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/mozart-s-touch-a-lightweight-multi-modal	Mozart's Touch: A Lightweight Multi-modal Music Generation Framework Based on Pre-Trained Large Models	2405.02801	https://arxiv.org/abs/2405.02801v3	https://arxiv.org/pdf/2405.02801v3.pdf	https://github.com/tiffanyblews/mozartstouch	true	true	true	pytorch
https://paperswithcode.com/paper/matrix-free-methods-for-finite-strain	Matrix-Free Methods for Finite-Strain Elasticity: Automatic Code Generation with No Performance Overhead	2505.15535	https://arxiv.org/abs/2505.15535v1	https://arxiv.org/pdf/2505.15535v1.pdf	https://github.com/mwichro/solid-matrix-free	true	false	true	none
https://paperswithcode.com/paper/a-sequential-benders-based-mixed-integer	A Sequential Benders-based Mixed-Integer Quadratic Programming Algorithm	2404.11786	https://arxiv.org/abs/2404.11786v1	https://arxiv.org/pdf/2404.11786v1.pdf	https://github.com/minlp-toolbox/camino	false	false	true	none
https://paperswithcode.com/paper/delgrad-exact-gradients-in-spiking-networks	DelGrad: Exact event-based gradients for training delays and weights on spiking neuromorphic hardware	2404.19165	https://arxiv.org/abs/2404.19165v3	https://arxiv.org/pdf/2404.19165v3.pdf	https://github.com/JulianGoeltz/fastAndDeep	false	false	true	pytorch
https://paperswithcode.com/paper/fast-and-deep-neuromorphic-learning-with-time	Fast and energy-efficient neuromorphic deep learning with first-spike times	1912.11443	https://arxiv.org/abs/1912.11443v4	https://arxiv.org/pdf/1912.11443v4.pdf	https://github.com/JulianGoeltz/fastAndDeep	false	false	true	pytorch
https://paperswithcode.com/paper/robust-benchmarking-in-noisy-environments	Robust benchmarking in noisy environments	1608.04295	http://arxiv.org/abs/1608.04295v1	http://arxiv.org/pdf/1608.04295v1.pdf	https://github.com/stdlib-js/utils-timeit	false	false	true	none
https://paperswithcode.com/paper/using-k-medoids-for-distributed-approximate	A Parametrizable Algorithm for Distributed Approximate Similarity Search with Arbitrary Distances	2405.13795	https://arxiv.org/abs/2405.13795v3	https://arxiv.org/pdf/2405.13795v3.pdf	https://github.com/elenagarciamorato/PDASC	true	false	true	none
https://paperswithcode.com/paper/toward-memory-aided-world-models-benchmarking	Toward Memory-Aided World Models: Benchmarking via Spatial Consistency	2505.22976	https://arxiv.org/abs/2505.22976v1	https://arxiv.org/pdf/2505.22976v1.pdf	https://github.com/kevin-lkw/loopnav	true	true	false	none
https://paperswithcode.com/paper/design-of-bayesian-clinical-trials-with	Design of Bayesian Clinical Trials with Clustered Data and Multiple Endpoints	2501.13218	https://arxiv.org/abs/2501.13218v2	https://arxiv.org/pdf/2501.13218v2.pdf	https://github.com/lmhagar/clusterdocs	true	true	false	none
https://paperswithcode.com/paper/enhancing-large-language-models-through-neuro	Enhancing Large Language Models through Neuro-Symbolic Integration and Ontological Reasoning	2504.07640	https://arxiv.org/abs/2504.07640v1	https://arxiv.org/pdf/2504.07640v1.pdf	https://github.com/ruslanmv/neuro-symbolic-interaction	true	true	true	none
https://paperswithcode.com/paper/inflationary-flows-calibrated-bayesian	Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models	2407.08843	https://arxiv.org/abs/2407.08843v3	https://arxiv.org/pdf/2407.08843v3.pdf	https://github.com/dannyfa/inflationary_flows	true	true	false	pytorch
https://paperswithcode.com/paper/tracking-changing-probabilities-via-dynamic	Tracking Changing Probabilities via Dynamic Learners	2402.10142	https://arxiv.org/abs/2402.10142v3	https://arxiv.org/pdf/2402.10142v3.pdf	https://github.com/omadanitet/sparse-moving-averages	true	true	true	none
