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/privacy-issues-in-large-language-models-a	Privacy Issues in Large Language Models: A Survey	2312.06717	https://arxiv.org/abs/2312.06717v4	https://arxiv.org/pdf/2312.06717v4.pdf	https://github.com/safr-ml-lab/survey-llm	true	true	true	tf
https://paperswithcode.com/paper/effects-of-diversity-incentives-on-sample	Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation	2401.06643	https://arxiv.org/abs/2401.06643v3	https://arxiv.org/pdf/2401.06643v3.pdf	https://github.com/kinit-sk/llm-div-incts	true	true	true	pytorch
https://paperswithcode.com/paper/detecting-attended-visual-targets-in-video	Detecting Attended Visual Targets in Video	2003.02501	https://arxiv.org/abs/2003.02501v2	https://arxiv.org/pdf/2003.02501v2.pdf	https://github.com/ejcgt/attention-target-detection	false	true	true	pytorch
https://paperswithcode.com/paper/spatially-adaptive-self-supervised-learning	Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising	2303.14934	https://arxiv.org/abs/2303.14934v1	https://arxiv.org/pdf/2303.14934v1.pdf	https://github.com/nagejacob/spatiallyadaptivessid	true	true	true	pytorch
https://paperswithcode.com/paper/rethinking-node-wise-propagation-for-large	Rethinking Node-wise Propagation for Large-scale Graph Learning	2402.06128	https://arxiv.org/abs/2402.06128v1	https://arxiv.org/pdf/2402.06128v1.pdf	https://github.com/xkli-allen/atp	true	true	false	pytorch
https://paperswithcode.com/paper/multi-granularity-correspondence-learning-1	Multi-granularity Correspondence Learning from Long-term Noisy Videos	2401.16702	https://arxiv.org/abs/2401.16702v1	https://arxiv.org/pdf/2401.16702v1.pdf	https://github.com/XLearning-SCU/2024-ICLR-Norton	false	false	true	pytorch
https://paperswithcode.com/paper/llm4eda-emerging-progress-in-large-language	LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation	2401.12224	https://arxiv.org/abs/2401.12224v1	https://arxiv.org/pdf/2401.12224v1.pdf	https://github.com/thinklab-sjtu/awesome-llm4eda	true	true	true	none
https://paperswithcode.com/paper/training-on-test-proteins-improves-fitness	Training on test proteins improves fitness, structure, and function prediction	2411.02109	https://arxiv.org/abs/2411.02109v1	https://arxiv.org/pdf/2411.02109v1.pdf	https://github.com/anton-bushuiev/ProteinTTT	true	false	true	pytorch
https://paperswithcode.com/paper/structured-complex-and-time-complete-temporal	SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting	2312.01052	https://arxiv.org/abs/2312.01052v2	https://arxiv.org/pdf/2312.01052v2.pdf	https://github.com/yecchen/gdelt-complexevent	true	true	true	pytorch
https://paperswithcode.com/paper/a-robust-ensemble-algorithm-for-ischemic	A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge	2403.19425	https://arxiv.org/abs/2403.19425v2	https://arxiv.org/pdf/2403.19425v2.pdf	https://github.com/ezequieldlrosa/isles22	true	true	false	none
https://paperswithcode.com/paper/khronos-a-unified-approach-for-spatio	Khronos: A Unified Approach for Spatio-Temporal Metric-Semantic SLAM in Dynamic Environments	2402.13817	https://arxiv.org/abs/2402.13817v2	https://arxiv.org/pdf/2402.13817v2.pdf	https://github.com/mit-spark/khronos	true	true	true	none
https://paperswithcode.com/paper/scene-graph-generation-from-hierarchical	Hierarchical Relationships: A New Perspective to Enhance Scene Graph Generation	2303.06842	https://arxiv.org/abs/2303.06842v5	https://arxiv.org/pdf/2303.06842v5.pdf	https://github.com/bowen-upenn/scene_graph_commonsense	true	false	true	pytorch
