Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
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https://paperswithcode.com/paper/up-nerf-unconstrained-pose-prior-free-neural
UP-NeRF: Unconstrained Pose-Prior-Free Neural Radiance Fields
2311.03784
https://arxiv.org/abs/2311.03784v2
https://arxiv.org/pdf/2311.03784v2.pdf
https://github.com/mlvlab/UP-NeRF
true
false
true
pytorch
https://paperswithcode.com/paper/toward-sufficient-spatial-frequency
Toward Sufficient Spatial-Frequency Interaction for Gradient-aware Underwater Image Enhancement
2309.04089
https://arxiv.org/abs/2309.04089v2
https://arxiv.org/pdf/2309.04089v2.pdf
https://github.com/zhihefang/SFGNet
true
true
true
pytorch
https://paperswithcode.com/paper/reinforcement-learning-discovers-efficient
Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies
2409.07932
https://arxiv.org/abs/2409.07932v2
https://arxiv.org/pdf/2409.07932v2.pdf
https://github.com/flxclxc/rl-graph-search
true
false
true
pytorch
https://paperswithcode.com/paper/affective-reasoning-at-utterance-level-in
How to Enhance Causal Discrimination of Utterances: A Case on Affective Reasoning
2305.02615
https://arxiv.org/abs/2305.02615v2
https://arxiv.org/pdf/2305.02615v2.pdf
https://github.com/zodiark-ch/mater-of-our-emnlp2023-paper
true
true
false
pytorch
https://paperswithcode.com/paper/sednet-shallow-encoder-decoder-network-for
SEDNet: Shallow Encoder-Decoder Network for Brain Tumor Segmentation
2401.13403
https://arxiv.org/abs/2401.13403v3
https://arxiv.org/pdf/2401.13403v3.pdf
https://github.com/chollette/SEDNet_Shallow-Encoder-Decoder-Network-for-Brain-Tumor-Segmentation
true
false
false
tf
https://paperswithcode.com/paper/hartley-spectral-pooling-for-deep-learning
Hartley Spectral Pooling for Deep Learning
1810.04028
https://arxiv.org/abs/1810.04028v2
https://arxiv.org/pdf/1810.04028v2.pdf
https://github.com/AlbertZhangHIT/Hartley-spectral-pooling
true
false
false
pytorch
https://paperswithcode.com/paper/beyond-automated-evaluation-metrics
Improving the TENOR of Labeling: Re-evaluating Topic Models for Content Analysis
2401.16348
https://arxiv.org/abs/2401.16348v2
https://arxiv.org/pdf/2401.16348v2.pdf
https://github.com/zli12321/tenor
true
true
true
none
https://paperswithcode.com/paper/dynamic-and-scalable-data-preparation-for
Dynamic and Scalable Data Preparation for Object-Centric Process Mining
2410.00596
https://arxiv.org/abs/2410.00596v1
https://arxiv.org/pdf/2410.00596v1.pdf
https://github.com/LienBosmans/stack-t
false
false
true
none
https://paperswithcode.com/paper/rethinking-image-mixture-for-unsupervised
Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning
2003.05438
https://arxiv.org/abs/2003.05438v5
https://arxiv.org/pdf/2003.05438v5.pdf
https://github.com/hannaiiyanggit/unicon
false
false
true
pytorch
https://paperswithcode.com/paper/a-simple-framework-for-contrastive-learning
A Simple Framework for Contrastive Learning of Visual Representations
2002.05709
https://arxiv.org/abs/2002.05709v3
https://arxiv.org/pdf/2002.05709v3.pdf
https://github.com/hannaiiyanggit/unicon
false
false
true
pytorch
https://paperswithcode.com/paper/supervised-contrastive-learning
Supervised Contrastive Learning
2004.11362
https://arxiv.org/abs/2004.11362v5
https://arxiv.org/pdf/2004.11362v5.pdf
https://github.com/hannaiiyanggit/unicon
false
false
true
pytorch
https://paperswithcode.com/paper/active-vision-reinforcement-learning-under
Active Vision Reinforcement Learning under Limited Visual Observability
2306.00975
https://arxiv.org/abs/2306.00975v2
https://arxiv.org/pdf/2306.00975v2.pdf
https://github.com/elicassion/active-gym
true
true
false
pytorch
https://paperswithcode.com/paper/improving-robustness-against-common
Improving robustness against common corruptions by covariate shift adaptation
