswithcode.com/paper/weisfeiler-leman-in-the-bamboo-novel-amr-1	Weisfeiler-leman in the bamboo: Novel AMR graph metrics and a benchmark for AMR graph similarity.	null	https://aclanthology.org/2021.tacl-1.85/	https://aclanthology.org/2021.tacl-1.85.pdf	https://github.com/flipz357/bamboo-amr-benchmark	false	false	false	none
https://paperswithcode.com/paper/spectralgpt-spectral-foundation-model	SpectralGPT: Spectral Remote Sensing Foundation Model	2311.07113	https://arxiv.org/abs/2311.07113v3	https://arxiv.org/pdf/2311.07113v3.pdf	https://github.com/danfenghong/IEEE_TPAMI_SpectralGPT	false	false	false	pytorch
https://paperswithcode.com/paper/og-hfyolo-orientation-gradient-guidance-and	OG-HFYOLO :Orientation gradient guidance and heterogeneous feature fusion for deformation table cell instance segmentation	2504.20682	https://arxiv.org/abs/2504.20682v2	https://arxiv.org/pdf/2504.20682v2.pdf	https://github.com/justliulong/oghfyolo	true	true	true	pytorch
https://paperswithcode.com/paper/mobileposer-real-time-full-body-pose	MobilePoser: Real-Time Full-Body Pose Estimation and 3D Human Translation from IMUs in Mobile Consumer Devices	2504.12492	https://arxiv.org/abs/2504.12492v1	https://arxiv.org/pdf/2504.12492v1.pdf	https://github.com/SPICExLAB/MobilePoser	true	false	false	pytorch
https://paperswithcode.com/paper/enhancing-the-geometric-problem-solving	Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration	2504.12773	https://arxiv.org/abs/2504.12773v1	https://arxiv.org/pdf/2504.12773v1.pdf	https://github.com/ycpnotfound/geogen	true	true	true	none
https://paperswithcode.com/paper/meltdown-bridging-the-perception-gap-in	Meltdown: Bridging the Perception Gap in Sustainable Food Behaviors Through Immersive VR	2504.14324	https://arxiv.org/abs/2504.14324v1	https://arxiv.org/pdf/2504.14324v1.pdf	https://github.com/florentianayuwono/meltdown	true	true	true	none
https://paperswithcode.com/paper/projected-normal-distribution-moment	Projected Normal Distribution: Moment Approximations and Generalizations	2506.17461	https://arxiv.org/abs/2506.17461v1	https://arxiv.org/pdf/2506.17461v1.pdf	https://github.com/dherrera1911/projnormal	true	true	true	pytorch
https://paperswithcode.com/paper/stochastic-quadrature-rules-for-solving-pdes	Stochastic Quadrature Rules for Solving PDEs using Neural Networks	2504.11976	https://arxiv.org/abs/2504.11976v2	https://arxiv.org/pdf/2504.11976v2.pdf	https://github.com/jamie-m-taylor/Stochastic-Integration	true	true	false	tf
https://paperswithcode.com/paper/2505-10978	Group-in-Group Policy Optimization for LLM Agent Training	2505.10978	https://arxiv.org/abs/2505.10978v1	https://arxiv.org/pdf/2505.10978v1.pdf	https://github.com/langfengq/verl-agent	true	true	true	pytorch
https://paperswithcode.com/paper/2505-11455	ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network	2505.11455	https://arxiv.org/abs/2505.11455v1	https://arxiv.org/pdf/2505.11455v1.pdf	https://github.com/dgxdn/asrc-snn	true	true	false	pytorch
https://paperswithcode.com/paper/2505-11190	JaxSGMC: Modular stochastic gradient MCMC in JAX	2505.11190	https://arxiv.org/abs/2505.11190v1	https://arxiv.org/pdf/2505.11190v1.pdf	https://github.com/tummfm/jax-sgmc	true	true	false	jax
https://paperswithcode.com/paper/subspace-identification-of-temperature	Subspace Identification of Temperature Dynamics	1908.02379	https://arxiv.org/abs/1908.02379v1	https://arxiv.org/pdf/1908.02379v1.pdf	https://github.com/AleksandarHaber/Subspace-Identification-State-Space-System-Identification-of-Dynamical-Systems-and-Time-Series-	false	false	true	none