https://paperswithcode.com/paper/a-closed-form-solution-to-best-rank-1-tensor	Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation	2103.02898	https://arxiv.org/abs/2103.02898v3	https://arxiv.org/pdf/2103.02898v3.pdf	https://github.com/gkazunii/Legendre-tucker-rank-reduction	true	false	true	none
https://paperswithcode.com/paper/translating-images-to-road-network-a-non-1	Translating Images to Road Network: A Sequence-to-Sequence Perspective	2402.08207	https://arxiv.org/abs/2402.08207v2	https://arxiv.org/pdf/2402.08207v2.pdf	https://github.com/MindSpore-scientific-2/code-3/tree/main/translating-math-formula-images	false	false	false	mindspore
https://paperswithcode.com/paper/activerag-revealing-the-treasures-of	ActiveRAG: Autonomously Knowledge Assimilation and Accommodation through Retrieval-Augmented Agents	2402.13547	https://arxiv.org/abs/2402.13547v2	https://arxiv.org/pdf/2402.13547v2.pdf	https://github.com/openmatch/activerag	true	true	true	none
https://paperswithcode.com/paper/instruction-tuned-language-models-are-better	Instruction-tuned Language Models are Better Knowledge Learners	2402.12847	https://arxiv.org/abs/2402.12847v2	https://arxiv.org/pdf/2402.12847v2.pdf	https://github.com/edward-sun/pit	true	true	true	none
https://paperswithcode.com/paper/scale-match-for-tiny-person-detection	Scale Match for Tiny Person Detection	1912.10664	https://arxiv.org/abs/1912.10664v1	https://arxiv.org/pdf/1912.10664v1.pdf	https://github.com/ucas-vg/TinyBenchmark	true	true	true	pytorch
https://paperswithcode.com/paper/object-localization-under-single-coarse-point	Object Localization under Single Coarse Point Supervision	2203.09338	https://arxiv.org/abs/2203.09338v1	https://arxiv.org/pdf/2203.09338v1.pdf	https://github.com/ucas-vg/TinyBenchmark	false	false	true	pytorch
https://paperswithcode.com/paper/point-to-box-network-for-accurate-object	Point-to-Box Network for Accurate Object Detection via Single Point Supervision	2207.06827	https://arxiv.org/abs/2207.06827v2	https://arxiv.org/pdf/2207.06827v2.pdf	https://github.com/ucas-vg/TinyBenchmark	false	false	true	pytorch
https://paperswithcode.com/paper/cpr-object-localization-via-single-coarse	CPR++: Object Localization via Single Coarse Point Supervision	2401.17203	https://arxiv.org/abs/2401.17203v1	https://arxiv.org/pdf/2401.17203v1.pdf	https://github.com/ucas-vg/TinyBenchmark	false	false	true	pytorch
https://paperswithcode.com/paper/caphuman-capture-your-moments-in-parallel	CapHuman: Capture Your Moments in Parallel Universes	2402.00627	https://arxiv.org/abs/2402.00627v3	https://arxiv.org/pdf/2402.00627v3.pdf	https://github.com/vamosc/caphuman	true	true	true	pytorch
https://paperswithcode.com/paper/pap-rec-personalized-automatic-prompt-for	PAP-REC: Personalized Automatic Prompt for Recommendation Language Model	2402.00284	https://arxiv.org/abs/2402.00284v1	https://arxiv.org/pdf/2402.00284v1.pdf	https://github.com/rutgerswiselab/pap-rec	true	true	false	pytorch
https://paperswithcode.com/paper/wordepth-variational-language-prior-for	WorDepth: Variational Language Prior for Monocular Depth Estimation	2404.03635	https://arxiv.org/abs/2404.03635v4	https://arxiv.org/pdf/2404.03635v4.pdf	https://github.com/adonis-galaxy/wordepth	true	true	true	pytorch
https://paperswithcode.com/paper/improving-multimodal-classification-of-social	Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary Tasks	2309.07794	https://arxiv.org/abs/2309.07794v2	https://arxiv.org/pdf/2309.07794v2.pdf	https://github.com/danaesavi/socialmedia-textimage-classification-auxlosses	true	true	false	pytorch
https://paperswithcode.com/paper/attention-based-simple-primitives-for-open	Attention Based Simple Primitives for Open World Compositional Zero-Shot Learning	2407.13715	https://arxiv.org/abs/2407.13715v1	https://arxiv.org/pdf/2407.13715v1.pdf	https://github.com/ans92/ASP	true	false	true	pytorch
