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/xception-deep-learning-with-depthwise	Xception: Deep Learning with Depthwise Separable Convolutions	1610.02357	http://arxiv.org/abs/1610.02357v3	http://arxiv.org/pdf/1610.02357v3.pdf	https://github.com/MindSpore-paper-code-2/code400/tree/main/Inception/xception	false	false	false	mindspore
https://paperswithcode.com/paper/generating-a-structured-summary-of-numerous	Generating a Structured Summary of Numerous Academic Papers: Dataset and Method	2302.04580	https://arxiv.org/abs/2302.04580v1	https://arxiv.org/pdf/2302.04580v1.pdf	https://github.com/stevenlau6/bigsurvey	true	true	false	none
https://paperswithcode.com/paper/complex-network-for-complex-problems-a	Complex Network for Complex Problems: A comparative study of CNN and Complex-valued CNN	2302.04584	https://arxiv.org/abs/2302.04584v1	https://arxiv.org/pdf/2302.04584v1.pdf	https://github.com/soumickmj/pytorch-complex	true	true	true	pytorch
https://paperswithcode.com/paper/toward-extremely-lightweight-distracted	Toward Extremely Lightweight Distracted Driver Recognition With Distillation-Based Neural Architecture Search and Knowledge Transfer	2302.04527	https://arxiv.org/abs/2302.04527v1	https://arxiv.org/pdf/2302.04527v1.pdf	https://github.com/dichao-liu/lightweight_distracted_driver_recognition_with_distillation-based_nas_and_knowledge_transfer	true	true	false	pytorch
https://paperswithcode.com/paper/emvd-dataset-a-dataset-of-extreme-vocal	EMVD dataset: a dataset of extreme vocal distortion techniques used in heavy metal	2406.17732	https://arxiv.org/abs/2406.17732v1	https://arxiv.org/pdf/2406.17732v1.pdf	https://github.com/modantailleur/extrememetalvocalsdataset	true	true	false	pytorch
https://paperswithcode.com/paper/contain-a-community-based-algorithm-for	CONTAIN: A Community-based Algorithm for Network Immunization	2303.01934	https://arxiv.org/abs/2303.01934v2	https://arxiv.org/pdf/2303.01934v2.pdf	https://github.com/ds4ai-upb/contain	true	true	false	none
https://paperswithcode.com/paper/the-cosmic-linear-anisotropy-solving-system-1	The Cosmic Linear Anisotropy Solving System (CLASS) II: Approximation schemes	1104.2933	http://arxiv.org/abs/1104.2933v3	http://arxiv.org/pdf/1104.2933v3.pdf	https://github.com/zachjweiner/class_public	false	false	true	none
https://paperswithcode.com/paper/sparse-bayesian-optimization	Sparse Bayesian Optimization	2203.01900	https://arxiv.org/abs/2203.01900v2	https://arxiv.org/pdf/2203.01900v2.pdf	https://github.com/facebookresearch/sparsebo	true	true	true	pytorch
https://paperswithcode.com/paper/gdcnet-calibrationless-geometric-distortion	GDCNet: Calibrationless geometric distortion correction of echo planar imaging data using deep learning	2402.18777	https://arxiv.org/abs/2402.18777v1	https://arxiv.org/pdf/2402.18777v1.pdf	https://github.com/imr-framework/gdcnet	true	true	false	tf
https://paperswithcode.com/paper/towards-democratizing-joint-embedding-self	Towards Democratizing Joint-Embedding Self-Supervised Learning	2303.01986	https://arxiv.org/abs/2303.01986v1	https://arxiv.org/pdf/2303.01986v1.pdf	https://github.com/facebookresearch/ffcv-ssl	true	true	true	pytorch
https://paperswithcode.com/paper/sequence-to-sequence-learning-with-neural	Sequence to Sequence Learning with Neural Networks	1409.3215	http://arxiv.org/abs/1409.3215v3	http://arxiv.org/pdf/1409.3215v3.pdf	https://github.com/Mind23-2/MindCode-73	false	false	true	mindspore
https://paperswithcode.com/paper/multi-task-learning-as-multi-objective	Multi-Task Learning as Multi-Objective Optimization	1810.04650	http://arxiv.org/abs/1810.04650v2	http://arxiv.org/pdf/1810.04650v2.pdf	https://github.com/isl-org/multiobjectiveoptimization	false	false	true	pytorch