https://paperswithcode.com/paper/glm-4-1v-thinking-towards-versatile	GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning	2507.01006	https://arxiv.org/abs/2507.01006v2	https://arxiv.org/pdf/2507.01006v2.pdf	https://github.com/thudm/glm-4.1v-thinking	true	true	true	none
https://paperswithcode.com/paper/fundamental-limits-of-perfect-concept-erasure	Fundamental Limits of Perfect Concept Erasure	2503.20098	https://arxiv.org/abs/2503.20098v1	https://arxiv.org/pdf/2503.20098v1.pdf	https://github.com/brcsomnath/PEF	true	false	true	pytorch
https://paperswithcode.com/paper/local-a-graph-based-active-learning-approach	LOCAL: A Graph-Based Active Learning Approach for Stability Analysis of DAC@NG Catalysts	2503.19445	https://arxiv.org/abs/2503.19445v1	https://arxiv.org/pdf/2503.19445v1.pdf	https://github.com/yueyin19960520/LOCAL	true	false	false	pytorch
https://paperswithcode.com/paper/ras-retrieval-and-structuring-for-knowledge	RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM Generation	2502.10996	https://arxiv.org/abs/2502.10996v2	https://arxiv.org/pdf/2502.10996v2.pdf	https://github.com/pat-jj/Retrieval-And-Structure	true	false	true	pytorch
https://paperswithcode.com/paper/on-the-reproducibility-of-learned-sparse	On the Reproducibility of Learned Sparse Retrieval Adaptations for Long Documents	2503.23824	https://arxiv.org/abs/2503.23824v1	https://arxiv.org/pdf/2503.23824v1.pdf	https://github.com/lionisakis/reproducibilitiy-lsr-long	true	true	false	pytorch
https://paperswithcode.com/paper/quantifying-lexical-semantic-shift-via	Quantifying Lexical Semantic Shift via Unbalanced Optimal Transport	2412.12569	https://arxiv.org/abs/2412.12569v1	https://arxiv.org/pdf/2412.12569v1.pdf	https://github.com/ryo-lyo/Semantic-Shift-via-UOT	true	false	true	none
https://paperswithcode.com/paper/ugodit-unsupervised-group-deep-image-prior	UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights	2505.11720	https://arxiv.org/abs/2505.11720v1	https://arxiv.org/pdf/2505.11720v1.pdf	https://github.com/sjames40/ugodit	true	true	false	pytorch
https://paperswithcode.com/paper/physics-informed-learning-for-the-friction	Physics-Informed Learning for the Friction Modeling of High-Ratio Harmonic Drives	2410.12685	https://arxiv.org/abs/2410.12685v1	https://arxiv.org/pdf/2410.12685v1.pdf	https://github.com/ami-iit/paper_sorrentino_2024_humanoids_friction_estimation	true	true	true	pytorch
https://paperswithcode.com/paper/filtrations-indexed-by-attracting-levels-and	Filtrations Indexed by Attracting Levels and their Applications	2506.18250	https://arxiv.org/abs/2506.18250v1	https://arxiv.org/pdf/2506.18250v1.pdf	https://github.com/yusuke-imoto-lab/eps-attracting-basin	true	true	true	none
https://paperswithcode.com/paper/pentestgpt-an-llm-empowered-automatic	PentestGPT: An LLM-empowered Automatic Penetration Testing Tool	2308.06782	https://arxiv.org/abs/2308.06782v2	https://arxiv.org/pdf/2308.06782v2.pdf	https://github.com/greydgl/pentestgpt	false	false	true	none
https://paperswithcode.com/paper/signet-convolutional-siamese-network-for	SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification	1707.02131	http://arxiv.org/abs/1707.02131v2	http://arxiv.org/pdf/1707.02131v2.pdf	https://github.com/debasis-dotcom/Real-or-Forged-signature-detection-using-Siamese-Network	false	false	true	none
https://paperswithcode.com/paper/transfer-learning-from-visual-speech	Transfer Learning from Visual Speech Recognition to Mouthing Recognition in German Sign Language	2505.13784	https://arxiv.org/abs/2505.13784v1	https://arxiv.org/pdf/2505.13784v1.pdf	https://github.com/nphamdinh/transfer-learning-vsr-mouthing-sign-language	true	true	false	pytorch