2006.16971
https://arxiv.org/abs/2006.16971v2
https://arxiv.org/pdf/2006.16971v2.pdf
https://github.com/Claydon-Wang/OFTTA
false
false
true
pytorch
https://paperswithcode.com/paper/do-we-really-need-to-access-the-source-data
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
2002.08546
https://arxiv.org/abs/2002.08546v6
https://arxiv.org/pdf/2002.08546v6.pdf
https://github.com/Claydon-Wang/OFTTA
false
false
true
pytorch
https://paperswithcode.com/paper/torchaudio-2-1-advancing-speech-recognition
TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch
2310.17864
https://arxiv.org/abs/2310.17864v1
https://arxiv.org/pdf/2310.17864v1.pdf
https://github.com/pytorch/audio
true
true
false
pytorch
https://paperswithcode.com/paper/2407-21024
An Autonomous GIS Agent Framework for Geospatial Data Retrieval
2407.21024
https://arxiv.org/abs/2407.21024v2
https://arxiv.org/pdf/2407.21024v2.pdf
https://github.com/teakinboyewa/autonomousgis_geodataretrieveragent
true
true
false
none
https://paperswithcode.com/paper/algebraic-proofs-of-path-disconnectedness
Algebraic Proofs of Path Disconnectedness using Time-Dependent Barrier Functions
2404.06985
https://arxiv.org/abs/2404.06985v1
https://arxiv.org/pdf/2404.06985v1.pdf
https://github.com/jarmill/set_connected
true
true
false
none
https://paperswithcode.com/paper/galapy-the-highly-optimised-c-python-spectral
GalaPy, the highly optimised C++/Python spectral modelling tool for galaxies - I - Library presentation and photometric fitting
2402.12427
https://arxiv.org/abs/2402.12427v1
https://arxiv.org/pdf/2402.12427v1.pdf
https://github.com/tommasoronconi/galapy
true
true
true
none
https://paperswithcode.com/paper/facial-expression-and-attributes-recognition-1
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks
2103.17107
https://arxiv.org/abs/2103.17107v3
https://arxiv.org/pdf/2103.17107v3.pdf
https://github.com/HSE-asavchenko/face-emotion-recognition
true
true
true
tf
https://paperswithcode.com/paper/provably-convergent-stochastic-fixed-point
Provably convergent stochastic fixed-point algorithm for free-support Wasserstein barycenter of continuous non-parametric measures
2505.24384
https://arxiv.org/abs/2505.24384v1
https://arxiv.org/pdf/2505.24384v1.pdf
https://github.com/chenzeyi1101/wb_algo
true
true
false
jax
https://paperswithcode.com/paper/hse-nn-team-at-the-4th-abaw-competition-multi
HSE-NN Team at the 4th ABAW Competition: Multi-task Emotion Recognition and Learning from Synthetic Images
2207.09508
https://arxiv.org/abs/2207.09508v3
https://arxiv.org/pdf/2207.09508v3.pdf
https://github.com/HSE-asavchenko/face-emotion-recognition
true
true
true
tf
https://paperswithcode.com/paper/colrio-lidar-ranging-inertial-centralized
CoLRIO: LiDAR-Ranging-Inertial Centralized State Estimation for Robotic Swarms
2402.11790
https://arxiv.org/abs/2402.11790v2
https://arxiv.org/pdf/2402.11790v2.pdf
https://github.com/pengyu-team/co-lrio
true
true
false
none
https://paperswithcode.com/paper/improving-reliable-navigation-under
Improving Reliable Navigation under Uncertainty via Predictions Informed by Non-Local Information
2307.14501
https://arxiv.org/abs/2307.14501v1
https://arxiv.org/pdf/2307.14501v1.pdf
https://github.com/RAIL-group/RAIL-group-software/tree/main/modules/lsp_gnn
true
false
false
none
https://paperswithcode.com/paper/augmenting-automation-intent-based-user
Augmenting Automation: Intent-Based User Instruction Classification with Machine Learning
2403.01242
https://arxiv.org/abs/2403.01242v1
https://arxiv.org/pdf/2403.01242v1.pdf
https://github.com/lbasyal/Intent_classification
true
false
false
none
https://paperswithcode.com/paper/recipegpt-generative-pre-training-based
RecipeGPT: Generative Pre-training Based Cooking Recipe Generation and Evaluation System