https://paperswithcode.com/paper/kblam-knowledge-base-augmented-language-model	KBLaM: Knowledge Base augmented Language Model	2410.10450	https://arxiv.org/abs/2410.10450v1	https://arxiv.org/pdf/2410.10450v1.pdf	https://github.com/microsoft/KBLaM	true	false	true	pytorch
https://paperswithcode.com/paper/natural-language-processing-in-ethiopian	Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities	2303.14406	https://arxiv.org/abs/2303.14406v1	https://arxiv.org/pdf/2303.14406v1.pdf	https://github.com/EthioNLP/Ethiopian-Language-Survey	true	false	true	none
https://paperswithcode.com/paper/adapt-an-interactive-procedure-for-multiple	AdaPT: An interactive procedure for multiple testing with side information	1609.06035	http://arxiv.org/abs/1609.06035v4	http://arxiv.org/pdf/1609.06035v4.pdf	https://github.com/patrickrchao/adaptmt	false	false	true	none
https://paperswithcode.com/paper/efficient-spatial-dataset-search-over	Joinable Search over Multi-source Spatial Datasets: Overlap, Coverage, and Efficiency	2311.13383	https://arxiv.org/abs/2311.13383v4	https://arxiv.org/pdf/2311.13383v4.pdf	https://github.com/yangwenzhe/msds_code	true	true	true	none
https://paperswithcode.com/paper/taming-knowledge-conflicts-in-language-models	Taming Knowledge Conflicts in Language Models	2503.10996	https://arxiv.org/abs/2503.10996v1	https://arxiv.org/pdf/2503.10996v1.pdf	https://github.com/GaotangLi/JUICE	true	false	true	pytorch
https://paperswithcode.com/paper/depgraph-towards-any-structural-pruning	DepGraph: Towards Any Structural Pruning	2301.12900	https://arxiv.org/abs/2301.12900v2	https://arxiv.org/pdf/2301.12900v2.pdf	https://github.com/VainF/Torch-Pruning	true	true	true	pytorch
https://paperswithcode.com/paper/learning-efficient-convolutional-networks	Learning Efficient Convolutional Networks through Network Slimming	1708.06519	http://arxiv.org/abs/1708.06519v1	http://arxiv.org/pdf/1708.06519v1.pdf	https://github.com/VainF/Torch-Pruning	false	false	true	pytorch
https://paperswithcode.com/paper/language-guided-concept-bottleneck-models-for	Language Guided Concept Bottleneck Models for Interpretable Continual Learning	2503.23283	https://arxiv.org/abs/2503.23283v1	https://arxiv.org/pdf/2503.23283v1.pdf	https://github.com/fishercats/clg-cbm	true	true	true	pytorch
https://paperswithcode.com/paper/ct-mamba-a-hybrid-convolutional-state-space	CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT Denoising	2411.07930	https://arxiv.org/abs/2411.07930v4	https://arxiv.org/pdf/2411.07930v4.pdf	https://github.com/zy2219105/ct-mamba	true	true	true	pytorch
https://paperswithcode.com/paper/high-throughput-precision-phenotyping-of-left	High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning	2106.12511	https://arxiv.org/abs/2106.12511v1	https://arxiv.org/pdf/2106.12511v1.pdf	https://github.com/echonet/lvh	true	true	false	pytorch
https://paperswithcode.com/paper/open-eyes-then-reason-fine-grained-visual	Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs	2501.06430	https://arxiv.org/abs/2501.06430v1	https://arxiv.org/pdf/2501.06430v1.pdf	https://github.com/ai4math-shanzhang/sve-math	true	true	true	pytorch
https://paperswithcode.com/paper/fast-video-generation-with-sliding-tile	Fast Video Generation with Sliding Tile Attention	2502.04507	https://arxiv.org/abs/2502.04507v1	https://arxiv.org/pdf/2502.04507v1.pdf	https://github.com/hao-ai-lab/fastvideo	false	false	true	pytorch
https://paperswithcode.com/paper/data-pruning-in-generative-diffusion-models	Data Pruning in Generative Diffusion Models	2411.12523	https://arxiv.org/abs/2411.12523v2	https://arxiv.org/pdf/2411.12523v2.pdf	https://github.com/briqr/diffusion_data_pruning	true	false	true	pytorch