https://paperswithcode.com/paper/dual-modal-attention-enhanced-text-video	Dual-Modal Attention-Enhanced Text-Video Retrieval with Triplet Partial Margin Contrastive Learning	2309.11082	https://arxiv.org/abs/2309.11082v3	https://arxiv.org/pdf/2309.11082v3.pdf	https://github.com/alipay/Ant-Multi-Modal-Framework	true	true	true	pytorch
https://paperswithcode.com/paper/cenet-context-enhancement-network-for-medical	CENet: Context Enhancement Network for Medical Image Segmentation	2505.18423	https://arxiv.org/abs/2505.18423v1	https://arxiv.org/pdf/2505.18423v1.pdf	https://github.com/xmindflow/cenet	true	true	true	pytorch
https://paperswithcode.com/paper/thinkvideo-high-quality-reasoning-video	ThinkVideo: High-Quality Reasoning Video Segmentation with Chain of Thoughts	2505.18561	https://arxiv.org/abs/2505.18561v1	https://arxiv.org/pdf/2505.18561v1.pdf	https://github.com/danielshkao/thinkvideo	true	true	true	none
https://paperswithcode.com/paper/henn-a-hierarchical-epsilon-net-navigation	HENN: A Hierarchical Epsilon Net Navigation Graph for Approximate Nearest Neighbor Search	2505.17368	https://arxiv.org/abs/2505.17368v1	https://arxiv.org/pdf/2505.17368v1.pdf	https://github.com/uic-indexlab/henn	true	true	false	none
https://paperswithcode.com/paper/constructive-characterisations-of-the-must	Constructive characterisations of the must-preorder for asynchrony	2501.13002	https://arxiv.org/abs/2501.13002v1	https://arxiv.org/pdf/2501.13002v1.pdf	https://github.com/gbtito/testing-theory	true	false	false	none
https://paperswithcode.com/paper/generative-novel-view-synthesis-with-3d-aware	Generative Novel View Synthesis with 3D-Aware Diffusion Models	2304.02602	https://arxiv.org/abs/2304.02602v1	https://arxiv.org/pdf/2304.02602v1.pdf	https://github.com/JhihYangWu/UnofficialGeNVS	false	false	true	pytorch
https://paperswithcode.com/paper/sparsity-may-be-all-you-need-sparse-random	Sparsity May Be All You Need: Sparse Random Parameter Adaptation	2502.15975	https://arxiv.org/abs/2502.15975v2	https://arxiv.org/pdf/2502.15975v2.pdf	https://github.com/IBM/SpaRTA	true	false	true	pytorch
https://paperswithcode.com/paper/hadamax-encoding-elevating-performance-in	Hadamax Encoding: Elevating Performance in Model-Free Atari	2505.15345	https://arxiv.org/abs/2505.15345v1	https://arxiv.org/pdf/2505.15345v1.pdf	https://github.com/jacobkooi/hadamax	true	true	true	jax
https://paperswithcode.com/paper/matryoshka-representations-for-adaptive	Matryoshka Representation Learning	2205.13147	https://arxiv.org/abs/2205.13147v4	https://arxiv.org/pdf/2205.13147v4.pdf	https://github.com/novasearch-team/rag-retrieval	false	false	true	pytorch
https://paperswithcode.com/paper/jasper-and-stella-distillation-of-sota	Jasper and Stella: distillation of SOTA embedding models	2412.19048	https://arxiv.org/abs/2412.19048v2	https://arxiv.org/pdf/2412.19048v2.pdf	https://github.com/novasearch-team/rag-retrieval	false	false	true	pytorch
https://paperswithcode.com/paper/forward-and-reverse-gradient-based	Forward and Reverse Gradient-Based Hyperparameter Optimization	1703.01785	http://arxiv.org/abs/1703.01785v3	http://arxiv.org/pdf/1703.01785v3.pdf	https://github.com/benchopt/benchmark_bilevel	false	false	true	jax
https://paperswithcode.com/paper/zero-shot-hyperspectral-pansharpening-using	Zero-Shot Hyperspectral Pansharpening Using Hysteresis-Based Tuning for Spectral Quality Control	2505.16658	https://arxiv.org/abs/2505.16658v1	https://arxiv.org/pdf/2505.16658v1.pdf	https://github.com/giu-guarino/rho-pnn	true	true	true	pytorch
https://paperswithcode.com/paper/background-matters-a-cross-view-bidirectional	Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation	2505.16625	https://arxiv.org/abs/2505.16625v1	https://arxiv.org/pdf/2505.16625v1.pdf	https://github.com/caoluyang0830/cvbm	true	true	true	pytorch