https://paperswithcode.com/paper/learning-semantic-proxies-from-visual-prompts	Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning	2402.02340	https://arxiv.org/abs/2402.02340v2	https://arxiv.org/pdf/2402.02340v2.pdf	https://github.com/noahsark/parameterefficient-dml	true	true	true	pytorch
https://paperswithcode.com/paper/fade-fusing-the-assets-of-decoder-and-encoder	FADE: Fusing the Assets of Decoder and Encoder for Task-Agnostic Upsampling	2207.10392	https://arxiv.org/abs/2207.10392v2	https://arxiv.org/pdf/2207.10392v2.pdf	https://github.com/poppinace/fade	false	false	true	pytorch
https://paperswithcode.com/paper/promptrr-diffusion-models-as-prompt	PromptRR: Diffusion Models as Prompt Generators for Single Image Reflection Removal	2402.02374	https://arxiv.org/abs/2402.02374v1	https://arxiv.org/pdf/2402.02374v1.pdf	https://github.com/taowangzj/promptrr	true	true	true	none
https://paperswithcode.com/paper/boosting-adversarial-transferability-across	Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping	2402.03951	https://arxiv.org/abs/2402.03951v1	https://arxiv.org/pdf/2402.03951v1.pdf	https://github.com/linqinliang/decowa	true	true	true	none
https://paperswithcode.com/paper/learning-to-simulate-complex-physics-with	Learning to Simulate Complex Physics with Graph Networks	2002.09405	https://arxiv.org/abs/2002.09405v2	https://arxiv.org/pdf/2002.09405v2.pdf	https://github.com/tumaer/lagrangebench	false	false	true	jax
https://paperswithcode.com/paper/feedback-loops-with-language-models-drive-in	Feedback Loops With Language Models Drive In-Context Reward Hacking	2402.06627	https://arxiv.org/abs/2402.06627v3	https://arxiv.org/pdf/2402.06627v3.pdf	https://github.com/aypan17/llm-feedback	true	true	true	none
https://paperswithcode.com/paper/how-faithful-is-your-synthetic-data-sample	How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models	2102.08921	https://arxiv.org/abs/2102.08921v2	https://arxiv.org/pdf/2102.08921v2.pdf	https://github.com/amazon-science/tabsyn	false	false	true	pytorch
https://paperswithcode.com/paper/actor-critic-algorithms-for-fiber-sampling	Learning to sample fibers for goodness-of-fit testing	2405.13950	https://arxiv.org/abs/2405.13950v3	https://arxiv.org/pdf/2405.13950v3.pdf	https://github.com/DLR-RM/stable-baselines3	true	true	false	pytorch
https://paperswithcode.com/paper/knowledge-driven-cross-document-relation	Knowledge-Driven Cross-Document Relation Extraction	2405.13546	https://arxiv.org/abs/2405.13546v2	https://arxiv.org/pdf/2405.13546v2.pdf	https://github.com/kracr/cross-doc-relation-extraction	true	true	false	pytorch
https://paperswithcode.com/paper/neural-optimizer-equation-decay-function-and	Neural Optimizer Equation, Decay Function, and Learning Rate Schedule Joint Evolution	2404.06679	https://arxiv.org/abs/2404.06679v1	https://arxiv.org/pdf/2404.06679v1.pdf	https://github.com/oustudent/neuraloptimizersearch	true	true	false	tf
https://paperswithcode.com/paper/how-to-tune-a-multilingual-encoder-model-for	How to Tune a Multilingual Encoder Model for Germanic Languages: A Study of PEFT, Full Fine-Tuning, and Language Adapters	2501.06025	https://arxiv.org/abs/2501.06025v1	https://arxiv.org/pdf/2501.06025v1.pdf	https://github.com/rominaoji/german-language-adapter	true	true	true	pytorch
https://paperswithcode.com/paper/fails-a-framework-for-automated-collection	FAILS: A Framework for Automated Collection and Analysis of LLM Service Incidents	2503.12185	https://arxiv.org/abs/2503.12185v1	https://arxiv.org/pdf/2503.12185v1.pdf	https://github.com/atlarge-research/fails	true	true	false	none