2003.02498
https://arxiv.org/abs/2003.02498v1
https://arxiv.org/pdf/2003.02498v1.pdf
https://github.com/LARC-CMU-SMU/RecipeGPT-exp
true
true
true
tf
https://paperswithcode.com/paper/finite-element-hybridization-of-port
Finite element hybridization of port-Hamiltonian systems
2302.06239
https://arxiv.org/abs/2302.06239v4
https://arxiv.org/pdf/2302.06239v4.pdf
https://github.com/a-brugnoli/ph_hybridization
true
true
true
none
https://paperswithcode.com/paper/robustness-of-graph-embedding-methods-for
Robustness of graph embedding methods for community detection
2405.00636
https://arxiv.org/abs/2405.00636v2
https://arxiv.org/pdf/2405.00636v2.pdf
https://github.com/zf-wei/Robustness-of-Graph-Embeddings-for-Community-Detection
true
false
true
none
https://paperswithcode.com/paper/deelema-missing-information-search-with-deep
DeeLeMa: Missing information search with Deep Learning for Mass estimation
2212.12836
https://arxiv.org/abs/2212.12836v3
https://arxiv.org/pdf/2212.12836v3.pdf
https://github.com/Yonsei-HEP-COSMO/DeeLeMa
true
true
true
pytorch
https://paperswithcode.com/paper/corrective-machine-unlearning
Corrective Machine Unlearning
2402.14015
https://arxiv.org/abs/2402.14015v2
https://arxiv.org/pdf/2402.14015v2.pdf
https://github.com/drimpossible/corrective-unlearning-bench
true
true
true
pytorch
https://paperswithcode.com/paper/a-goal-driven-approach-to-systems
A Goal-Driven Approach to Systems Neuroscience
2311.02704
https://arxiv.org/abs/2311.02704v1
https://arxiv.org/pdf/2311.02704v1.pdf
https://github.com/HZhongLab/melander_nayebi_2021
false
false
false
none
https://paperswithcode.com/paper/3d-vessel-reconstruction-from-sparse-view
3D Vessel Reconstruction from Sparse-View Dynamic DSA Images via Vessel Probability Guided Attenuation Learning
2405.10705
https://arxiv.org/abs/2405.10705v1
https://arxiv.org/pdf/2405.10705v1.pdf
https://github.com/Zhentao-Liu/VPAL
true
false
true
none
https://paperswithcode.com/paper/cmdag-a-chinese-metaphor-dataset-with
CMDAG: A Chinese Metaphor Dataset with Annotated Grounds as CoT for Boosting Metaphor Generation
2402.13145
https://arxiv.org/abs/2402.13145v2
https://arxiv.org/pdf/2402.13145v2.pdf
https://github.com/xingweiqu/NLPCC-2024-Shared-Task-9
false
false
true
none
https://paperswithcode.com/paper/the-media-bias-taxonomy-a-systematic
The Media Bias Taxonomy: A Systematic Literature Review on the Forms and Automated Detection of Media Bias
2312.16148
https://arxiv.org/abs/2312.16148v3
https://arxiv.org/pdf/2312.16148v3.pdf
https://github.com/media-bias-group/media-bias-taxonomy
true
true
false
none
https://paperswithcode.com/paper/a-novel-and-accurate-bilstm-configuration
A Novel and Accurate BiLSTM Configuration Controller for Modular Soft Robots with Module Number Adaptability
2401.10997
https://arxiv.org/abs/2401.10997v1
https://arxiv.org/pdf/2401.10997v1.pdf
https://github.com/zixichen007115/23zcd
true
true
false
none
https://paperswithcode.com/paper/unsupervised-video-summarization
Unsupervised Video Summarization via Iterative Training and Simplified GAN
2311.03745
https://arxiv.org/abs/2311.03745v2
https://arxiv.org/pdf/2311.03745v2.pdf
https://github.com/hanklee97121/SUM-SR-5iter
true
false
false
pytorch
https://paperswithcode.com/paper/an-explicit-version-of-chen-s-theorem
An explicit version of Chen's theorem and the linear sieve
2207.09452
https://arxiv.org/abs/2207.09452v6
https://arxiv.org/pdf/2207.09452v6.pdf
https://github.com/Valeriia57/Chen-s-theorem
true
false
false
none
https://paperswithcode.com/paper/a-pattern-to-align-them-all-integrating
A Pattern to Align Them All: Integrating Different Modalities to Define Multi-Modal Entities
2410.13803
https://arxiv.org/abs/2410.13803v1
https://arxiv.org/pdf/2410.13803v1.pdf
https://github.com/ida-fbk/multimodalpattern