https://paperswithcode.com/paper/cartesian-double-theories-a-double	Cartesian double theories: A double-categorical framework for categorical doctrines	2310.05384	https://arxiv.org/abs/2310.05384v3	https://arxiv.org/pdf/2310.05384v3.pdf	https://github.com/toposinstitute/catcolab	false	false	true	none
https://paperswithcode.com/paper/arb-a-comprehensive-arabic-multimodal	ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark	2505.17021	https://arxiv.org/abs/2505.17021v1	https://arxiv.org/pdf/2505.17021v1.pdf	https://github.com/mbzuai-oryx/arb	true	true	true	none
https://paperswithcode.com/paper/specextend-a-drop-in-enhancement-for	SpecExtend: A Drop-in Enhancement for Speculative Decoding of Long Sequences	2505.20776	https://arxiv.org/abs/2505.20776v1	https://arxiv.org/pdf/2505.20776v1.pdf	https://github.com/jycha98/specextend	true	true	false	pytorch
https://paperswithcode.com/paper/viability-of-future-actions-robust-safety-in	Viability of Future Actions: Robust Safety in Reinforcement Learning via Entropy Regularization	2506.10871	https://arxiv.org/abs/2506.10871v1	https://arxiv.org/pdf/2506.10871v1.pdf	https://github.com/data-science-in-mechanical-engineering/entropy_robustness	true	true	false	none
https://paperswithcode.com/paper/frcrn-boosting-feature-representation-using	FRCRN: Boosting Feature Representation using Frequency Recurrence for Monaural Speech Enhancement	2206.07293	https://arxiv.org/abs/2206.07293v3	https://arxiv.org/pdf/2206.07293v3.pdf	https://github.com/modelscope/ClearerVoice-Studio	true	true	true	pytorch
https://paperswithcode.com/paper/mossformer-pushing-the-performance-limit-of	MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions	2302.11824	https://arxiv.org/abs/2302.11824v1	https://arxiv.org/pdf/2302.11824v1.pdf	https://github.com/modelscope/ClearerVoice-Studio	true	false	true	pytorch
https://paperswithcode.com/paper/plant-bioelectric-early-warning-systems-a	Plant Bioelectric Early Warning Systems: A Five-Year Investigation into Human-Plant Electromagnetic Communication	2506.04132	https://arxiv.org/abs/2506.04132v1	https://arxiv.org/pdf/2506.04132v1.pdf	https://github.com/pgloor/hiddenbiosignals	true	false	false	pytorch
https://paperswithcode.com/paper/how-does-gpt-2-compute-greater-than-1	How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model	2305.00586	https://arxiv.org/abs/2305.00586v5	https://arxiv.org/pdf/2305.00586v5.pdf	https://github.com/technion-cs-nlp/peap	false	false	true	jax
https://paperswithcode.com/paper/narrative-shift-detection-a-hybrid-approach	Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models	2506.20269	https://arxiv.org/abs/2506.20269v1	https://arxiv.org/pdf/2506.20269v1.pdf	https://github.com/k-rlange/t2snarrativechanges	true	true	false	none
https://paperswithcode.com/paper/asf-yolo-a-novel-yolo-model-with-attentional	ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation	2312.06458	https://arxiv.org/abs/2312.06458v2	https://arxiv.org/pdf/2312.06458v2.pdf	https://github.com/mkang315/asf-yolo	true	true	true	pytorch
https://paperswithcode.com/paper/how-do-we-answer-complex-questions-discourse-1	How Do We Answer Complex Questions: Discourse Structure of Long-form Answers	2203.11048	https://arxiv.org/abs/2203.11048v1	https://arxiv.org/pdf/2203.11048v1.pdf	https://github.com/utcsnlp/lfqa_discourse	true	true	true	none
https://paperswithcode.com/paper/a-model-for-every-user-and-budget-label-free	A Model for Every User and Budget: Label-Free and Personalized Mixed-Precision Quantization	2307.12659	https://arxiv.org/abs/2307.12659v2	https://arxiv.org/pdf/2307.12659v2.pdf	https://github.com/samsunglabs/myqasr	true	true	true	pytorch