https://paperswithcode.com/paper/improving-factual-error-correction-by	Improving Factual Error Correction by Learning to Inject Factual Errors	2312.07049	https://arxiv.org/abs/2312.07049v1	https://arxiv.org/pdf/2312.07049v1.pdf	https://github.com/nlpcode/life	true	true	false	pytorch
https://paperswithcode.com/paper/attentron-few-shot-text-to-speech-utilizing-1	Attentron: Few-Shot Text-to-Speech Utilizing Attention-Based Variable-Length Embedding	2005.08484	http://arxiv.org/abs/2005.08484v2	http://arxiv.org/pdf/2005.08484v2.pdf	https://github.com/jasminsternkopf/mel_cepstral_distance	false	false	true	none
https://paperswithcode.com/paper/towards-universal-soccer-video-understanding	Towards Universal Soccer Video Understanding	2412.01820	https://arxiv.org/abs/2412.01820v2	https://arxiv.org/pdf/2412.01820v2.pdf	https://github.com/jyrao/UniSoccer	true	false	false	pytorch
https://paperswithcode.com/paper/sconna-a-stochastic-computing-based-optical	SCONNA: A Stochastic Computing Based Optical Accelerator for Ultra-Fast, Energy-Efficient Inference of Integer-Quantized CNNs	2302.07036	https://arxiv.org/abs/2302.07036v1	https://arxiv.org/pdf/2302.07036v1.pdf	https://github.com/uky-ucat/sc_onn_sim	true	true	true	pytorch
https://paperswithcode.com/paper/team-detr-guide-queries-as-a-professional	Team DETR: Guide Queries as a Professional Team in Detection Transformers	2302.07116	https://arxiv.org/abs/2302.07116v3	https://arxiv.org/pdf/2302.07116v3.pdf	https://github.com/horrible-dong/teamdetr	true	true	true	pytorch
https://paperswithcode.com/paper/sp-nas-serial-to-parallel-backbone-search-for	SP-NAS: Serial-to-Parallel Backbone Search for Object Detection	null	http://openaccess.thecvf.com/content_CVPR_2020/html/Jiang_SP-NAS_Serial-to-Parallel_Backbone_Search_for_Object_Detection_CVPR_2020_paper.html	http://openaccess.thecvf.com/content_CVPR_2020/papers/Jiang_SP-NAS_Serial-to-Parallel_Backbone_Search_for_Object_Detection_CVPR_2020_paper.pdf	https://github.com/2023-MindSpore-4/Code11/tree/main/Spnas	false	false	false	mindspore
https://paperswithcode.com/paper/euca-a-practical-prototyping-framework	EUCA: the End-User-Centered Explainable AI Framework	2102.02437	https://arxiv.org/abs/2102.02437v2	https://arxiv.org/pdf/2102.02437v2.pdf	https://github.com/weinajin/euca	false	false	true	none
https://paperswithcode.com/paper/the-language-of-opinion-change-on-social	The language of opinion change on social media under the lens of communicative action	2210.17234	https://arxiv.org/abs/2210.17234v1	https://arxiv.org/pdf/2210.17234v1.pdf	https://github.com/corradomonti/10-dim-of-op-change	true	true	false	none
https://paperswithcode.com/paper/hierarchical-text-conditional-image	Hierarchical Text-Conditional Image Generation with CLIP Latents	2204.06125	https://arxiv.org/abs/2204.06125v1	https://arxiv.org/pdf/2204.06125v1.pdf	https://github.com/laion-ai/conditioned-prior	false	false	true	pytorch
https://paperswithcode.com/paper/dp-bart-for-privatized-text-rewriting-under	DP-BART for Privatized Text Rewriting under Local Differential Privacy	2302.07636	https://arxiv.org/abs/2302.07636v2	https://arxiv.org/pdf/2302.07636v2.pdf	https://github.com/trusthlt/dp-bart-private-rewriting	true	true	true	pytorch
https://paperswithcode.com/paper/optical-flow-estimation-with-event-based	Optical flow estimation from event-based cameras and spiking neural networks	2302.06492	https://arxiv.org/abs/2302.06492v2	https://arxiv.org/pdf/2302.06492v2.pdf	https://github.com/j-cuadrado/of_ev_snn	true	true	true	pytorch
https://paperswithcode.com/paper/the-enmity-paradox	The Enmity Paradox	2304.10076	https://arxiv.org/abs/2304.10076v1	https://arxiv.org/pdf/2304.10076v1.pdf	https://github.com/aghasemian/enmityparadox	true	true	false	none
https://paperswithcode.com/paper/human-guided-ground-truth-generation-for	Human Guided Ground-truth Generation for Realistic Image Super-resolution	2303.13069	https://arxiv.org/abs/2303.13069v1	https://arxiv.org/pdf/2303.13069v1.pdf	https://github.com/chrisdud0257/hggt	true	true	true	pytorch