https://paperswithcode.com/paper/compass-enhancing-spatial-understanding-in	CoMPaSS: Enhancing Spatial Understanding in Text-to-Image Diffusion Models	2412.13195	https://arxiv.org/abs/2412.13195v1	https://arxiv.org/pdf/2412.13195v1.pdf	https://github.com/blurgyy/compass	true	true	true	none
https://paperswithcode.com/paper/demystify-transformers-convolutions-in-modern	Demystify Transformers & Convolutions in Modern Image Deep Networks	2211.05781	https://arxiv.org/abs/2211.05781v3	https://arxiv.org/pdf/2211.05781v3.pdf	https://github.com/opengvlab/stm-evaluation	true	true	true	pytorch
https://paperswithcode.com/paper/lcpy-an-open-source-python-package-for	lcpy: an open-source python package for parametric and dynamic Life Cycle Assessment and Life Cycle Costing	2506.13744	https://arxiv.org/abs/2506.13744v1	https://arxiv.org/pdf/2506.13744v1.pdf	https://github.com/spirdgk/lcpy	true	true	false	none
https://paperswithcode.com/paper/long-tailed-out-of-distribution-detection	Long-Tailed Out-of-Distribution Detection: Prioritizing Attention to Tail	2408.06742	https://arxiv.org/abs/2408.06742v3	https://arxiv.org/pdf/2408.06742v3.pdf	https://github.com/inar-design/patt	true	true	true	pytorch
https://paperswithcode.com/paper/beyond-data-quantity-key-factors-driving	Beyond Data Quantity: Key Factors Driving Performance in Multilingual Language Models	2412.12500	https://arxiv.org/abs/2412.12500v1	https://arxiv.org/pdf/2412.12500v1.pdf	https://github.com/PortNLP/SHAP-MLLM-Analysis	true	false	true	none
https://paperswithcode.com/paper/preference-oriented-supervised-fine-tuning	Preference-Oriented Supervised Fine-Tuning: Favoring Target Model Over Aligned Large Language Models	2412.12865	https://arxiv.org/abs/2412.12865v1	https://arxiv.org/pdf/2412.12865v1.pdf	https://github.com/Savannah120/alignment-handbook-PoFT	true	false	true	pytorch
https://paperswithcode.com/paper/a-real-time-system-for-scheduling-and	A Real-Time System for Scheduling and Managing UAV Delivery in Urban	2412.11590	https://arxiv.org/abs/2412.11590v1	https://arxiv.org/pdf/2412.11590v1.pdf	https://github.com/chengji253/uavdeliverysystem	true	true	true	none
https://paperswithcode.com/paper/3d-interaction-geometric-pre-training-for	3D Interaction Geometric Pre-training for Molecular Relational Learning	2412.02957	https://arxiv.org/abs/2412.02957v1	https://arxiv.org/pdf/2412.02957v1.pdf	https://github.com/Namkyeong/3DMRL	true	false	true	pytorch
https://paperswithcode.com/paper/sfm-free-3d-gaussian-splatting-via	SfM-Free 3D Gaussian Splatting via Hierarchical Training	2412.01553	https://arxiv.org/abs/2412.01553v1	https://arxiv.org/pdf/2412.01553v1.pdf	https://github.com/jibo27/3dgs_hierarchical_training	true	true	true	pytorch
https://paperswithcode.com/paper/the-densest-swamp-problem-subhypergraphs-with	The Densest SWAMP problem: subhypergraphs with arbitrary monotonic partial edge rewards	2506.12998	https://arxiv.org/abs/2506.12998v1	https://arxiv.org/pdf/2506.12998v1.pdf	https://github.com/vedangi/densest-swamp	true	true	false	none
https://paperswithcode.com/paper/cweval-outcome-driven-evaluation-on	CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation	2501.08200	https://arxiv.org/abs/2501.08200v1	https://arxiv.org/pdf/2501.08200v1.pdf	https://github.com/co1lin/cweval	true	true	true	none
https://paperswithcode.com/paper/the-kfiou-loss-for-rotated-object-detection-1	The KFIoU Loss for Rotated Object Detection	2201.12558	https://arxiv.org/abs/2201.12558v6	https://arxiv.org/pdf/2201.12558v6.pdf	https://github.com/Jittor/JDet	true	true	true	none
https://paperswithcode.com/paper/h-vmunet-high-order-vision-mamba-unet-for	H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation	2403.13642	https://arxiv.org/abs/2403.13642v1	https://arxiv.org/pdf/2403.13642v1.pdf	https://github.com/wurenkai/h-vmunet	true	true	true	pytorch