https://paperswithcode.com/paper/c-tlsan-content-enhanced-time-aware-long-and	C-TLSAN: Content-Enhanced Time-Aware Long- and Short-Term Attention Network for Personalized Recommendation	2506.13021	https://arxiv.org/abs/2506.13021v1	https://arxiv.org/pdf/2506.13021v1.pdf	https://github.com/booml247/ctlsan	true	true	true	tf
https://paperswithcode.com/paper/discosg-towards-discourse-level-text-scene	DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement	2506.15583	https://arxiv.org/abs/2506.15583v1	https://arxiv.org/pdf/2506.15583v1.pdf	https://github.com/zhuang-li/factual	false	false	true	pytorch
https://paperswithcode.com/paper/going-beyond-s-8-fast-inference-of-the-matter	Going beyond $S_8$: fast inference of the matter power spectrum from weak-lensing surveys	2506.16434	https://arxiv.org/abs/2506.16434v1	https://arxiv.org/pdf/2506.16434v1.pdf	https://github.com/xuod/cls2pk	true	true	false	none
https://paperswithcode.com/paper/ai-research-agents-for-machine-learning	AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench	2507.02554	https://arxiv.org/abs/2507.02554v1	https://arxiv.org/pdf/2507.02554v1.pdf	https://github.com/facebookresearch/aira-dojo	true	true	true	none
https://paperswithcode.com/paper/lpoi-listwise-preference-optimization-for	LPOI: Listwise Preference Optimization for Vision Language Models	2505.21061	https://arxiv.org/abs/2505.21061v1	https://arxiv.org/pdf/2505.21061v1.pdf	https://github.com/fatemehpesaran310/lpoi	true	true	true	pytorch
https://paperswithcode.com/paper/ai-face-a-million-scale-demographically	AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark	2406.00783	https://arxiv.org/abs/2406.00783v2	https://arxiv.org/pdf/2406.00783v2.pdf	https://github.com/purdue-m2/ai-face-fairnessbench	true	true	true	pytorch
https://paperswithcode.com/paper/automatic-brain-tumor-segmentation-using-1	Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks	1709.00382	http://arxiv.org/abs/1709.00382v2	http://arxiv.org/pdf/1709.00382v2.pdf	https://github.com/taigw/brats18_docker	false	false	true	none
https://paperswithcode.com/paper/supportnet-solving-catastrophic-forgetting-in	SupportNet: solving catastrophic forgetting in class incremental learning with support data	1806.02942	http://arxiv.org/abs/1806.02942v3	http://arxiv.org/pdf/1806.02942v3.pdf	https://github.com/lykaust15/SupportNet	true	true	true	tf
https://paperswithcode.com/paper/deep-k-means-jointly-clustering-with-k-means	Deep $k$-Means: Jointly clustering with $k$-Means and learning representations	1806.10069	http://arxiv.org/abs/1806.10069v2	http://arxiv.org/pdf/1806.10069v2.pdf	https://github.com/MaziarMF/deep-k-means	true	true	true	tf
https://paperswithcode.com/paper/infrared-and-visible-image-fusion-using-a	Infrared and Visible Image Fusion using a Deep Learning Framework	1804.06992	http://arxiv.org/abs/1804.06992v4	http://arxiv.org/pdf/1804.06992v4.pdf	https://github.com/exceptionLi/imagefusion_deeplearning	true	true	true	none
https://paperswithcode.com/paper/a-review-on-deep-learning-techniques-applied	A Review on Deep Learning Techniques Applied to Semantic Segmentation	1704.06857	http://arxiv.org/abs/1704.06857v1	http://arxiv.org/pdf/1704.06857v1.pdf	https://github.com/demul/image_segmentation_project	false	false	true	tf
https://paperswithcode.com/paper/apply-artificial-neural-network-to-solving	Apply Artificial Neural Network to Solving Manpower Scheduling Problem	2105.03541	https://arxiv.org/abs/2105.03541v1	https://arxiv.org/pdf/2105.03541v1.pdf	https://github.com/ChineseBest/AT-504	true	false	false	none