https://paperswithcode.com/paper/frequency-assisted-mamba-for-remote-sensing	Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution	2405.04964	https://arxiv.org/abs/2405.04964v2	https://arxiv.org/pdf/2405.04964v2.pdf	https://github.com/XY-boy/FreMamba	true	true	false	pytorch
https://paperswithcode.com/paper/multi3woz-a-multilingual-multi-domain-multi	Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems	2307.14031	https://arxiv.org/abs/2307.14031v1	https://arxiv.org/pdf/2307.14031v1.pdf	https://github.com/cambridgeltl/multi3woz	true	true	true	none
https://paperswithcode.com/paper/rgbd-object-tracking-an-in-depth-review	RGBD Object Tracking: An In-depth Review	2203.14134	https://arxiv.org/abs/2203.14134v1	https://arxiv.org/pdf/2203.14134v1.pdf	https://github.com/memoryunreal/rgbd-tracking-review	true	true	true	pytorch
https://paperswithcode.com/paper/alias-free-convnets-fractional-shift	Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations	2303.08085	https://arxiv.org/abs/2303.08085v2	https://arxiv.org/pdf/2303.08085v2.pdf	https://github.com/hmichaeli/alias_free_convnets	true	true	true	pytorch
https://paperswithcode.com/paper/a-legendre-gauss-pseudospectral-collocation	A Legendre-Gauss Pseudospectral Collocation Method for Trajectory Optimization in Second Order Systems	2302.09036	https://arxiv.org/abs/2302.09036v1	https://arxiv.org/pdf/2302.09036v1.pdf	https://github.com/aunsiro/optibot	false	false	true	none
https://paperswithcode.com/paper/marginalised-gaussian-processes-with-nested	Marginalised Gaussian Processes with Nested Sampling	2010.16344	https://arxiv.org/abs/2010.16344v2	https://arxiv.org/pdf/2010.16344v2.pdf	https://github.com/frgsimpson/nsampling	true	true	true	tf
https://paperswithcode.com/paper/filtering-distillation-and-hard-negatives-for	Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training	2301.02280	https://arxiv.org/abs/2301.02280v2	https://arxiv.org/pdf/2301.02280v2.pdf	https://github.com/facebookresearch/diht	true	true	true	pytorch
https://paperswithcode.com/paper/multi-modal-self-supervised-learning-for	Multi-Modal Self-Supervised Learning for Recommendation	2302.10632	https://arxiv.org/abs/2302.10632v5	https://arxiv.org/pdf/2302.10632v5.pdf	https://github.com/hkuds/mmssl	true	true	true	pytorch
https://paperswithcode.com/paper/graph-attention-networks	Graph Attention Networks	1710.10903	http://arxiv.org/abs/1710.10903v3	http://arxiv.org/pdf/1710.10903v3.pdf	https://github.com/taishan1994/pytorch_gat	false	false	true	pytorch
https://paperswithcode.com/paper/logit-margin-matters-improving-transferable	Logit Margin Matters: Improving Transferable Targeted Adversarial Attack by Logit Calibration	2303.03680	https://arxiv.org/abs/2303.03680v1	https://arxiv.org/pdf/2303.03680v1.pdf	https://github.com/wjjll/target-attack	true	true	false	pytorch
https://paperswithcode.com/paper/weigh-your-own-words-improving-hate-speech	Weigh Your Own Words: Improving Hate Speech Counter Narrative Generation via Attention Regularization	2309.02311	https://arxiv.org/abs/2309.02311v1	https://arxiv.org/pdf/2309.02311v1.pdf	https://github.com/milanlproc/weigh-your-own-words	true	true	false	pytorch
https://paperswithcode.com/paper/bidirectional-reachable-hierarchical	Bidirectional-Reachable Hierarchical Reinforcement Learning with Mutually Responsive Policies	2406.18053	https://arxiv.org/abs/2406.18053v1	https://arxiv.org/pdf/2406.18053v1.pdf	https://github.com/roythuly/brhpo	true	true	false	pytorch
https://paperswithcode.com/paper/quantifying-uncertainties-in-the-solar-axion	Quantifying uncertainties in the solar axion flux and their impact on determining axion model parameters	2101.08789	https://arxiv.org/abs/2101.08789v3	https://arxiv.org/pdf/2101.08789v3.pdf	https://github.com/sebhoof/SolarAxionFlux	true	true	true	none