https://paperswithcode.com/paper/leveraging-out-of-domain-data-for-domain	Can Out-of-Domain data help to Learn Domain-Specific Prompts for Multimodal Misinformation Detection?	2311.16496	https://arxiv.org/abs/2311.16496v4	https://arxiv.org/pdf/2311.16496v4.pdf	https://github.com/scviab/dpod	true	true	true	pytorch
https://paperswithcode.com/paper/towards-more-trustworthy-deep-code-models-by	Towards More Trustworthy Deep Code Models by Enabling Out-of-Distribution Detection	2502.18883	https://arxiv.org/abs/2502.18883v1	https://arxiv.org/pdf/2502.18883v1.pdf	https://github.com/yanyanfu/cood	true	true	false	pytorch
https://paperswithcode.com/paper/wakemint-detecting-sleepminting	WakeMint: Detecting Sleepminting Vulnerabilities in NFT Smart Contracts	2502.19032	https://arxiv.org/abs/2502.19032v1	https://arxiv.org/pdf/2502.19032v1.pdf	https://github.com/lei-xiao2/wakemint2	true	true	false	none
https://paperswithcode.com/paper/icm-assistant-instruction-tuning-multimodal	ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation	2412.18216	https://arxiv.org/abs/2412.18216v2	https://arxiv.org/pdf/2412.18216v2.pdf	https://github.com/zhaoyuzhi/icm-assistant	true	true	true	pytorch
https://paperswithcode.com/paper/structvizor-interactive-profiling-of-semi	StructVizor: Interactive Profiling of Semi-Structured Textual Data	2503.06500	https://arxiv.org/abs/2503.06500v1	https://arxiv.org/pdf/2503.06500v1.pdf	https://github.com/Amur-N/Semi-structured-Dataset-Collection	true	false	false	none
https://paperswithcode.com/paper/upc-sentinel-an-accurate-approach-for	UPC Sentinel: An Accurate Approach for Detecting Upgradeability Proxy Contracts in Ethereum	2501.00674	https://arxiv.org/abs/2501.00674v1	https://arxiv.org/pdf/2501.00674v1.pdf	https://github.com/SAILResearch/replication-24-amir-upc_sentinel	true	false	true	none
https://paperswithcode.com/paper/mcbench-a-benchmark-suite-for-monte-carlo	MCBench: A Benchmark Suite for Monte Carlo Sampling Algorithms	2501.03138	https://arxiv.org/abs/2501.03138v1	https://arxiv.org/pdf/2501.03138v1.pdf	https://github.com/tudo-physik-e4/mcbench	true	true	true	none
https://paperswithcode.com/paper/stability-of-data-dependent-ridge	Stability of Data-Dependent Ridge-Regularization for Inverse Problems	2406.12289	https://arxiv.org/abs/2406.12289v2	https://arxiv.org/pdf/2406.12289v2.pdf	https://github.com/fabianaltekrueger/dataadaptiverr	true	true	true	pytorch
https://paperswithcode.com/paper/2408-00109	Back to the Continuous Attractor	2408.00109	https://arxiv.org/abs/2408.00109v3	https://arxiv.org/pdf/2408.00109v3.pdf	https://github.com/catniplab/back_to_the_continuous_attractor	true	true	false	pytorch
https://paperswithcode.com/paper/normalizing-batch-normalization-for-long	Normalizing Batch Normalization for Long-Tailed Recognition	2501.03122	https://arxiv.org/abs/2501.03122v1	https://arxiv.org/pdf/2501.03122v1.pdf	https://github.com/yuxiangbao/nbn	true	true	true	pytorch
https://paperswithcode.com/paper/generalizable-lightweight-proxy-for-robust-1	Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations	2306.05031	https://arxiv.org/abs/2306.05031v2	https://arxiv.org/pdf/2306.05031v2.pdf	https://github.com/hyeonjeongha/mm-poisonrag	false	false	true	pytorch
https://paperswithcode.com/paper/urinary-tract-infection-detection-in-digital	Urinary Tract Infection Detection in Digital Remote Monitoring: Strategies for Managing Participant-Specific Prediction Complexity	2502.17484	https://arxiv.org/abs/2502.17484v1	https://arxiv.org/pdf/2502.17484v1.pdf	https://github.com/Kexin-Fan/Multi-Source-Analysing	true	false	false	none
https://paperswithcode.com/paper/seconnds-secure-outsourced-neural-network	SecONNds: Secure Outsourced Neural Network Inference on ImageNet	2506.11586	https://arxiv.org/abs/2506.11586v1	https://arxiv.org/pdf/2506.11586v1.pdf	https://github.com/seconnds/seconnds_1_25	true	true	false	none