true
true
true
none
https://paperswithcode.com/paper/tackling-the-abstraction-and-reasoning-corpus-1
Tackling the Abstraction and Reasoning Corpus with Vision Transformers: the Importance of 2D Representation, Positions, and Objects
2410.06405
https://arxiv.org/abs/2410.06405v1
https://arxiv.org/pdf/2410.06405v1.pdf
https://github.com/khalil-research/ViTARC
true
false
true
pytorch
https://paperswithcode.com/paper/revisiting-rcnn-on-awakening-the
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
1803.06799
http://arxiv.org/abs/1803.06799v3
http://arxiv.org/pdf/1803.06799v3.pdf
https://github.com/MindSpore-paper-code-3/code10/tree/main/faster_rcnn_ssod
false
false
false
mindspore
https://paperswithcode.com/paper/evolution-strategies-as-a-scalable
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
1703.03864
http://arxiv.org/abs/1703.03864v2
http://arxiv.org/pdf/1703.03864v2.pdf
https://github.com/cesch97/NeuroEvolution
false
false
true
none
https://paperswithcode.com/paper/improving-continuous-time-conflict-based
Improving Continuous-time Conflict Based Search
2101.09723
https://arxiv.org/abs/2101.09723v2
https://arxiv.org/pdf/2101.09723v2.pdf
https://github.com/thaynewalker/ccbs
false
false
true
none
https://paperswithcode.com/paper/varformer-adapting-var-s-generative-prior-for
Varformer: Adapting VAR's Generative Prior for Image Restoration
2412.21063
https://arxiv.org/abs/2412.21063v1
https://arxiv.org/pdf/2412.21063v1.pdf
https://github.com/siywang541/Varformer
true
false
true
pytorch
https://paperswithcode.com/paper/improved-yolov5-network-for-real-time-multi
Improved YOLOv5 network for real-time multi-scale traffic sign detection
2112.08782
https://arxiv.org/abs/2112.08782v2
https://arxiv.org/pdf/2112.08782v2.pdf
https://github.com/NWPU-Li/AF_FPN
false
false
true
pytorch
https://paperswithcode.com/paper/160600942
Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations
1606.00942
http://arxiv.org/abs/1606.00942v2
http://arxiv.org/pdf/1606.00942v2.pdf
https://github.com/EiffL/SpectralFlow
false
false
true
tf
https://paperswithcode.com/paper/backpropagation-for-implicit-spectral
Backpropagation for Implicit Spectral Densities
1806.00499
http://arxiv.org/abs/1806.00499v1
http://arxiv.org/pdf/1806.00499v1.pdf
https://github.com/EiffL/SpectralFlow
false
false
true
tf
https://paperswithcode.com/paper/mixed-integer-optimal-control-via
Mixed-Integer Optimal Control via Reinforcement Learning: A Case Study on Hybrid Electric Vehicle Energy Management
2305.01461
https://arxiv.org/abs/2305.01461v3
https://arxiv.org/pdf/2305.01461v3.pdf
https://github.com/xujinming01/td3aq
true
true
true
pytorch
https://paperswithcode.com/paper/unsupervised-learning-of-phylogenetic-trees
Unsupervised Learning of Phylogenetic Trees via Split-Weight Embedding
2312.16074
https://arxiv.org/abs/2312.16074v2
https://arxiv.org/pdf/2312.16074v2.pdf
https://github.com/solislemuslab/phyloclustering.jl
true
true
true
none
https://paperswithcode.com/paper/multi-eup-the-multilingual-european
Multi-EuP: The Multilingual European Parliament Dataset for Analysis of Bias in Information Retrieval
2311.01870
https://arxiv.org/abs/2311.01870v1
https://arxiv.org/pdf/2311.01870v1.pdf
https://github.com/jrnlp/multi-eup
true
true
false
none
https://paperswithcode.com/paper/diversified-outlier-exposure-for-out-of
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation
null
https://openreview.net/forum?id=RuxBLfiEqI
https://openreview.net/pdf?id=RuxBLfiEqI
https://github.com/zfancy/divoe
true
true
false
pytorch
https://paperswithcode.com/paper/temporal-3d-shape-modeling-for-video-based
Temporal 3D Shape Modeling for Video-Based Cloth-Changing Person Re-Identification
null