https://paperswithcode.com/paper/axion-helioscopes-as-solar-thermometers	Axion Helioscopes as Solar Thermometers	2306.00077	https://arxiv.org/abs/2306.00077v2	https://arxiv.org/pdf/2306.00077v2.pdf	https://github.com/sebhoof/SolarAxionFlux	true	true	true	none
https://paperswithcode.com/paper/domain-adaptation-of-echocardiography	Domain Adaptation of Echocardiography Segmentation Via Reinforcement Learning	2406.17902	https://arxiv.org/abs/2406.17902v1	https://arxiv.org/pdf/2406.17902v1.pdf	https://github.com/arnaudjudge/rl4seg	true	true	true	pytorch
https://paperswithcode.com/paper/the-barker-proposal-combining-robustness-and	The Barker proposal: combining robustness and efficiency in gradient-based MCMC	1908.11812	http://arxiv.org/abs/1908.11812v2	http://arxiv.org/pdf/1908.11812v2.pdf	https://github.com/UCL/rmcmc	false	false	false	none
https://paperswithcode.com/paper/unsupervised-domain-expansion-for-visual	Unsupervised Domain Expansion for Visual Categorization	2104.00233	https://arxiv.org/abs/2104.00233v1	https://arxiv.org/pdf/2104.00233v1.pdf	https://github.com/theeighthday/co-teaching	false	false	true	pytorch
https://paperswithcode.com/paper/face-fast-accurate-and-context-aware-audio	Face: Fast, Accurate and Context-Aware Audio Annotation and Classification	2303.03666	https://arxiv.org/abs/2303.03666v1	https://arxiv.org/pdf/2303.03666v1.pdf	https://github.com/gitmehrdad/face	true	true	true	none
https://paperswithcode.com/paper/what-learned-representations-and-influence	What Learned Representations and Influence Functions Can Tell Us About Adversarial Examples	2309.10916	https://arxiv.org/abs/2309.10916v3	https://arxiv.org/pdf/2309.10916v3.pdf	https://github.com/sjabin/nnif	true	true	false	pytorch
https://paperswithcode.com/paper/patchbackdoor-backdoor-attack-against-deep	PatchBackdoor: Backdoor Attack against Deep Neural Networks without Model Modification	2308.11822	https://arxiv.org/abs/2308.11822v1	https://arxiv.org/pdf/2308.11822v1.pdf	https://github.com/xaiveryuan/patchbackdoor	true	true	false	pytorch
https://paperswithcode.com/paper/on-slicing-sorted-integer-sequences	On Slicing Sorted Integer Sequences	1907.01032	https://arxiv.org/abs/1907.01032v2	https://arxiv.org/pdf/1907.01032v2.pdf	https://github.com/jermp/s_indexes	true	true	true	none
https://paperswithcode.com/paper/techniques-for-inverted-index-compression	Techniques for Inverted Index Compression	1908.10598	https://arxiv.org/abs/1908.10598v2	https://arxiv.org/pdf/1908.10598v2.pdf	https://github.com/jermp/s_indexes	false	false	true	none
https://paperswithcode.com/paper/rlx2-training-a-sparse-deep-reinforcement	RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch	2205.15043	https://arxiv.org/abs/2205.15043v2	https://arxiv.org/pdf/2205.15043v2.pdf	https://github.com/tyq1024/rlx2	true	true	false	pytorch
https://paperswithcode.com/paper/evotorch-scalable-evolutionary-computation-in	EvoTorch: Scalable Evolutionary Computation in Python	2302.12600	https://arxiv.org/abs/2302.12600v3	https://arxiv.org/pdf/2302.12600v3.pdf	https://github.com/nnaisense/evotorch	true	true	true	jax
https://paperswithcode.com/paper/semantic-segmentation-for-autonomous-driving	Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time Capability	2207.12939	https://arxiv.org/abs/2207.12939v1	https://arxiv.org/pdf/2207.12939v1.pdf	https://github.com/sinop97/drive_sim_road_generation	true	true	true	none
https://paperswithcode.com/paper/fastami-a-monte-carlo-approach-to-the	FastAMI -- a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics	2305.03022	https://arxiv.org/abs/2305.03022v1	https://arxiv.org/pdf/2305.03022v1.pdf	https://github.com/mad-lab-fau/fastami	true	false	false	none