https://paperswithcode.com/paper/slowcal-sgd-slow-query-points-improve-local	SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization	2304.04169	https://arxiv.org/abs/2304.04169v2	https://arxiv.org/pdf/2304.04169v2.pdf	https://github.com/dahan198/slowcal-sgd	true	true	true	pytorch
https://paperswithcode.com/paper/figstep-jailbreaking-large-vision-language	FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts	2311.05608	https://arxiv.org/abs/2311.05608v3	https://arxiv.org/pdf/2311.05608v3.pdf	https://github.com/thuccslab/figstep	true	true	true	none
https://paperswithcode.com/paper/generating-structured-outputs-from-language	Generating Structured Outputs from Language Models: Benchmark and Studies	2501.10868	https://arxiv.org/abs/2501.10868v1	https://arxiv.org/pdf/2501.10868v1.pdf	https://github.com/guidance-ai/llguidance	true	true	true	none
https://paperswithcode.com/paper/synthetic-data-augmentation-for-enhancing	Synthetic Data Augmentation for Enhancing Harmful Algal Bloom Detection with Machine Learning	2503.03794	https://arxiv.org/abs/2503.03794v1	https://arxiv.org/pdf/2503.03794v1.pdf	https://github.com/Tonyhrule/Synthetic-HAB-ML-Augmentation	true	false	false	none
https://paperswithcode.com/paper/evaluating-knowledge-generation-and-self	Evaluating Knowledge Generation and Self-Refinement Strategies for LLM-based Column Type Annotation	2503.02718	https://arxiv.org/abs/2503.02718v1	https://arxiv.org/pdf/2503.02718v1.pdf	https://github.com/wbsg-uni-mannheim/tabanngpt	true	true	true	pytorch
https://paperswithcode.com/paper/muble-mujoco-and-blender-simulation	MuBlE: MuJoCo and Blender simulation Environment and Benchmark for Task Planning in Robot Manipulation	2503.02834	https://arxiv.org/abs/2503.02834v1	https://arxiv.org/pdf/2503.02834v1.pdf	https://github.com/michaal94/muble	true	true	false	none
https://paperswithcode.com/paper/r2-t2-re-routing-in-test-time-for-multimodal	R2-T2: Re-Routing in Test-Time for Multimodal Mixture-of-Experts	2502.20395	https://arxiv.org/abs/2502.20395v1	https://arxiv.org/pdf/2502.20395v1.pdf	https://github.com/tianyi-lab/R2-T2	true	false	true	pytorch
https://paperswithcode.com/paper/reasoning-language-models-a-blueprint	Reasoning Language Models: A Blueprint	2501.11223	https://arxiv.org/abs/2501.11223v3	https://arxiv.org/pdf/2501.11223v3.pdf	https://github.com/spcl/x1	true	true	true	pytorch
https://paperswithcode.com/paper/efficient-training-of-large-vision-models-via	Efficient Training of Large Vision Models via Advanced Automated Progressive Learning	2410.00350	https://arxiv.org/abs/2410.00350v1	https://arxiv.org/pdf/2410.00350v1.pdf	https://github.com/changlin31/autoprog-zero	true	true	true	pytorch
https://paperswithcode.com/paper/hdee-heterogeneous-domain-expert-ensemble	HDEE: Heterogeneous Domain Expert Ensemble	2502.19385	https://arxiv.org/abs/2502.19385v1	https://arxiv.org/pdf/2502.19385v1.pdf	https://github.com/gensyn-ai/hdee	true	true	true	pytorch
https://paperswithcode.com/paper/fintsb-a-comprehensive-and-practical	FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting	2502.18834	https://arxiv.org/abs/2502.18834v1	https://arxiv.org/pdf/2502.18834v1.pdf	https://github.com/tongjifinlab/fintsbenchmark	true	true	true	pytorch
https://paperswithcode.com/paper/sharingan-a-transformer-architecture-for	Sharingan: A Transformer Architecture for Multi-Person Gaze Following	null	http://openaccess.thecvf.com//content/CVPR2024/html/Tafasca_Sharingan_A_Transformer_Architecture_for_Multi-Person_Gaze_Following_CVPR_2024_paper.html	http://openaccess.thecvf.com//content/CVPR2024/papers/Tafasca_Sharingan_A_Transformer_Architecture_for_Multi-Person_Gaze_Following_CVPR_2024_paper.pdf	https://github.com/idiap/sharingan	false	false	false	pytorch