https://paperswithcode.com/paper/towards-understanding-jailbreak-attacks-in	Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis	2406.10794	https://arxiv.org/abs/2406.10794v3	https://arxiv.org/pdf/2406.10794v3.pdf	https://github.com/yuplin2333/representation-space-jailbreak	true	true	true	pytorch
https://paperswithcode.com/paper/shuttleset-a-human-annotated-stroke-level	ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis	2306.04948	https://arxiv.org/abs/2306.04948v1	https://arxiv.org/pdf/2306.04948v1.pdf	https://github.com/andychiangsh/badge	false	false	true	none
https://paperswithcode.com/paper/ehrnoteqa-a-patient-specific-question	EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries	2402.16040	https://arxiv.org/abs/2402.16040v5	https://arxiv.org/pdf/2402.16040v5.pdf	https://github.com/ji-youn-kim/ehrnoteqa	true	true	true	pytorch
https://paperswithcode.com/paper/fvit-a-focal-vision-transformer-with-gabor	FViT: A Focal Vision Transformer with Gabor Filter	2402.11303	https://arxiv.org/abs/2402.11303v3	https://arxiv.org/pdf/2402.11303v3.pdf	https://github.com/nkusyl/fvit	true	true	true	pytorch
https://paperswithcode.com/paper/generative-3d-part-assembly-via-part-whole	Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing	2402.17464	https://arxiv.org/abs/2402.17464v3	https://arxiv.org/pdf/2402.17464v3.pdf	https://github.com/pkudba/3dhpa	true	true	false	pytorch
https://paperswithcode.com/paper/pcr-99-a-practical-method-for-point-cloud	PCR-99: A Practical Method for Point Cloud Registration with 99 Percent Outliers	2402.16598	https://arxiv.org/abs/2402.16598v6	https://arxiv.org/pdf/2402.16598v6.pdf	https://github.com/sunghoon031/pcr-99	true	true	true	none
https://paperswithcode.com/paper/a-framework-for-standardizing-similarity	A Framework for Standardizing Similarity Measures in a Rapidly Evolving Field	2409.18333	https://arxiv.org/abs/2409.18333v1	https://arxiv.org/pdf/2409.18333v1.pdf	https://github.com/nacloos/similarity-repository	true	false	false	pytorch
https://paperswithcode.com/paper/soul-unlocking-the-power-of-second-order	SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning	2404.18239	https://arxiv.org/abs/2404.18239v4	https://arxiv.org/pdf/2404.18239v4.pdf	https://github.com/optml-group/soul	true	true	true	none
https://paperswithcode.com/paper/label-informed-contrastive-pretraining-for	Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs	2402.17791	https://arxiv.org/abs/2402.17791v1	https://arxiv.org/pdf/2402.17791v1.pdf	https://github.com/zhangtia16/licap	true	true	true	pytorch
https://paperswithcode.com/paper/univs-unified-and-universal-video	UniVS: Unified and Universal Video Segmentation with Prompts as Queries	2402.18115	https://arxiv.org/abs/2402.18115v2	https://arxiv.org/pdf/2402.18115v2.pdf	https://github.com/minghanli/univs	true	true	true	pytorch
https://paperswithcode.com/paper/rethinking-centered-kernel-alignment-in	Rethinking Centered Kernel Alignment in Knowledge Distillation	2401.11824	https://arxiv.org/abs/2401.11824v4	https://arxiv.org/pdf/2401.11824v4.pdf	https://github.com/klayand/pcka	true	true	false	none
https://paperswithcode.com/paper/retaining-key-information-under-high	Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs	2406.02376	https://arxiv.org/abs/2406.02376v2	https://arxiv.org/pdf/2406.02376v2.pdf	https://github.com/DeepLearnXMU/QGC	true	true	false	pytorch
https://paperswithcode.com/paper/sonata-self-supervised-learning-of-reliable	Sonata: Self-Supervised Learning of Reliable Point Representations	2503.16429	https://arxiv.org/abs/2503.16429v1	https://arxiv.org/pdf/2503.16429v1.pdf	https://github.com/facebookresearch/sonata	true	false	true	pytorch