https://paperswithcode.com/paper/interpolation-in-generative-models	Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models	1904.03445	https://arxiv.org/abs/1904.03445v3	https://arxiv.org/pdf/1904.03445v3.pdf	https://github.com/gmum/feature-based-interpolation	true	true	false	pytorch
https://paperswithcode.com/paper/universal-construction-of-decoders-from	Universal construction of decoders from encoding black boxes	2110.00258	https://arxiv.org/abs/2110.00258v5	https://arxiv.org/pdf/2110.00258v5.pdf	https://github.com/sy3104/isometry_inversion	true	true	true	none
https://paperswithcode.com/paper/conserved-currents-for-kerr-and-orthogonality	Conserved currents for Kerr and orthogonality of quasinormal modes	2210.15935	https://arxiv.org/abs/2210.15935v3	https://arxiv.org/pdf/2210.15935v3.pdf	https://github.com/sprogl/h-k-tensors	true	true	true	none
https://paperswithcode.com/paper/styleganex-stylegan-based-manipulation-beyond	StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Faces	2303.06146	https://arxiv.org/abs/2303.06146v2	https://arxiv.org/pdf/2303.06146v2.pdf	https://github.com/williamyang1991/styleganex	true	true	true	pytorch
https://paperswithcode.com/paper/simple-domain-generalization-methods-are	Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization	2303.18031	https://arxiv.org/abs/2303.18031v1	https://arxiv.org/pdf/2303.18031v1.pdf	https://github.com/shiralab/opendg-eval	true	true	false	pytorch
https://paperswithcode.com/paper/cbam-convolutional-block-attention-module	CBAM: Convolutional Block Attention Module	1807.06521	http://arxiv.org/abs/1807.06521v2	http://arxiv.org/pdf/1807.06521v2.pdf	https://github.com/2023-MindSpore-1/ms-code-6/tree/main/CBAM	false	false	false	mindspore
https://paperswithcode.com/paper/cliff-carrying-location-information-in-full	CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation	2208.00571	https://arxiv.org/abs/2208.00571v2	https://arxiv.org/pdf/2208.00571v2.pdf	https://github.com/2023-MindSpore-1/ms-code-6/tree/main/CLIFF	false	false	false	mindspore
https://paperswithcode.com/paper/bandwidth-selection-for-gaussian-kernel-ridge	Bandwidth Selection for Gaussian Kernel Ridge Regression via Jacobian Control	2205.11956	https://arxiv.org/abs/2205.11956v4	https://arxiv.org/pdf/2205.11956v4.pdf	https://github.com/allerbo/jacobian_bandwidth_selection	true	true	true	none
https://paperswithcode.com/paper/managing-power-grids-through-topology-actions	Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents	2304.00765	https://arxiv.org/abs/2304.00765v2	https://arxiv.org/pdf/2304.00765v2.pdf	https://github.com/fraunhoferiee/curriculumagent	true	true	false	pytorch
https://paperswithcode.com/paper/gradient-driven-3d-segmentation-and	Gradient-Driven 3D Segmentation and Affordance Transfer in Gaussian Splatting Using 2D Masks	2409.11681	https://arxiv.org/abs/2409.11681v1	https://arxiv.org/pdf/2409.11681v1.pdf	https://github.com/JojiJoseph/3dgs-gradient-segmentation	true	false	true	pytorch
https://paperswithcode.com/paper/uniformer-unified-multi-view-fusion	UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View	2207.08536	https://arxiv.org/abs/2207.08536v2	https://arxiv.org/pdf/2207.08536v2.pdf	https://github.com/cfzd/unifusion	true	true	true	none
https://paperswithcode.com/paper/deepinteraction-3d-object-detection-via	DeepInteraction: 3D Object Detection via Modality Interaction	2208.11112	https://arxiv.org/abs/2208.11112v4	https://arxiv.org/pdf/2208.11112v4.pdf	https://github.com/fudan-zvg/gss	false	false	true	pytorch
https://paperswithcode.com/paper/differentially-private-algorithms-for-3	Differentially Private Algorithms for Synthetic Power System Datasets	2303.11079	https://arxiv.org/abs/2303.11079v1	https://arxiv.org/pdf/2303.11079v1.pdf	https://github.com/wdvorkin/syntheticdata	true	true	false	none