https://openaccess.thecvf.com/content/WACV2024W/RWS/html/Nguyen_Temporal_3D_Shape_Modeling_for_Video-Based_Cloth-Changing_Person_Re-Identification_WACVW_2024_paper.html
https://openaccess.thecvf.com/content/WACV2024W/RWS/papers/Nguyen_Temporal_3D_Shape_Modeling_for_Video-Based_Cloth-Changing_Person_Re-Identification_WACVW_2024_paper.pdf
https://github.com/dustin-nguyen-qil/Videobased-ClothChanging-ReID-Baseline
false
false
false
pytorch
https://paperswithcode.com/paper/band-selection-with-higher-order-multivariate
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images
1808.03513
http://arxiv.org/abs/1808.03513v1
http://arxiv.org/pdf/1808.03513v1.pdf
https://github.com/ZKSI/CumulantsFeatures.jl
false
false
true
none
https://paperswithcode.com/paper/the-use-of-the-higher-order-singular-value
The use of the Higher Order Singular Value Decomposition of the 4-cumulant's tensors in features selection and outlier detection
1804.00541
http://arxiv.org/abs/1804.00541v3
http://arxiv.org/pdf/1804.00541v3.pdf
https://github.com/ZKSI/CumulantsFeatures.jl
true
true
true
none
https://paperswithcode.com/paper/3d-shape-temporal-aggregation-for-video-based
3D Shape Temporal Aggregation for Video-Based Clothing-Change Person Re-Identication
null
https://link.springer.com/chapter/10.1007/978-3-031-26348-4_5
https://openaccess.thecvf.com/content/ACCV2022/papers/Han_3D_Shape_Temporal_Aggregation_for_Video-Based_Clothing-Change_Person_Re-identification_ACCV_2022_paper.pdf
https://github.com/dustin-nguyen-qil/Videobased-ClothChanging-ReID-Baseline
false
false
false
pytorch
https://paperswithcode.com/paper/reference-based-restoration-of-digitized
Reference-based Restoration of Digitized Analog Videotapes
2310.14926
https://arxiv.org/abs/2310.14926v2
https://arxiv.org/pdf/2310.14926v2.pdf
https://github.com/miccunifi/analog-video-restoration
false
false
true
pytorch
https://paperswithcode.com/paper/be-careful-when-evaluating-explanations
Be Careful When Evaluating Explanations Regarding Ground Truth
2311.04813
https://arxiv.org/abs/2311.04813v1
https://arxiv.org/pdf/2311.04813v1.pdf
https://github.com/mi2datalab/be-careful-evaluating-explanations
true
true
false
pytorch
https://paperswithcode.com/paper/uni-moe-scaling-unified-multimodal-llms-with
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
2405.11273
https://arxiv.org/abs/2405.11273v1
https://arxiv.org/pdf/2405.11273v1.pdf
https://github.com/hitsz-tmg/umoe-scaling-unified-multimodal-llms
true
true
true
pytorch
https://paperswithcode.com/paper/multi-order-graph-clustering-with-adaptive
Multi-order Graph Clustering with Adaptive Node-level Weight Learning
2405.12183
https://arxiv.org/abs/2405.12183v1
https://arxiv.org/pdf/2405.12183v1.pdf
https://github.com/scutft-ml/mogc
true
true
true
none
https://paperswithcode.com/paper/a-comparative-study-of-deep-reinforcement-1
A Comparative Study of Deep Reinforcement Learning Models: DQN vs PPO vs A2C
2407.14151
https://arxiv.org/abs/2407.14151v1
https://arxiv.org/pdf/2407.14151v1.pdf
https://github.com/neilus03/drl_comparative_study
true
true
false
pytorch
https://paperswithcode.com/paper/iclr-2021-challenge-for-computational
ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results
2108.09810
https://arxiv.org/abs/2108.09810v2
https://arxiv.org/pdf/2108.09810v2.pdf
https://github.com/oxcsml/geomstats
false
false
true
jax
https://paperswithcode.com/paper/an-iterative-conditional-dispatch-algorithm
An iterative sample scenario approach for the dynamic dispatch waves problem
2308.14476
https://arxiv.org/abs/2308.14476v3
https://arxiv.org/pdf/2308.14476v3.pdf
https://github.com/leonlan/dynamic-dispatch-waves
true
true
true
none
https://paperswithcode.com/paper/grounding-dino-marrying-dino-with-grounded
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
2303.05499
https://arxiv.org/abs/2303.05499v5
