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

Dataset card Data Studio Files
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https://paperswithcode.com/paper/dual-invariance-self-training-for-reliable
Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition
2501.17628
https://arxiv.org/abs/2501.17628v1
https://arxiv.org/pdf/2501.17628v1.pdf
https://github.com/sahar-nasiri/dist
true
true
false
pytorch
https://paperswithcode.com/paper/waste-not-want-not-why-rarefying-microbiome
Waste Not, Want Not: Why Rarefying Microbiome Data is Inadmissible
1310.0424
https://arxiv.org/abs/1310.0424v2
https://arxiv.org/pdf/1310.0424v2.pdf
https://github.com/joey711/phyloseq
false
false
true
none
https://paperswithcode.com/paper/self-adaptive-training-beyond-empirical-risk
Self-Adaptive Training: beyond Empirical Risk Minimization
2002.10319
https://arxiv.org/abs/2002.10319v2
https://arxiv.org/pdf/2002.10319v2.pdf
https://github.com/BorealisAI/towards-better-sel-cls
false
false
true
pytorch
https://paperswithcode.com/paper/stochastic-gradient-descent-with
Stochastic Gradient Descent with Preconditioned Polyak Step-size
2310.02093
https://arxiv.org/abs/2310.02093v1
https://arxiv.org/pdf/2310.02093v1.pdf
https://github.com/fxrshed/scaledsps
true
true
false
pytorch
https://paperswithcode.com/paper/turingbench-a-benchmark-environment-for
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation
2109.13296
https://arxiv.org/abs/2109.13296v1
https://arxiv.org/pdf/2109.13296v1.pdf
https://github.com/amritabh/conda-gen-text-detection
false
false
true
pytorch
https://paperswithcode.com/paper/quantum-accelerated-causal-tomography-circuit
A scalable quantum gate-based implementation for causal hypothesis testing
2209.02016
https://arxiv.org/abs/2209.02016v4
https://arxiv.org/pdf/2209.02016v4.pdf
https://github.com/advanced-research-centre/qacht
true
true
false
none
https://paperswithcode.com/paper/integrating-earth-observation-data-into
Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities
2301.12985
https://arxiv.org/abs/2301.12985v1
https://arxiv.org/pdf/2301.12985v1.pdf
https://github.com/AIandGlobalDevelopmentLab/causalimages-software
false
false
true
tf
https://paperswithcode.com/paper/all-languages-matter-on-the-multilingual
All Languages Matter: On the Multilingual Safety of Large Language Models
2310.00905
https://arxiv.org/abs/2310.00905v2
https://arxiv.org/pdf/2310.00905v2.pdf
https://github.com/jarviswang94/multilingual_safety_benchmark
true
true
true
none
https://paperswithcode.com/paper/understanding-in-context-learning-from
Understanding In-Context Learning from Repetitions
2310.00297
https://arxiv.org/abs/2310.00297v3
https://arxiv.org/pdf/2310.00297v3.pdf
https://github.com/elliottyan/understand-icl-from-repetition
true
true
true
pytorch
https://paperswithcode.com/paper/an-image-is-worth-16x16-words-transformers-1
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
2010.11929
https://arxiv.org/abs/2010.11929v2
https://arxiv.org/pdf/2010.11929v2.pdf
https://github.com/uygarkurt/ViT-PyTorch
false
false
true
pytorch
https://paperswithcode.com/paper/fedaiot-a-federated-learning-benchmark-for
FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things
2310.00109
https://arxiv.org/abs/2310.00109v3
https://arxiv.org/pdf/2310.00109v3.pdf
https://github.com/aiot-mlsys-lab/fedaiot
true
true
true
pytorch
https://paperswithcode.com/paper/hydra-multi-head-low-rank-adaptation-for
Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuning
2309.06922
https://arxiv.org/abs/2309.06922v1