https://paperswithcode.com/paper/spectral-leakage-and-rethinking-the-kernel	Spectral Leakage and Rethinking the Kernel Size in CNNs	2101.10143	https://arxiv.org/abs/2101.10143v2	https://arxiv.org/pdf/2101.10143v2.pdf	https://github.com/EvgenyKashin/non-leaking-conv	false	false	true	pytorch
https://paperswithcode.com/paper/paracosm-a-language-and-tool-for-testing	Paracosm: A Language and Tool for Testing Autonomous Driving Systems	1902.01084	https://arxiv.org/abs/1902.01084v2	https://arxiv.org/pdf/1902.01084v2.pdf	https://gitlab.mpi-sws.org/mathur/paracosm	true	false	false	none
https://paperswithcode.com/paper/interpretable-and-compositional-relation	Interpretable and Compositional Relation Learning by Joint Training with an Autoencoder	1805.09547	http://arxiv.org/abs/1805.09547v1	http://arxiv.org/pdf/1805.09547v1.pdf	https://github.com/tianran/glimvec	true	true	true	none
https://paperswithcode.com/paper/a-counterexample-to-the-unit-conjecture-for	A counterexample to the unit conjecture for group rings	2102.11818	https://arxiv.org/abs/2102.11818v4	https://arxiv.org/pdf/2102.11818v4.pdf	https://github.com/alex-konovalov/Kaplansky-units-counterexample	false	false	true	none
https://paperswithcode.com/paper/lan-learning-adaptive-neighbors-for-real-time	LAN: Learning Adaptive Neighbors for Real-Time Insider Threat Detection	2403.09209	https://arxiv.org/abs/2403.09209v2	https://arxiv.org/pdf/2403.09209v2.pdf	https://github.com/li1neo/lan	true	true	false	pytorch
https://paperswithcode.com/paper/estimating-missing-data-in-temporal-data	Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks	1711.08742	http://arxiv.org/abs/1711.08742v1	http://arxiv.org/pdf/1711.08742v1.pdf	https://github.com/jsyoon0823/MRNN	false	false	true	tf
https://paperswithcode.com/paper/terahertz-field-induced-near-cutoff-even	Terahertz field induced near-cutoff even-order harmonics in femtosecond laser	2008.10017	https://arxiv.org/abs/2008.10017v2	https://arxiv.org/pdf/2008.10017v2.pdf	https://github.com/timy/NCEH-THz	true	false	true	none
https://paperswithcode.com/paper/pointer-sentinel-mixture-models	Pointer Sentinel Mixture Models	1609.07843	http://arxiv.org/abs/1609.07843v1	http://arxiv.org/pdf/1609.07843v1.pdf	https://github.com/mikekestemont/pie	false	false	true	pytorch
https://paperswithcode.com/paper/edgeconnect-generative-image-inpainting-with	EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning	1901.00212	http://arxiv.org/abs/1901.00212v3	http://arxiv.org/pdf/1901.00212v3.pdf	https://github.com/youyuge34/Anime-InPainting	false	false	true	pytorch
https://paperswithcode.com/paper/a-neural-representation-of-sketch-drawings	A Neural Representation of Sketch Drawings	1704.03477	http://arxiv.org/abs/1704.03477v4	http://arxiv.org/pdf/1704.03477v4.pdf	https://github.com/cpmpercussion/keras-mdn-layer	false	false	true	tf
https://paperswithcode.com/paper/falkon-an-optimal-large-scale-kernel-method	FALKON: An Optimal Large Scale Kernel Method	1705.10958	http://arxiv.org/abs/1705.10958v3	http://arxiv.org/pdf/1705.10958v3.pdf	https://github.com/enry12/FALKON	false	false	true	none
https://paperswithcode.com/paper/unpaired-image-to-image-translation-using	Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks	1703.10593	https://arxiv.org/abs/1703.10593v7	https://arxiv.org/pdf/1703.10593v7.pdf	https://github.com/taivu1998/GANime	false	false	true	tf
https://paperswithcode.com/paper/mce-2018-the-1st-multi-target-speaker	MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation (MCE) Plan, Dataset and Baseline System	1807.06663	http://arxiv.org/abs/1807.06663v1	http://arxiv.org/pdf/1807.06663v1.pdf	https://github.com/swshon/multi-speakerID	false	false	true	none