https://paperswithcode.com/paper/realtabformer-generating-realistic-relational	REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers	2302.02041	https://arxiv.org/abs/2302.02041v1	https://arxiv.org/pdf/2302.02041v1.pdf	https://github.com/worldbank/realtabformer	false	false	true	pytorch
https://paperswithcode.com/paper/deep-common-feature-mining-for-efficient	Deep Common Feature Mining for Efficient Video Semantic Segmentation	2403.02689	https://arxiv.org/abs/2403.02689v2	https://arxiv.org/pdf/2403.02689v2.pdf	https://github.com/buaahugegun/dcfm	true	true	false	pytorch
https://paperswithcode.com/paper/tpch-tensor-interacted-projection-and	TPCH: Tensor-interacted Projection and Cooperative Hashing for Multi-view Clustering	2412.18847	https://arxiv.org/abs/2412.18847v1	https://arxiv.org/pdf/2412.18847v1.pdf	https://github.com/jankin-wang/tpch	true	true	false	none
https://paperswithcode.com/paper/semi-truths-a-large-scale-dataset-of-ai	Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors	2411.07472	https://arxiv.org/abs/2411.07472v1	https://arxiv.org/pdf/2411.07472v1.pdf	https://github.com/j-kruk/semitruths	true	true	true	pytorch
https://paperswithcode.com/paper/invariant-derivations-and-trace-bounds	Invariant derivations and trace bounds	2312.03101	https://arxiv.org/abs/2312.03101v4	https://arxiv.org/pdf/2312.03101v4.pdf	https://github.com/skipgaribaldi/invariant-derivations	true	true	true	none
https://paperswithcode.com/paper/sampling-is-all-you-need-on-modeling-long	Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction	2205.10249	https://arxiv.org/abs/2205.10249v2	https://arxiv.org/pdf/2205.10249v2.pdf	https://github.com/reczoo/FuxiCTR	false	false	true	pytorch
https://paperswithcode.com/paper/edicho-consistent-image-editing-in-the-wild	Edicho: Consistent Image Editing in the Wild	2412.21079	https://arxiv.org/abs/2412.21079v3	https://arxiv.org/pdf/2412.21079v3.pdf	https://github.com/ezioby/edicho	true	true	true	none
https://paperswithcode.com/paper/exploiting-music-source-separation-for	Exploiting Music Source Separation for Automatic Lyrics Transcription with Whisper	2506.15514	https://arxiv.org/abs/2506.15514v1	https://arxiv.org/pdf/2506.15514v1.pdf	https://github.com/jaza-syed/mss-alt	true	true	true	pytorch
https://paperswithcode.com/paper/adversarial-attacks-on-robotic-vision	Adversarial Attacks on Robotic Vision Language Action Models	2506.03350	https://arxiv.org/abs/2506.03350v1	https://arxiv.org/pdf/2506.03350v1.pdf	https://github.com/eliotjones1/robogcg	true	true	false	pytorch
https://paperswithcode.com/paper/navigating-image-restoration-with-var-s	Navigating Image Restoration with VAR's Distribution Alignment Prior	null	http://openaccess.thecvf.com//content/CVPR2025/html/Wang_Navigating_Image_Restoration_with_VARs_Distribution_Alignment_Prior_CVPR_2025_paper.html	http://openaccess.thecvf.com//content/CVPR2025/papers/Wang_Navigating_Image_Restoration_with_VARs_Distribution_Alignment_Prior_CVPR_2025_paper.pdf	https://github.com/siywang541/Varformer	true	true	false	pytorch
https://paperswithcode.com/paper/causal-aware-large-language-models-enhancing	Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting	2505.24710	https://arxiv.org/abs/2505.24710v1	https://arxiv.org/pdf/2505.24710v1.pdf	https://github.com/dmirlab-group/causal-aware_llms	true	true	false	pytorch
https://paperswithcode.com/paper/nfisis-new-perspectives-on-fuzzy-inference	NFISiS: New Perspectives on Fuzzy Inference Systems for Renewable Energy Forecasting	2506.06285	https://arxiv.org/abs/2506.06285v1	https://arxiv.org/pdf/2506.06285v1.pdf	https://github.com/kaikerochaalves/NFISiS_PyPi	true	false	false	none