https://arxiv.org/pdf/2309.06922v1.pdf
https://github.com/extremebird/hydra
true
true
true
jax
https://paperswithcode.com/paper/mini-gpts-efficient-large-language-models
Mini-GPTs: Efficient Large Language Models through Contextual Pruning
2312.12682
https://arxiv.org/abs/2312.12682v1
https://arxiv.org/pdf/2312.12682v1.pdf
https://github.com/tval2/contextual-pruning
false
true
false
pytorch
https://paperswithcode.com/paper/colora-continuous-low-rank-adaptation-for
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
2402.14646
https://arxiv.org/abs/2402.14646v2
https://arxiv.org/pdf/2402.14646v2.pdf
https://github.com/julesberman/colora
true
true
false
jax
https://paperswithcode.com/paper/sublinear-time-opinion-estimation-in-the
Sublinear-Time Opinion Estimation in the Friedkin--Johnsen Model
2404.16464
https://arxiv.org/abs/2404.16464v1
https://arxiv.org/pdf/2404.16464v1.pdf
https://github.com/stefanresearch/sublinear-time-opinions
true
true
true
none
https://paperswithcode.com/paper/determination-of-optimal-chain-coupling-made
Determination of Optimal Chain Coupling made by Embedding in D-Wave Quantum Annealer
2406.03364
https://arxiv.org/abs/2406.03364v1
https://arxiv.org/pdf/2406.03364v1.pdf
https://github.com/hunpyolee/optimizechainstrength
true
true
false
none
https://paperswithcode.com/paper/population-group-2-0-bringing-the-umls
Population Group 2.0: Bringing the UMLS Semantic Network up to Speed
null
https://pubmed.ncbi.nlm.nih.gov/40380730/
https://ebooks.iospress.nl/doi/10.3233/SHTI250627
https://github.com/narenkhatwani/population-group-2.0
false
false
false
none
https://paperswithcode.com/paper/going-incognito-in-the-metaverse
Going Incognito in the Metaverse: Achieving Theoretically Optimal Privacy-Usability Tradeoffs in VR
2208.05604
https://arxiv.org/abs/2208.05604v5
https://arxiv.org/pdf/2208.05604v5.pdf
https://github.com/metaguard/metaguard
true
true
true
none
https://paperswithcode.com/paper/self-normalizing-neural-networks
Self-Normalizing Neural Networks
1706.02515
http://arxiv.org/abs/1706.02515v5
http://arxiv.org/pdf/1706.02515v5.pdf
https://github.com/2023-MindSpore-4/Code7/tree/main/snn_mlp
false
false
false
mindspore
https://paperswithcode.com/paper/is-automated-topic-model-evaluation-broken
Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence
2107.02173
https://arxiv.org/abs/2107.02173v3
https://arxiv.org/pdf/2107.02173v3.pdf
https://github.com/dominiksinsaarland/evaluating-topic-model-output
false
false
true
none
https://paperswithcode.com/paper/re-visiting-automated-topic-model-evaluation
Revisiting Automated Topic Model Evaluation with Large Language Models
2305.12152
https://arxiv.org/abs/2305.12152v2
https://arxiv.org/pdf/2305.12152v2.pdf
https://github.com/dominiksinsaarland/evaluating-topic-model-output
true
true
true
none
https://paperswithcode.com/paper/randomizing-hypergraphs-preserving-degree
Randomizing hypergraphs preserving degree correlation and local clustering
2106.12162
https://arxiv.org/abs/2106.12162v2
https://arxiv.org/pdf/2106.12162v2.pdf
https://github.com/kazuibasou/hyper-dk-series
true
true
true
none
https://paperswithcode.com/paper/identifying-important-group-of-pixels-using
Identifying Important Group of Pixels using Interactions
2401.03785
https://arxiv.org/abs/2401.03785v3
https://arxiv.org/pdf/2401.03785v3.pdf
https://github.com/kosukesumiyasu/moxi
true
true
true
pytorch
https://paperswithcode.com/paper/automated-security-response-through-online
Automated Security Response through Online Learning with Adaptive Conjectures
2402.12499