https://paperswithcode.com/paper/vectornet-encoding-hd-maps-and-agent-dynamics	VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation	2005.04259	https://arxiv.org/abs/2005.04259v1	https://arxiv.org/pdf/2005.04259v1.pdf	https://github.com/henry1iu/tnt-trajectory-prediction	false	false	true	pytorch
https://paperswithcode.com/paper/tnt-target-driven-trajectory-prediction	TNT: Target-driveN Trajectory Prediction	2008.08294	https://arxiv.org/abs/2008.08294v2	https://arxiv.org/pdf/2008.08294v2.pdf	https://github.com/henry1iu/tnt-trajectory-prediction	false	false	true	pytorch
https://paperswithcode.com/paper/triaan-vc-triple-adaptive-attention	TriAAN-VC: Triple Adaptive Attention Normalization for Any-to-Any Voice Conversion	2303.09057	https://arxiv.org/abs/2303.09057v1	https://arxiv.org/pdf/2303.09057v1.pdf	https://github.com/winddori2002/TriAAN-VC	true	false	true	pytorch
https://paperswithcode.com/paper/clip-goes-3d-leveraging-prompt-tuning-for	CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition	2303.11313	https://arxiv.org/abs/2303.11313v3	https://arxiv.org/pdf/2303.11313v3.pdf	https://github.com/deeptibhegde/clip-goes-3d	true	true	true	pytorch
https://paperswithcode.com/paper/generative-semantic-segmentation	Generative Semantic Segmentation	2303.11316	https://arxiv.org/abs/2303.11316v2	https://arxiv.org/pdf/2303.11316v2.pdf	https://github.com/fudan-zvg/gss	true	true	true	pytorch
https://paperswithcode.com/paper/self-supervised-learning-for-multimodal-non	Self-Supervised Learning for Multimodal Non-Rigid 3D Shape Matching	2303.10971	https://arxiv.org/abs/2303.10971v1	https://arxiv.org/pdf/2303.10971v1.pdf	https://github.com/dongliangcao/Self-Supervised-Multimodal-Shape-Matching	true	true	true	pytorch
https://paperswithcode.com/paper/less-is-more-reducing-task-and-model	Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation	2303.11203	https://arxiv.org/abs/2303.11203v2	https://arxiv.org/pdf/2303.11203v2.pdf	https://github.com/l1997i/lim3d	true	true	true	pytorch
https://paperswithcode.com/paper/natcs-eliciting-natural-customer-support	NatCS: Eliciting Natural Customer Support Dialogues	2305.03007	https://arxiv.org/abs/2305.03007v1	https://arxiv.org/pdf/2305.03007v1.pdf	https://github.com/amazon-research/dstc11-track2-intent-induction	false	false	true	none
https://paperswithcode.com/paper/intent-induction-from-conversations-for-task	Intent Induction from Conversations for Task-Oriented Dialogue Track at DSTC 11	2304.12982	https://arxiv.org/abs/2304.12982v1	https://arxiv.org/pdf/2304.12982v1.pdf	https://github.com/amazon-research/dstc11-track2-intent-induction	false	false	true	none
https://paperswithcode.com/paper/query-encoder-distillation-via-embedding	Query Encoder Distillation via Embedding Alignment is a Strong Baseline Method to Boost Dense Retriever Online Efficiency	2306.11550	https://arxiv.org/abs/2306.11550v1	https://arxiv.org/pdf/2306.11550v1.pdf	https://github.com/guest400123064/distill-retriever	true	true	false	pytorch
https://paperswithcode.com/paper/generative-multiplane-neural-radiance-for-3d	Generative Multiplane Neural Radiance for 3D-Aware Image Generation	2304.01172	https://arxiv.org/abs/2304.01172v1	https://arxiv.org/pdf/2304.01172v1.pdf	https://github.com/virobo-15/gmnr	true	true	true	pytorch
https://paperswithcode.com/paper/a-discontinuous-galerkin-approach-for	A discontinuous Galerkin approach for atmospheric flows with implicit condensation	2305.13847	https://arxiv.org/abs/2305.13847v3	https://arxiv.org/pdf/2305.13847v3.pdf	https://github.com/hvonwah/cloud-models-code	true	true	false	none
https://paperswithcode.com/paper/magvlt-masked-generative-vision-and-language	MAGVLT: Masked Generative Vision-and-Language Transformer	2303.12208	https://arxiv.org/abs/2303.12208v1	https://arxiv.org/pdf/2303.12208v1.pdf	https://github.com/kakaobrain/magvlt	true	false	true	pytorch