https://paperswithcode.com/paper/identifying-spurious-correlations-using	Identifying Spurious Correlations using Counterfactual Alignment	2312.02186	https://arxiv.org/abs/2312.02186v3	https://arxiv.org/pdf/2312.02186v3.pdf	https://github.com/ieee8023/latentshift	true	true	true	pytorch
https://paperswithcode.com/paper/cooperative-open-ended-learning-framework-for	Cooperative Open-ended Learning Framework for Zero-shot Coordination	2302.04831	https://arxiv.org/abs/2302.04831v4	https://arxiv.org/pdf/2302.04831v4.pdf	https://github.com/PKU-Alignment/ProAgent	false	false	true	pytorch
https://paperswithcode.com/paper/optimal-group-fair-classifiers-from-linear	A Unified Post-Processing Framework for Group Fairness in Classification	2405.04025	https://arxiv.org/abs/2405.04025v2	https://arxiv.org/pdf/2405.04025v2.pdf	https://github.com/rxian/fair-classification	true	true	true	none
https://paperswithcode.com/paper/teaching-lmms-for-image-quality-scoring-and	Teaching LMMs for Image Quality Scoring and Interpreting	2503.09197	https://arxiv.org/abs/2503.09197v1	https://arxiv.org/pdf/2503.09197v1.pdf	https://github.com/q-future/q-sit	true	true	true	pytorch
https://paperswithcode.com/paper/pretraining-language-models-to-ponder-in	Pretraining Language Models to Ponder in Continuous Space	2505.20674	https://arxiv.org/abs/2505.20674v1	https://arxiv.org/pdf/2505.20674v1.pdf	https://github.com/lumia-group/ponderinglm	true	true	true	pytorch
https://paperswithcode.com/paper/fading-in-the-flow-suppression-of-cold-gas	Fading in the Flow: Suppression of cold gas growth in expanding galactic outflows	2506.08545	https://arxiv.org/abs/2506.08545v2	https://arxiv.org/pdf/2506.08545v2.pdf	https://github.com/dutta-alankar/cloud-crushing_PLUTO	true	true	false	none
https://paperswithcode.com/paper/group-robust-sample-reweighting-for	Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions	2503.07315	https://arxiv.org/abs/2503.07315v1	https://arxiv.org/pdf/2503.07315v1.pdf	https://github.com/qiaoruiyt/gsr	true	true	false	pytorch
https://paperswithcode.com/paper/planetesimal-impact-vapor-plumes-and-nebular	Planetesimal Impact Vapor Plumes and Nebular Shocks form Chondritic Mixtures	2503.05636	https://arxiv.org/abs/2503.05636v1	https://arxiv.org/pdf/2503.05636v1.pdf	https://github.com/ststewart/ivans	true	true	false	none
https://paperswithcode.com/paper/chatbench-from-static-benchmarks-to-human-ai	ChatBench: From Static Benchmarks to Human-AI Evaluation	2504.07114	https://arxiv.org/abs/2504.07114v1	https://arxiv.org/pdf/2504.07114v1.pdf	https://github.com/serinachang5/interactive-eval	true	true	true	none
https://paperswithcode.com/paper/infofusion-controller-informed-trrt-star-with	InfoFusion Controller: Informed TRRT Star with Mutual Information based on Fusion of Pure Pursuit and MPC for Enhanced Path Planning	2503.06010	https://arxiv.org/abs/2503.06010v1	https://arxiv.org/pdf/2503.06010v1.pdf	https://github.com/drawingprocess/infofusioncontroller	true	true	false	none
https://paperswithcode.com/paper/generator-a-long-context-generative-genomic	GENERator: A Long-Context Generative Genomic Foundation Model	2502.07272	https://arxiv.org/abs/2502.07272v3	https://arxiv.org/pdf/2502.07272v3.pdf	https://github.com/generteam/generator	true	true	true	pytorch
https://paperswithcode.com/paper/controller-distillation-reduces-fragile-brain	Controller Distillation Reduces Fragile Brain-Body Co-Adaptation and Enables Migrations in MAP-Elites	2504.06523	https://arxiv.org/abs/2504.06523v1	https://arxiv.org/pdf/2504.06523v1.pdf	https://github.com/mertan-a/pollination	true	false	false	pytorch
https://paperswithcode.com/paper/holistic-fusion-task-and-setup-agnostic-robot	Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs	2504.06479	https://arxiv.org/abs/2504.06479v1	https://arxiv.org/pdf/2504.06479v1.pdf	https://github.com/leggedrobotics/holistic_fusion	true	false	true	none