https://arxiv.org/pdf/2303.05499v5.pdf
https://github.com/camenduru/grounded-segment-anything-colab
false
false
true
none
https://paperswithcode.com/paper/ttt-a-temporal-refinement-heuristic-for
TTT: A Temporal Refinement Heuristic for Tenuously Tractable Discrete Time Reachability Problems
2407.14394
https://arxiv.org/abs/2407.14394v2
https://arxiv.org/pdf/2407.14394v2.pdf
https://github.com/sisl/OVERTVerify.jl
true
false
false
none
https://paperswithcode.com/paper/deep-learning-for-portfolio-optimisation
Deep Learning for Portfolio Optimization
2005.13665
https://arxiv.org/abs/2005.13665v3
https://arxiv.org/pdf/2005.13665v3.pdf
https://github.com/thinklab-sjtu/linsatnet
false
false
true
pytorch
https://paperswithcode.com/paper/jkonet-proximal-optimal-transport-modeling-of
Proximal Optimal Transport Modeling of Population Dynamics
2106.06345
https://arxiv.org/abs/2106.06345v4
https://arxiv.org/pdf/2106.06345v4.pdf
https://github.com/gjhuizing/wsingular
false
false
true
pytorch
https://paperswithcode.com/paper/joint-or-disjoint-mixing-training-regimes-for
Joint or Disjoint: Mixing Training Regimes for Early-Exit Models
2407.14320
https://arxiv.org/abs/2407.14320v1
https://arxiv.org/pdf/2407.14320v1.pdf
https://github.com/kamadforge/early-exit-benchmark
true
false
false
pytorch
https://paperswithcode.com/paper/renderme-360-a-large-digital-asset-library-1
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
2305.13353
https://arxiv.org/abs/2305.13353v1
https://arxiv.org/pdf/2305.13353v1.pdf
https://github.com/renderme-360/renderme-360
true
true
true
pytorch
https://paperswithcode.com/paper/moleculargpt-open-large-language-model-llm
MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction
2406.12950
https://arxiv.org/abs/2406.12950v2
https://arxiv.org/pdf/2406.12950v2.pdf
https://github.com/nyushcs/moleculargpt
true
true
true
pytorch
https://paperswithcode.com/paper/wasserstein-k-centres-clustering-for
Wasserstein $k$-Centers Clustering for Distributional Data
2407.08228
https://arxiv.org/abs/2407.08228v4
https://arxiv.org/pdf/2407.08228v4.pdf
https://github.com/RyoOkano21/kCentresDIstributionalClustering
true
false
false
none
https://paperswithcode.com/paper/can-llms-speak-for-diverse-people-tuning-llms
Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements
2402.10614
https://arxiv.org/abs/2402.10614v2
https://arxiv.org/pdf/2402.10614v2.pdf
https://github.com/tianyi-lab/debatune
true
true
true
none
https://paperswithcode.com/paper/diffusion-self-guidance-for-controllable-1
Diffusion Self-Guidance for Controllable Image Generation
2306.00986
https://arxiv.org/abs/2306.00986v3
https://arxiv.org/pdf/2306.00986v3.pdf
https://github.com/Sainzerjj/Free-Guidance-Diffusion
false
false
true
pytorch
https://paperswithcode.com/paper/pareto-actor-critic-for-equilibrium-selection
Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning
2209.14344
https://arxiv.org/abs/2209.14344v3
https://arxiv.org/pdf/2209.14344v3.pdf
https://github.com/uoe-agents/epymarl
true
true
true
pytorch
https://paperswithcode.com/paper/progressive-distillation-for-fast-sampling-of-1
Progressive Distillation for Fast Sampling of Diffusion Models
2202.00512
https://arxiv.org/abs/2202.00512v2
https://arxiv.org/pdf/2202.00512v2.pdf
https://github.com/deepxuan/dn-dp
false
false
true
pytorch
https://paperswithcode.com/paper/improving-diffusion-model-efficiency-through
Improving Diffusion Model Efficiency Through Patching
2207.04316
https://arxiv.org/abs/2207.04316v1
https://arxiv.org/pdf/2207.04316v1.pdf
https://github.com/deepxuan/dn-dp
false
false
true
pytorch
https://paperswithcode.com/paper/differentiable-all-pole-filters-for-time
Differentiable All-pole Filters for Time-varying Audio Systems
2404.07970
https://arxiv.org/abs/2404.07970v4