https://paperswithcode.com/paper/dimal-deep-isometric-manifold-learning-using	DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic Sampling	1711.06011	http://arxiv.org/abs/1711.06011v2	http://arxiv.org/pdf/1711.06011v2.pdf	https://github.com/paigautam/DIMAL	true	false	true	pytorch
https://paperswithcode.com/paper/mila-multi-view-intensive-fidelity-long-term	MiLA: Multi-view Intensive-fidelity Long-term Video Generation World Model for Autonomous Driving	2503.15875	https://arxiv.org/abs/2503.15875v1	https://arxiv.org/pdf/2503.15875v1.pdf	https://github.com/xiaomi-mlab/mila.github.io	true	true	false	none
https://paperswithcode.com/paper/fast-graph-condensation-with-structure-based	Fast Graph Condensation with Structure-based Neural Tangent Kernel	2310.11046	https://arxiv.org/abs/2310.11046v2	https://arxiv.org/pdf/2310.11046v2.pdf	https://github.com/wanglin0126/gcsntk	true	true	false	pytorch
https://paperswithcode.com/paper/usat-a-universal-speaker-adaptive-text-to	USAT: A Universal Speaker-Adaptive Text-to-Speech Approach	2404.18094	https://arxiv.org/abs/2404.18094v1	https://arxiv.org/pdf/2404.18094v1.pdf	https://github.com/mushanshanshan/esltts	true	true	true	none
https://paperswithcode.com/paper/safe-deep-model-based-reinforcement-learning	Safe Deep Model-Based Reinforcement Learning with Lyapunov Functions	2405.16184	https://arxiv.org/abs/2405.16184v1	https://arxiv.org/pdf/2405.16184v1.pdf	https://github.com/harryzhangOG/salved	true	true	false	tf
https://paperswithcode.com/paper/clip-ebc-clip-can-count-accurately-through	CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification	2403.09281	https://arxiv.org/abs/2403.09281v3	https://arxiv.org/pdf/2403.09281v3.pdf	https://github.com/Yiming-M/CLIP-EBC	true	true	true	pytorch
https://paperswithcode.com/paper/3am-an-ambiguity-aware-multi-modal-machine	3AM: An Ambiguity-Aware Multi-Modal Machine Translation Dataset	2404.18413	https://arxiv.org/abs/2404.18413v1	https://arxiv.org/pdf/2404.18413v1.pdf	https://github.com/maxylee/3am	true	true	false	none
https://paperswithcode.com/paper/oodrobustbench-benchmarking-and-analyzing	OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift	2310.12793	https://arxiv.org/abs/2310.12793v2	https://arxiv.org/pdf/2310.12793v2.pdf	https://github.com/treelli/apt	false	false	true	pytorch
https://paperswithcode.com/paper/what-do-we-learn-from-inverting-clip-models	What do we learn from inverting CLIP models?	2403.02580	https://arxiv.org/abs/2403.02580v1	https://arxiv.org/pdf/2403.02580v1.pdf	https://github.com/hamidkazemi22/clipinversion	true	true	true	pytorch
https://paperswithcode.com/paper/xoftr-cross-modal-feature-matching	XoFTR: Cross-modal Feature Matching Transformer	2404.09692	https://arxiv.org/abs/2404.09692v1	https://arxiv.org/pdf/2404.09692v1.pdf	https://github.com/ondert/xoftr	true	true	true	pytorch
https://paperswithcode.com/paper/actor-identified-spatiotemporal-action	Actor-identified Spatiotemporal Action Detection --- Detecting Who Is Doing What in Videos	2208.12940	https://arxiv.org/abs/2208.12940v2	https://arxiv.org/pdf/2208.12940v2.pdf	https://github.com/fandulu/asad	true	true	true	none
https://paperswithcode.com/paper/inverse-decision-making-using-neural	Inverse decision-making using neural amortized Bayesian actors	2409.03710	https://arxiv.org/abs/2409.03710v2	https://arxiv.org/pdf/2409.03710v2.pdf	https://github.com/rothkopflab/naba	true	true	false	jax
https://paperswithcode.com/paper/approach-to-predicting-news-a-precise-multi	Approach to Predicting News -- A Precise Multi-LSTM Network With BERT	2204.12093	https://arxiv.org/abs/2204.12093v1	https://arxiv.org/pdf/2204.12093v1.pdf	https://github.com/LanaChen0/Predict_News	true	true	true	tf