https://arxiv.org/abs/2402.12499v4
https://arxiv.org/pdf/2402.12499v4.pdf
https://github.com/limmen/csle
true
true
false
none
https://paperswithcode.com/paper/on-the-minimal-modules-for-exceptional-lie
On the minimal modules for exceptional Lie algebras: Jordan blocks and stabilisers
1508.02918
https://arxiv.org/abs/1508.02918v6
https://arxiv.org/pdf/1508.02918v6.pdf
https://github.com/davistem/nilpotent_orbits_gap
true
true
false
none
https://paperswithcode.com/paper/explainable-multimodal-emotion-reasoning
Explainable Multimodal Emotion Recognition
2306.15401
https://arxiv.org/abs/2306.15401v6
https://arxiv.org/pdf/2306.15401v6.pdf
https://github.com/zeroqiaoba/affectgpt
true
true
true
pytorch
https://paperswithcode.com/paper/seamlessm4t-massively-multilingual-multimodal
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
2308.11596
https://arxiv.org/abs/2308.11596v3
https://arxiv.org/pdf/2308.11596v3.pdf
https://github.com/facebookresearch/seamless_communication
true
true
false
pytorch
https://paperswithcode.com/paper/deriving-analytical-solutions-using-symbolic-1
Deriving Analytical Solutions Using Symbolic Matrix Structural Analysis: Part 2 -- Plane Trusses
2411.16573
https://arxiv.org/abs/2411.16573v1
https://arxiv.org/pdf/2411.16573v1.pdf
https://github.com/vplevris/symbolicmsa-2dtrusses
true
true
false
none
https://paperswithcode.com/paper/simple-pose-rethinking-and-improving-a-bottom
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
1911.10529
https://arxiv.org/abs/1911.10529v1
https://arxiv.org/pdf/1911.10529v1.pdf
https://github.com/2023-MindSpore-4/Code11/tree/main/simple_pose
false
false
false
mindspore
https://paperswithcode.com/paper/heuristic-learning-with-graph-neural-networks
Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction
2406.07979
https://arxiv.org/abs/2406.07979v2
https://arxiv.org/pdf/2406.07979v2.pdf
https://github.com/LARS-research/HL-GNN
true
false
true
pytorch
https://paperswithcode.com/paper/taming-diffusion-probabilistic-models-for
Taming Diffusion Probabilistic Models for Character Control
2404.15121
https://arxiv.org/abs/2404.15121v1
https://arxiv.org/pdf/2404.15121v1.pdf
https://github.com/AIGAnimation/CAMDM
false
false
true
pytorch
https://paperswithcode.com/paper/on-the-differentiability-of-the-primal-dual
On the Differentiability of the Primal-Dual Interior-Point Method
2406.11749
https://arxiv.org/abs/2406.11749v2
https://arxiv.org/pdf/2406.11749v2.pdf
https://github.com/kevin-tracy/qpax
true
true
true
jax
https://paperswithcode.com/paper/triggerless-backdoor-attack-for-nlp-tasks
Triggerless Backdoor Attack for NLP Tasks with Clean Labels
2111.07970
https://arxiv.org/abs/2111.07970v2
https://arxiv.org/pdf/2111.07970v2.pdf
https://github.com/2023-MindSpore-4/Code12/tree/main/ganleilei/CleanLabelBackdoorAttackMindspore-master
false
false
false
mindspore
https://paperswithcode.com/paper/context-based-interpretable-spatio-temporal
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
2402.19237
https://arxiv.org/abs/2402.19237v1
https://arxiv.org/pdf/2402.19237v1.pdf
https://github.com/qualityminds/cistgcn
true
true
true
pytorch
https://paperswithcode.com/paper/electron-energization-in-reconnection
Electron Energization in Reconnection: Eulerian versus Lagrangian Perspectives
2310.17480
https://arxiv.org/abs/2310.17480v2
https://arxiv.org/pdf/2310.17480v2.pdf
https://github.com/ammarhakim/gkyl-paper-inp
true
true
false
none
https://paperswithcode.com/paper/a-survey-on-autonomous-driving-datasets-data
A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook
2401.01454
https://arxiv.org/abs/2401.01454v2
https://arxiv.org/pdf/2401.01454v2.pdf
https://github.com/mingyuliu1/autonomous_driving_datasets
true
true
true
none
https://paperswithcode.com/paper/logformer-a-pre-train-and-tuning-pipeline-for
LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection
2401.04749
https://arxiv.org/abs/2401.04749v1
https://arxiv.org/pdf/2401.04749v1.pdf
https://github.com/hc-guo/logformer
true
true
false
pytorch
https://paperswithcode.com/paper/violation-of-expectation-via-metacognitive
Violation of Expectation via Metacognitive Prompting Reduces Theory of Mind Prediction Error in Large Language Models
2310.06983
https://arxiv.org/abs/2310.06983v1
https://arxiv.org/pdf/2310.06983v1.pdf
https://github.com/plastic-labs/voe-paper-eval
true
true
false
none
https://paperswithcode.com/paper/evolution-of-fullerenes-in-circumstellar
Evolution of Fullerenes in Circumstellar Envelopes by Carbon Condensation: Insights from Reactive Molecular Dynamics Simulations
2310.17095
https://arxiv.org/abs/2310.17095v1
https://arxiv.org/pdf/2310.17095v1.pdf
https://github.com/mengzss/fullerene_evolution
true
true
false
none
https://paperswithcode.com/paper/flag-hilbert-poincare-series-of-hyperplane
Flag Hilbert-Poincaré series of hyperplane arrangements and their Igusa zeta functions
2103.03640
https://arxiv.org/abs/2103.03640v2
https://arxiv.org/pdf/2103.03640v2.pdf
https://github.com/joshmaglione/hypigu
true
true
true
none
https://paperswithcode.com/paper/paraphrase-types-for-generation-and-detection
Paraphrase Types for Generation and Detection
2310.14863
https://arxiv.org/abs/2310.14863v3
https://arxiv.org/pdf/2310.14863v3.pdf
https://github.com/jpwahle/emnlp23-paraphrase-types
true
true
true
pytorch
https://paperswithcode.com/paper/on-the-representational-capacity-of-recurrent
On the Representational Capacity of Recurrent Neural Language Models
2310.12942
https://arxiv.org/abs/2310.12942v5
https://arxiv.org/pdf/2310.12942v5.pdf
https://github.com/rycolab/rnn-turing-completeness
true
true
true
none
https://paperswithcode.com/paper/pruning-for-protection-increasing-jailbreak
Pruning for Protection: Increasing Jailbreak Resistance in Aligned LLMs Without Fine-Tuning
2401.10862
https://arxiv.org/abs/2401.10862v3
https://arxiv.org/pdf/2401.10862v3.pdf
https://github.com/crystaleye42/eval-safety
true
true
true
pytorch
https://paperswithcode.com/paper/efficient-graduated-non-convexity-for-pose
Efficient Graduated Non-Convexity for Pose Graph Optimization
2310.06765
https://arxiv.org/abs/2310.06765v1
https://arxiv.org/pdf/2310.06765v1.pdf
https://github.com/SNU-DLLAB/EGNC-PGO
true
true
true
none
https://paperswithcode.com/paper/chatvis-automating-scientific-visualization
ChatVis: Automating Scientific Visualization with a Large Language Model
2410.11863
https://arxiv.org/abs/2410.11863v1
https://arxiv.org/pdf/2410.11863v1.pdf
https://github.com/tanwimallick/chatvis
true
true
false
none
https://paperswithcode.com/paper/variable-selection-for-partially-linear
Robust variable selection for partially linear additive models
2401.10869
https://arxiv.org/abs/2401.10869v2
https://arxiv.org/pdf/2401.10869v2.pdf
https://github.com/alemermartinez/rplam-vs
true
true
false
none
https://paperswithcode.com/paper/multi-task-faces-mtf-data-set-a-legally-and
Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification Tasks
2311.11882
https://arxiv.org/abs/2311.11882v1
https://arxiv.org/pdf/2311.11882v1.pdf
https://github.com/ramihaf/mtf_data_set
true
true
false
pytorch