https://arxiv.org/pdf/2404.07970v4.pdf
https://github.com/DiffAPF/web
true
false
false
none
https://paperswithcode.com/paper/removing-biases-from-molecular
Removing Biases from Molecular Representations via Information Maximization
2312.00718
https://arxiv.org/abs/2312.00718v1
https://arxiv.org/pdf/2312.00718v1.pdf
https://github.com/uhlerlab/infocore
true
true
true
pytorch
https://paperswithcode.com/paper/famo-fast-adaptive-multitask-optimization-1
FAMO: Fast Adaptive Multitask Optimization
2306.03792
https://arxiv.org/abs/2306.03792v3
https://arxiv.org/pdf/2306.03792v3.pdf
https://github.com/cranial-xix/famo
true
true
true
pytorch
https://paperswithcode.com/paper/improving-the-astrometric-solution-of-the
Improving the astrometric solution of the Hyper Suprime-Cam with anisotropic Gaussian processes
2103.09881
https://arxiv.org/abs/2103.09881v1
https://arxiv.org/pdf/2103.09881v1.pdf
https://github.com/PFLeget/treegp
true
true
true
none
https://paperswithcode.com/paper/averitec-a-dataset-for-real-world-claim-1
AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web
2305.13117
https://arxiv.org/abs/2305.13117v3
https://arxiv.org/pdf/2305.13117v3.pdf
https://github.com/ssu-humane/hero
false
false
false
pytorch
https://paperswithcode.com/paper/the-positioning-of-stress-fibers-in
The positioning of stress fibers in contractile cells minimizes internal mechanical stress
2407.07797
https://arxiv.org/abs/2407.07797v2
https://arxiv.org/pdf/2407.07797v2.pdf
https://github.com/usschwarz/dune-structures
true
false
false
none
https://paperswithcode.com/paper/caseformer-pre-training-for-legal-case
Caseformer: Pre-training for Legal Case Retrieval Based on Inter-Case Distinctions
2311.00333
https://arxiv.org/abs/2311.00333v2
https://arxiv.org/pdf/2311.00333v2.pdf
https://github.com/oneal2000/caseformer
true
true
false
pytorch
https://paperswithcode.com/paper/automated-detection-of-label-errors-in
Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification
2207.06104
https://arxiv.org/abs/2207.06104v2
https://arxiv.org/pdf/2207.06104v2.pdf
https://github.com/mrcoee/automatic-label-error-detection
true
true
true
none
https://paperswithcode.com/paper/occamy-a-preemptive-buffer-management-for-on
Occamy: A Preemptive Buffer Management for On-chip Shared-memory Switches
2501.13570
https://arxiv.org/abs/2501.13570v1
https://arxiv.org/pdf/2501.13570v1.pdf
https://github.com/ants-xjtu/occamy
true
true
false
none
https://paperswithcode.com/paper/does-it-chug-towards-a-data-driven
Does it Chug? Towards a Data-Driven Understanding of Guitar Tone Description
2412.11769
https://arxiv.org/abs/2412.11769v1
https://arxiv.org/pdf/2412.11769v1.pdf
https://github.com/pratikstar/doesitchug
true
true
false
none
https://paperswithcode.com/paper/global-transformer-overheating-from
Global transformer overheating from geomagnetic storms
2403.18070
https://arxiv.org/abs/2403.18070v2
https://arxiv.org/pdf/2403.18070v2.pdf
https://github.com/allfed/geomagneticmodel
true
true
false
tf
https://paperswithcode.com/paper/llara-aligning-large-language-models-with
LLaRA: Large Language-Recommendation Assistant
2312.02445
https://arxiv.org/abs/2312.02445v4
https://arxiv.org/pdf/2312.02445v4.pdf
https://github.com/ljy0ustc/llara
true
true
false
pytorch
https://paperswithcode.com/paper/embedding-neighborhoods-simultaneously-t-sne
ENS-t-SNE: Embedding Neighborhoods Simultaneously t-SNE
2205.11720
https://arxiv.org/abs/2205.11720v3
https://arxiv.org/pdf/2205.11720v3.pdf
https://github.com/enggiqbal/mpse-tsne
true
true
false
none
https://paperswithcode.com/paper/muse-text-to-image-generation-via-masked
Muse: Text-To-Image Generation via Masked Generative Transformers
2301.00704
https://arxiv.org/abs/2301.00704v1
https://arxiv.org/pdf/2301.00704v1.pdf