https://paperswithcode.com/paper/language-model-adaptation-to-specialized	Language Model Adaptation to Specialized Domains through Selective Masking based on Genre and Topical Characteristics	2402.12036	https://arxiv.org/abs/2402.12036v2	https://arxiv.org/pdf/2402.12036v2.pdf	https://github.com/ygorg/legal-masking	true	true	true	pytorch
https://paperswithcode.com/paper/rephrase-and-respond-let-large-language	Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves	2311.04205	https://arxiv.org/abs/2311.04205v2	https://arxiv.org/pdf/2311.04205v2.pdf	https://github.com/xirui-li/drattack	false	false	true	none
https://paperswithcode.com/paper/data-filtering-networks	Data Filtering Networks	2309.17425	https://arxiv.org/abs/2309.17425v3	https://arxiv.org/pdf/2309.17425v3.pdf	https://github.com/apple/ml-mobileclip	false	false	true	pytorch
https://paperswithcode.com/paper/sigmoid-loss-for-language-image-pre-training	Sigmoid Loss for Language Image Pre-Training	2303.15343	https://arxiv.org/abs/2303.15343v4	https://arxiv.org/pdf/2303.15343v4.pdf	https://github.com/apple/ml-mobileclip	false	false	true	pytorch
https://paperswithcode.com/paper/learning-transferable-visual-models-from	Learning Transferable Visual Models From Natural Language Supervision	2103.00020	https://arxiv.org/abs/2103.00020v1	https://arxiv.org/pdf/2103.00020v1.pdf	https://github.com/apple/ml-mobileclip	false	false	true	pytorch
https://paperswithcode.com/paper/llm-as-os-llmao-agents-as-apps-envisioning	LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem	2312.03815	https://arxiv.org/abs/2312.03815v2	https://arxiv.org/pdf/2312.03815v2.pdf	https://github.com/agiresearch/aios	false	false	true	none
https://paperswithcode.com/paper/on-the-convergence-of-locally-adaptive-and	On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network Posteriors	2403.08609	https://arxiv.org/abs/2403.08609v2	https://arxiv.org/pdf/2403.08609v2.pdf	https://github.com/timrensmeyer/Convergence-Experiments	true	true	false	pytorch
https://paperswithcode.com/paper/tetrasphere-a-neural-descriptor-for-o-3	TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis	2211.14456	https://arxiv.org/abs/2211.14456v6	https://arxiv.org/pdf/2211.14456v6.pdf	https://github.com/pavlo-melnyk/tetrasphere	true	true	true	pytorch
https://paperswithcode.com/paper/generative-ensemble-deep-learning-severe	Generative ensemble deep learning severe weather prediction from a deterministic convection-allowing model	2310.06045	https://arxiv.org/abs/2310.06045v2	https://arxiv.org/pdf/2310.06045v2.pdf	https://github.com/yingkaisha/aies_d_23_0094	true	true	true	tf
https://paperswithcode.com/paper/balancing-act-constraining-disparate-impact	Balancing Act: Constraining Disparate Impact in Sparse Models	2310.20673	https://arxiv.org/abs/2310.20673v2	https://arxiv.org/pdf/2310.20673v2.pdf	https://github.com/merajhashemi/balancing-act	true	true	true	pytorch
https://paperswithcode.com/paper/pathfinding-future-pim-architectures-by	Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology	2308.00846	https://arxiv.org/abs/2308.00846v3	https://arxiv.org/pdf/2308.00846v3.pdf	https://github.com/via-research/upimulator	true	true	true	none
https://paperswithcode.com/paper/core-llm-as-interpreter-for-natural-language	AIOS Compiler: LLM as Interpreter for Natural Language Programming and Flow Programming of AI Agents	2405.06907	https://arxiv.org/abs/2405.06907v2	https://arxiv.org/pdf/2405.06907v2.pdf	https://github.com/agiresearch/aios	true	true	false	none