https://paperswithcode.com/paper/fairness-through-robustness-investigating	Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning	2006.12621	https://arxiv.org/abs/2006.12621v4	https://arxiv.org/pdf/2006.12621v4.pdf	https://github.com/nvedant07/Fairness-Through-Robustness	true	true	true	pytorch
https://paperswithcode.com/paper/image-to-image-translation-with-conditional	Image-to-Image Translation with Conditional Adversarial Networks	1611.07004	http://arxiv.org/abs/1611.07004v3	http://arxiv.org/pdf/1611.07004v3.pdf	https://github.com/taivu1998/GANime	false	false	true	tf
https://paperswithcode.com/paper/190407947	Fast Radio Bursts	1904.07947	http://arxiv.org/abs/1904.07947v1	http://arxiv.org/pdf/1904.07947v1.pdf	https://github.com/kiyo-masui/burst_search	true	true	false	none
https://paperswithcode.com/paper/fully-convolutional-networks-for-semantic-1	Fully Convolutional Networks for Semantic Segmentation	1411.4038	http://arxiv.org/abs/1411.4038v2	http://arxiv.org/pdf/1411.4038v2.pdf	https://github.com/demul/image_segmentation_project	false	false	true	tf
https://paperswithcode.com/paper/backpropagation-through-the-void-optimizing	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation	1711.00123	http://arxiv.org/abs/1711.00123v3	http://arxiv.org/pdf/1711.00123v3.pdf	https://github.com/TalkToTheGAN/REGAN	false	false	true	pytorch
https://paperswithcode.com/paper/generalized-system-identification-with-stable	Generalized system identification with stable spline kernels	1309.7857	http://arxiv.org/abs/1309.7857v4	http://arxiv.org/pdf/1309.7857v4.pdf	https://github.com/saravkin/IPsolve	true	true	false	none
https://paperswithcode.com/paper/overlap-aware-low-latency-online-speaker	Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation	2109.06483	https://arxiv.org/abs/2109.06483v1	https://arxiv.org/pdf/2109.06483v1.pdf	https://github.com/juanmc2005/streamingspeakerdiarization	true	true	false	pytorch
https://paperswithcode.com/paper/realtime-multi-person-2d-pose-estimation	Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields	1611.08050	http://arxiv.org/abs/1611.08050v2	http://arxiv.org/pdf/1611.08050v2.pdf	https://github.com/sananand007/Xrelab	false	false	true	tf
https://paperswithcode.com/paper/densely-connected-convolutional-networks	Densely Connected Convolutional Networks	1608.06993	http://arxiv.org/abs/1608.06993v5	http://arxiv.org/pdf/1608.06993v5.pdf	https://github.com/jonnor/datascience-master	false	false	true	none
https://paperswithcode.com/paper/crisismmd-multimodal-twitter-datasets-from	CrisisMMD: Multimodal Twitter Datasets from Natural Disasters	1805.00713	https://arxiv.org/abs/1805.00713v1	https://arxiv.org/pdf/1805.00713v1.pdf	https://github.com/firojalam/multimodal_social_media	false	false	true	none
https://paperswithcode.com/paper/openai-gym	OpenAI Gym	1606.01540	http://arxiv.org/abs/1606.01540v1	http://arxiv.org/pdf/1606.01540v1.pdf	https://github.com/n0o8o0n1um/Gym1	false	false	true	tf
https://paperswithcode.com/paper/semi-adversarial-networks-convolutional	Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images	1712.00321	http://arxiv.org/abs/1712.00321v3	http://arxiv.org/pdf/1712.00321v3.pdf	https://github.com/iPRoBe-lab/semi-adversarial-networks	false	false	true	pytorch
https://paperswithcode.com/paper/learning-to-generate-samples-from-noise	Learning to Generate Samples from Noise through Infusion Training	1703.06975	http://arxiv.org/abs/1703.06975v1	http://arxiv.org/pdf/1703.06975v1.pdf	https://github.com/bordesf/Infusion	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.