https://paperswithcode.com/paper/enforcement-agents-enhancing-accountability	Enforcement Agents: Enhancing Accountability and Resilience in Multi-Agent AI Frameworks	2504.04070	https://arxiv.org/abs/2504.04070v1	https://arxiv.org/pdf/2504.04070v1.pdf	https://github.com/SAGAR-TAMANG/Enforcement-Agents	true	false	true	none
https://paperswithcode.com/paper/frnet-frustum-range-networks-for-scalable	FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation	2312.04484	https://arxiv.org/abs/2312.04484v3	https://arxiv.org/pdf/2312.04484v3.pdf	https://github.com/Xiangxu-0103/FRNet	true	true	true	pytorch
https://paperswithcode.com/paper/boosting-relational-deep-learning-with	Boosting Relational Deep Learning with Pretrained Tabular Models	2504.04934	https://arxiv.org/abs/2504.04934v1	https://arxiv.org/pdf/2504.04934v1.pdf	https://github.com/AntonioLonga/LightRDL	true	true	false	pytorch
https://paperswithcode.com/paper/continual-deep-reinforcement-learning-with	Continual Deep Reinforcement Learning with Task-Agnostic Policy Distillation	2411.16532	https://arxiv.org/abs/2411.16532v1	https://arxiv.org/pdf/2411.16532v1.pdf	https://github.com/wabbajack1/tapd	true	true	true	pytorch
https://paperswithcode.com/paper/darkelf-a-python-package-for-dark-matter	DarkELF: A python package for dark matter scattering in dielectric targets	2104.12786	https://arxiv.org/abs/2104.12786v1	https://arxiv.org/pdf/2104.12786v1.pdf	https://github.com/tongylin/DarkELF	true	true	true	none
https://paperswithcode.com/paper/dark-matter-direct-detection-from-the-single	Dark matter direct detection from the single phonon to the nuclear recoil regime	2205.02250	https://arxiv.org/abs/2205.02250v2	https://arxiv.org/pdf/2205.02250v2.pdf	https://github.com/tongylin/DarkELF	true	true	true	none
https://paperswithcode.com/paper/segagent-exploring-pixel-understanding-1	SegAgent: Exploring Pixel Understanding Capabilities in MLLMs by Imitating Human Annotator Trajectories	2503.08625	https://arxiv.org/abs/2503.08625v1	https://arxiv.org/pdf/2503.08625v1.pdf	https://github.com/aim-uofa/SegAgent	true	true	true	none
https://paperswithcode.com/paper/rsar-restricted-state-angle-resolver-and	RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark	2501.04440	https://arxiv.org/abs/2501.04440v1	https://arxiv.org/pdf/2501.04440v1.pdf	https://github.com/visionxlab/earth-adapter	false	false	true	pytorch
https://paperswithcode.com/paper/earth-adapter-bridge-the-geospatial-domain	Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency Adaptation	2504.06220	https://arxiv.org/abs/2504.06220v3	https://arxiv.org/pdf/2504.06220v3.pdf	https://github.com/visionxlab/earth-adapter	true	true	true	pytorch
https://paperswithcode.com/paper/cyberllminstruct-a-new-dataset-for-analysing	CyberLLMInstruct: A New Dataset for Analysing Safety of Fine-Tuned LLMs Using Cyber Security Data	2503.09334	https://arxiv.org/abs/2503.09334v2	https://arxiv.org/pdf/2503.09334v2.pdf	https://github.com/adelsamir01/cyberllminstruct	true	true	true	pytorch
https://paperswithcode.com/paper/growing-black-hole-hair-in-nonminimally	Growing black-hole hair in nonminimally coupled biscalar gravity	2501.14034	https://arxiv.org/abs/2501.14034v1	https://arxiv.org/pdf/2501.14034v1.pdf	https://bitbucket.org/canuda/canuda_axidilaton	true	true	false	none
https://paperswithcode.com/paper/the-kodaira-dimension-of-hilbert-modular	The Kodaira dimension of Hilbert modular threefolds	2501.15719	https://arxiv.org/abs/2501.15719v1	https://arxiv.org/pdf/2501.15719v1.pdf	https://github.com/adammlogan/hilbert-modular-threefolds	true	true	false	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.