https://paperswithcode.com/paper/multimodal-industrial-anomaly-detection-by	Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping	2312.04521	https://arxiv.org/abs/2312.04521v2	https://arxiv.org/pdf/2312.04521v2.pdf	https://github.com/cvlab-unibo/crossmodal-feature-mapping	false	false	true	pytorch
https://paperswithcode.com/paper/tabret-pre-training-transformer-based-tabular	TabRet: Pre-training Transformer-based Tabular Models for Unseen Columns	2303.15747	https://arxiv.org/abs/2303.15747v4	https://arxiv.org/pdf/2303.15747v4.pdf	https://github.com/pfnet-research/tabret	true	true	true	pytorch
https://paperswithcode.com/paper/pynet-qxq-a-distilled-pynet-for-qxq-bayer	PyNET-QxQ: An Efficient PyNET Variant for QxQ Bayer Pattern Demosaicing in CMOS Image Sensors	2203.04314	https://arxiv.org/abs/2203.04314v2	https://arxiv.org/pdf/2203.04314v2.pdf	https://github.com/minhyeok01/pynet-qxq	true	true	false	pytorch
https://paperswithcode.com/paper/polynomial-time-and-dependent-types	Polynomial Time and Dependent Types	2307.09145	https://arxiv.org/abs/2307.09145v2	https://arxiv.org/pdf/2307.09145v2.pdf	https://github.com/bobatkey/qtt-models	true	true	false	none
https://paperswithcode.com/paper/how-to-boost-face-recognition-with-stylegan	How to Boost Face Recognition with StyleGAN?	2210.10090	https://arxiv.org/abs/2210.10090v2	https://arxiv.org/pdf/2210.10090v2.pdf	https://github.com/seva100/stylegan-for-facerec	true	true	true	pytorch
https://paperswithcode.com/paper/defending-llms-against-jailbreaking-attacks	Defending LLMs against Jailbreaking Attacks via Backtranslation	2402.16459	https://arxiv.org/abs/2402.16459v3	https://arxiv.org/pdf/2402.16459v3.pdf	https://github.com/yihanwang617/llm-jailbreaking-defense	true	true	true	none
https://paperswithcode.com/paper/mirror-cognitive-inner-monologue-between	MIRROR: Cognitive Inner Monologue Between Conversational Turns for Persistent Reflection and Reasoning in Conversational LLMs	2506.00430	https://arxiv.org/abs/2506.00430v1	https://arxiv.org/pdf/2506.00430v1.pdf	https://github.com/nicolehsing/MIRROR	true	false	true	none
https://paperswithcode.com/paper/mci-net-multi-scale-context-integrated	Mci-net: multi-scale context integrated network for liver ct image segmentation	null	https://www.sciencedirect.com/science/article/pii/S0045790622003408	https://www.sciencedirect.com/science/article/pii/S0045790622003408	https://github.com/Xie-Xiwang/MCI-Net	true	false	false	pytorch
https://paperswithcode.com/paper/breaking-the-silence-detecting-and-mitigating	Breaking the Silence Detecting and Mitigating Gendered Abuse in Hindi, Tamil, and Indian English Online Spaces	2404.02013	https://arxiv.org/abs/2404.02013v2	https://arxiv.org/pdf/2404.02013v2.pdf	https://github.com/advaithavetagiri/cnlp-nits-pp	true	true	false	none
https://paperswithcode.com/paper/music-demixing-with-the-slicq-transform	Music demixing with the sliCQ transform	2112.05509	https://arxiv.org/abs/2112.05509v1	https://arxiv.org/pdf/2112.05509v1.pdf	https://github.com/sevagh/xumx-slicq	true	true	true	pytorch
https://paperswithcode.com/paper/snrgan-the-semi-noise-reduction-gan-for-image	SNRGAN: The Semi Noise Reduction GAN for Image Denoising	null	https://ieeexplore.ieee.org/abstract/document/10475264	https://ieeexplore.ieee.org/abstract/document/10475264	https://github.com/mehrshadmmt/SNRGAN-The-Semi-Noise-Reduction-GAN-for-Image-Denoising	false	false	false	pytorch
https://paperswithcode.com/paper/airloc-object-based-indoor-relocalization	AirLoc: Object-based Indoor Relocalization	2304.00954	https://arxiv.org/abs/2304.00954v1	https://arxiv.org/pdf/2304.00954v1.pdf	https://github.com/sair-lab/airloc	true	true	true	pytorch
https://paperswithcode.com/paper/privacy-preserving-representations-are-not	Privacy-Preserving Representations are not Enough -- Recovering Scene Content from Camera Poses	2305.04603	https://arxiv.org/abs/2305.04603v1	https://arxiv.org/pdf/2305.04603v1.pdf	https://github.com/kunalchelani/objectpositioningfromposes	true	true	false	none