https://github.com/baaivision/muse-pytorch
false
false
true
pytorch
https://paperswithcode.com/paper/leveraging-vision-centric-multi-modal-1
Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection
2310.15670
https://arxiv.org/abs/2310.15670v1
https://arxiv.org/pdf/2310.15670v1.pdf
https://github.com/opendrivelab/birds-eye-view-perception
true
true
true
pytorch
https://paperswithcode.com/paper/shape-iou-more-accurate-metric-considering
Shape-IoU: More Accurate Metric considering Bounding Box Shape and Scale
2312.17663
https://arxiv.org/abs/2312.17663v2
https://arxiv.org/pdf/2312.17663v2.pdf
https://github.com/malagoutou/shape-iou
true
true
true
none
https://paperswithcode.com/paper/svft-parameter-efficient-fine-tuning-with
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
2405.19597
https://arxiv.org/abs/2405.19597v1
https://arxiv.org/pdf/2405.19597v1.pdf
https://github.com/vijaylingam95/svft
true
true
false
pytorch
https://paperswithcode.com/paper/attention-beats-linear-for-fast-implicit
Attention Beats Linear for Fast Implicit Neural Representation Generation
2407.15355
https://arxiv.org/abs/2407.15355v1
https://arxiv.org/pdf/2407.15355v1.pdf
https://github.com/roninton/anr
true
true
true
pytorch
https://paperswithcode.com/paper/growing-urban-bicycle-networks
Growing Urban Bicycle Networks
2107.02185
https://arxiv.org/abs/2107.02185v3
https://arxiv.org/pdf/2107.02185v3.pdf
https://github.com/mszell/bikenwgrowth
true
true
true
none
https://paperswithcode.com/paper/distance-guided-generative-adversarial
Distance Guided Generative Adversarial Network for Explainable Binary Classifications
2312.17538
https://arxiv.org/abs/2312.17538v1
https://arxiv.org/pdf/2312.17538v1.pdf
https://github.com/yxiangxiong/disgan
true
true
false
pytorch
https://paperswithcode.com/paper/towards-efficient-and-effective-deep
Towards Efficient and Effective Deep Clustering with Dynamic Grouping and Prototype Aggregation
2401.13581
https://arxiv.org/abs/2401.13581v2
https://arxiv.org/pdf/2401.13581v2.pdf
https://github.com/regan-zhang/digpro
true
true
true
pytorch
https://paperswithcode.com/paper/mint-evaluating-llms-in-multi-turn
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
2309.10691
https://arxiv.org/abs/2309.10691v3
https://arxiv.org/pdf/2309.10691v3.pdf
https://github.com/xingyaoww/mint-bench
false
false
true
none
https://paperswithcode.com/paper/iroyinspeech-a-multi-purpose-yoruba-speech
ÌròyìnSpeech: A multi-purpose Yorùbá Speech Corpus
2307.16071
https://arxiv.org/abs/2307.16071v2
https://arxiv.org/pdf/2307.16071v2.pdf
https://github.com/niger-volta-lti/yoruba-voice
true
true
true
none
https://paperswithcode.com/paper/gifsplanation-via-latent-shift-a-simple
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays
2102.09475
https://arxiv.org/abs/2102.09475v2
https://arxiv.org/pdf/2102.09475v2.pdf
https://github.com/ieee8023/latentshift
false
false
true
pytorch
https://paperswithcode.com/paper/codex-a-cluster-based-method-for-explainable
CODEX: A Cluster-Based Method for Explainable Reinforcement Learning
2312.04216
https://arxiv.org/abs/2312.04216v1
https://arxiv.org/pdf/2312.04216v1.pdf
https://github.com/ainfosec/codex
true
true
false
none
https://paperswithcode.com/paper/domain-private-transformers
Domain Private Transformers for Multi-Domain Dialog Systems
2305.14208
https://arxiv.org/abs/2305.14208v2
https://arxiv.org/pdf/2305.14208v2.pdf
https://github.com/asappresearch/domain-private-transformers
true
true
true
pytorch
https://paperswithcode.com/paper/weakly-supervised-video-individual
Weakly Supervised Video Individual CountingWeakly Supervised Video Individual Counting
2312.05923
https://arxiv.org/abs/2312.05923v1
https://arxiv.org/pdf/2312.05923v1.pdf
https://github.com/streamer-ap/cgnet
true
true
false
pytorch