https://paperswithcode.com/paper/contextual-learning-in-fourier-complex-field	Contextual Learning in Fourier Complex Field for VHR Remote Sensing Images	2210.15972	https://arxiv.org/abs/2210.15972v1	https://arxiv.org/pdf/2210.15972v1.pdf	https://github.com/MindCode-4/code-11/tree/main/contextual-learning	false	false	false	mindspore
https://paperswithcode.com/paper/approaching-test-time-augmentation-in-the	Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural Networks	2304.05104	https://arxiv.org/abs/2304.05104v2	https://arxiv.org/pdf/2304.05104v2.pdf	https://github.com/pedrormconde/mv-atta	true	true	true	pytorch
https://paperswithcode.com/paper/orco-towards-better-generalization-via	OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning	2403.18550	https://arxiv.org/abs/2403.18550v1	https://arxiv.org/pdf/2403.18550v1.pdf	https://github.com/noorahmedds/orco	true	true	true	pytorch
https://paperswithcode.com/paper/computational-sentence-level-metrics	Computational Sentence-level Metrics Predicting Human Sentence Comprehension	2403.15822	https://arxiv.org/abs/2403.15822v2	https://arxiv.org/pdf/2403.15822v2.pdf	https://github.com/fivehills/sentence-relevance-and-sentence-surprisal	true	true	false	none
https://paperswithcode.com/paper/homogeneous-tokenizer-matters-homogeneous	Homogeneous Tokenizer Matters: Homogeneous Visual Tokenizer for Remote Sensing Image Understanding	2403.18593	https://arxiv.org/abs/2403.18593v2	https://arxiv.org/pdf/2403.18593v2.pdf	https://github.com/geox-lab/hook	true	true	true	pytorch
https://paperswithcode.com/paper/deepsdf-learning-continuous-signed-distance	DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation	1901.05103	http://arxiv.org/abs/1901.05103v1	http://arxiv.org/pdf/1901.05103v1.pdf	https://github.com/maurock/deepsdf	false	false	true	pytorch
https://paperswithcode.com/paper/clip-fields-weakly-supervised-semantic-fields	CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory	2210.05663	https://arxiv.org/abs/2210.05663v3	https://arxiv.org/pdf/2210.05663v3.pdf	https://github.com/notmahi/clip-fields	true	false	true	pytorch
https://paperswithcode.com/paper/diffusionface-towards-a-comprehensive-dataset	DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery Analysis	2403.18471	https://arxiv.org/abs/2403.18471v1	https://arxiv.org/pdf/2403.18471v1.pdf	https://github.com/rapisurazurite/diffface	true	true	false	none
https://paperswithcode.com/paper/unprocessing-seven-years-of-algorithmic	Unprocessing Seven Years of Algorithmic Fairness	2306.07261	https://arxiv.org/abs/2306.07261v5	https://arxiv.org/pdf/2306.07261v5.pdf	https://github.com/socialfoundations/error-parity	true	true	true	none
https://paperswithcode.com/paper/weight-inherited-distillation-for-task	Weight-Inherited Distillation for Task-Agnostic BERT Compression	2305.09098	https://arxiv.org/abs/2305.09098v2	https://arxiv.org/pdf/2305.09098v2.pdf	https://github.com/wutaiqiang/WID-NAACL2024	true	true	true	pytorch
https://paperswithcode.com/paper/a-structural-text-based-scaling-model-for	A Structural Text-Based Scaling Model for Analyzing Political Discourse	2410.11897	https://arxiv.org/abs/2410.11897v1	https://arxiv.org/pdf/2410.11897v1.pdf	https://github.com/vavrajan/stbs	true	true	true	tf
https://paperswithcode.com/paper/nach0-multimodal-natural-and-chemical	nach0: Multimodal Natural and Chemical Languages Foundation Model	2311.12410	https://arxiv.org/abs/2311.12410v3	https://arxiv.org/pdf/2311.12410v3.pdf	https://github.com/insilicomedicine/nach0	true	true	true	none
https://paperswithcode.com/paper/decode-neural-signal-as-speech	NeuSpeech: Decode Neural signal as Speech	2403.01748	https://arxiv.org/abs/2403.01748v3	https://arxiv.org/pdf/2403.01748v3.pdf	https://github.com/mikewangwzhl/eeg-to-text	false	false	true	pytorch