https://paperswithcode.com/paper/bi-mapper-holistic-bev-semantic-mapping-for	Bi-Mapper: Holistic BEV Semantic Mapping for Autonomous Driving	2305.04205	https://arxiv.org/abs/2305.04205v3	https://arxiv.org/pdf/2305.04205v3.pdf	https://github.com/lynn-yu/bi-mapper	true	true	true	pytorch
https://paperswithcode.com/paper/hatemm-a-multi-modal-dataset-for-hate-video	HateMM: A Multi-Modal Dataset for Hate Video Classification	2305.03915	https://arxiv.org/abs/2305.03915v1	https://arxiv.org/pdf/2305.03915v1.pdf	https://github.com/hate-alert/hatemm	true	true	false	pytorch
https://paperswithcode.com/paper/the-metric-space-of-collider-events	The Metric Space of Collider Events	1902.02346	http://arxiv.org/abs/1902.02346v3	http://arxiv.org/pdf/1902.02346v3.pdf	https://github.com/jet-net/jetnet	false	false	true	pytorch
https://paperswithcode.com/paper/on-the-evaluation-of-generative-models-in	Evaluating generative models in high energy physics	2211.10295	https://arxiv.org/abs/2211.10295v2	https://arxiv.org/pdf/2211.10295v2.pdf	https://github.com/jet-net/jetnet	true	true	true	pytorch
https://paperswithcode.com/paper/the-neural-hawkes-process-a-neurally-self	The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process	1612.09328	http://arxiv.org/abs/1612.09328v3	http://arxiv.org/pdf/1612.09328v3.pdf	https://github.com/sohamch/Neural-Hawkes-study	false	false	true	pytorch
https://paperswithcode.com/paper/attacking-pre-trained-recommendation	Attacking Pre-trained Recommendation	2305.03995	https://arxiv.org/abs/2305.03995v1	https://arxiv.org/pdf/2305.03995v1.pdf	https://github.com/wyqing20/aprec	true	true	false	pytorch
https://paperswithcode.com/paper/monocular-3d-human-pose-estimation-for-sports	Monocular 3D Human Pose Estimation for Sports Broadcasts using Partial Sports Field Registration	2304.04437	https://arxiv.org/abs/2304.04437v1	https://arxiv.org/pdf/2304.04437v1.pdf	https://github.com/tobibaum/partialsportsfieldreg_3dhpe	true	true	true	none
https://paperswithcode.com/paper/learning-to-estimate-external-forces-of-human	Learning to Estimate External Forces of Human Motion in Video	2207.05845	https://arxiv.org/abs/2207.05845v1	https://arxiv.org/pdf/2207.05845v1.pdf	https://github.com/michigancog/forcepose	true	true	true	pytorch
https://paperswithcode.com/paper/low-cost-portable-easy-to-use-kiosks-to	Low-cost, portable, easy-to-use kiosks to facilitate home-cage testing of non-human primates during vision-based behavioral tasks	2401.03727	https://arxiv.org/abs/2401.03727v1	https://arxiv.org/pdf/2401.03727v1.pdf	https://github.com/vital-kolab/nhp-turk	true	true	false	none
https://paperswithcode.com/paper/intelligent-client-selection-for-federated	Intelligent Client Selection for Federated Learning using Cellular Automata	2310.00627	https://arxiv.org/abs/2310.00627v2	https://arxiv.org/pdf/2310.00627v2.pdf	https://github.com/nikopavl4/ca_client_selection	true	true	false	pytorch

Subsets and Splits

Framework Repo Connectivity Analysis

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

Deduplicated Paper-Code Links

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

Paper Repo Counts & Distribution

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

Quantum Papers with Code Links

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

Financial Stock Price Prediction

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

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

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

Search for YOLO Links

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

Prompt Optimization and Personalization

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