https://paperswithcode.com/paper/gptscore-evaluate-as-you-desire	GPTScore: Evaluate as You Desire	2302.04166	https://arxiv.org/abs/2302.04166v2	https://arxiv.org/pdf/2302.04166v2.pdf	https://github.com/osu-nlp-group/llm-cn-eval	false	false	true	pytorch
https://paperswithcode.com/paper/using-pre-trained-language-models-for	Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study	2204.01440	https://arxiv.org/abs/2204.01440v1	https://arxiv.org/pdf/2204.01440v1.pdf	https://github.com/osu-nlp-group/llm-cn-eval	false	false	true	pytorch
https://paperswithcode.com/paper/mmoe-mixture-of-multimodal-interaction	MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts	2311.09580	https://arxiv.org/abs/2311.09580v3	https://arxiv.org/pdf/2311.09580v3.pdf	https://github.com/lwaekfjlk/mmoe	true	true	true	pytorch
https://paperswithcode.com/paper/on-interference-rejection-using-riemannian	On Interference-Rejection Using Riemannian Geometry for Direction of Arrival Estimation	2301.03399	https://arxiv.org/abs/2301.03399v2	https://arxiv.org/pdf/2301.03399v2.pdf	https://github.com/amitaybar/interference-rejection-using-riemannian-geometry-for-doa-estimation	true	true	false	none
https://paperswithcode.com/paper/integrate-the-essence-and-eliminate-the-dross	Integrate the Essence and Eliminate the Dross: Fine-Grained Self-Consistency for Free-Form Language Generation	2407.02056	https://arxiv.org/abs/2407.02056v1	https://arxiv.org/pdf/2407.02056v1.pdf	https://github.com/WangXinglin/FSC	true	true	true	none
https://paperswithcode.com/paper/aetta-label-free-accuracy-estimation-for-test	AETTA: Label-Free Accuracy Estimation for Test-Time Adaptation	2404.01351	https://arxiv.org/abs/2404.01351v1	https://arxiv.org/pdf/2404.01351v1.pdf	https://github.com/taeckyung/aetta	true	true	false	pytorch
https://paperswithcode.com/paper/age-of-information-in-prioritized-random	Age of Information in Prioritized Random Access	2112.01182	https://arxiv.org/abs/2112.01182v1	https://arxiv.org/pdf/2112.01182v1.pdf	https://github.com/khachoang1412/AoI_prioritized_random_access	true	false	false	none
https://paperswithcode.com/paper/quantifying-distribution-shifts-and	Quantifying Distribution Shifts and Uncertainties for Enhanced Model Robustness in Machine Learning Applications	2405.01978	https://arxiv.org/abs/2405.01978v1	https://arxiv.org/pdf/2405.01978v1.pdf	https://github.com/veflo/uncert_quant	true	true	true	tf
https://paperswithcode.com/paper/scalable-3d-registration-via-truncated-entry	Scalable 3D Registration via Truncated Entry-wise Absolute Residuals	2404.00915	https://arxiv.org/abs/2404.00915v2	https://arxiv.org/pdf/2404.00915v2.pdf	https://github.com/tyhuang98/tear-release	true	true	false	none
https://paperswithcode.com/paper/pixel-wise-agricultural-image-time-series	Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approach	2303.12533	https://arxiv.org/abs/2303.12533v2	https://arxiv.org/pdf/2303.12533v2.pdf	https://github.com/elliotvincent/agriitsc	true	true	true	pytorch
https://paperswithcode.com/paper/comparing-personalized-relevance-algorithms	Comparing Personalized Relevance Algorithms for Directed Graphs	2405.02261	https://arxiv.org/abs/2405.02261v1	https://arxiv.org/pdf/2405.02261v1.pdf	https://github.com/cyclerank/cyclerank-demo	true	true	false	none
https://paperswithcode.com/paper/nuqmm-quantized-matmul-for-efficient	LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models	2206.09557	https://arxiv.org/abs/2206.09557v4	https://arxiv.org/pdf/2206.09557v4.pdf	https://github.com/naver-aics/lut-gemm	true	true	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.