https://paperswithcode.com/paper/unearthing-a-billion-telegram-posts-about-the
Unearthing a Billion Telegram Posts about the 2024 U.S. Presidential Election: Development of a Public Dataset
2410.23638
https://arxiv.org/abs/2410.23638v1
https://arxiv.org/pdf/2410.23638v1.pdf
https://github.com/leonardo-blas/usc-tg-24-us-election
true
true
true
none
https://paperswithcode.com/paper/resnet50-on-cifar-100-without-transfer
ResNet50_on_Cifar_100_Without_Transfer_Learning
null
https://github.com/batuhan3526/ResNet50_on_Cifar_100_Without_Transfer_Learning/blob/master/abstract.txt
https://github.com/batuhan3526/ResNet50_on_Cifar_100_Without_Transfer_Learning/blob/master/abstract.txt
https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet50
false
false
false
mindspore
https://paperswithcode.com/paper/chatgpt-as-data-augmentation-for
ChatGPT as Data Augmentation for Compositional Generalization: A Case Study in Open Intent Detection
2308.13517
https://arxiv.org/abs/2308.13517v1
https://arxiv.org/pdf/2308.13517v1.pdf
https://github.com/fangyihao/gptaug
true
false
false
pytorch
https://paperswithcode.com/paper/a-structured-l-bfgs-method-and-its
A structured L-BFGS method and its application to inverse problems
2310.07296
https://arxiv.org/abs/2310.07296v7
https://arxiv.org/pdf/2310.07296v7.pdf
https://github.com/hariagr/slbfgs
true
true
false
none
https://paperswithcode.com/paper/neur2sp-neural-two-stage-stochastic
Neur2SP: Neural Two-Stage Stochastic Programming
2205.12006
https://arxiv.org/abs/2205.12006v2
https://arxiv.org/pdf/2205.12006v2.pdf
https://github.com/khalil-research/neur2ro
false
false
true
pytorch
https://paperswithcode.com/paper/are-eeg-to-text-models-working
Are EEG-to-Text Models Working?
2405.06459
https://arxiv.org/abs/2405.06459v4
https://arxiv.org/pdf/2405.06459v4.pdf
https://github.com/mikewangwzhl/eeg-to-text
true
true
true
pytorch
https://paperswithcode.com/paper/contrastive-modules-with-temporal-attention
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
2311.01075
https://arxiv.org/abs/2311.01075v1
https://arxiv.org/pdf/2311.01075v1.pdf
https://github.com/niiceMing/CMTA
true
false
false
pytorch
https://paperswithcode.com/paper/mutox-universal-multilingual-audio-based
MuTox: Universal MUltilingual Audio-based TOXicity Dataset and Zero-shot Detector
2401.05060
https://arxiv.org/abs/2401.05060v2
https://arxiv.org/pdf/2401.05060v2.pdf
https://github.com/facebookresearch/seamless_communication
true
true
false
pytorch
https://paperswithcode.com/paper/adaptive-optimizers-with-sparse-group-lasso-1
Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction
2107.14432
https://arxiv.org/abs/2107.14432v6
https://arxiv.org/pdf/2107.14432v6.pdf
https://github.com/intelligent-machine-learning/tfplus
true
true
true
tf
https://paperswithcode.com/paper/wasm-icare-a-portable-and-privacy-preserving
Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models
2310.09252
https://arxiv.org/abs/2310.09252v1
https://arxiv.org/pdf/2310.09252v1.pdf
https://github.com/jeyabbalas/wasm-icare
true
true
false
none
https://paperswithcode.com/paper/time-varying-optimization-of-lti-systems-via
Time-Varying Optimization of LTI Systems via Projected Primal-Dual Gradient Flows
2101.01799
https://arxiv.org/abs/2101.01799v3
https://arxiv.org/pdf/2101.01799v3.pdf
https://github.com/gianlucaBi/onlinePrimalDual_rampMetering
true
true
false
none
https://paperswithcode.com/paper/efficient-psf-modeling-with-shopt-jl-a-psf
Efficient PSF Modeling with ShOpt.jl: A PSF Benchmarking Study with JWST NIRCam Imaging
2401.11625
https://arxiv.org/abs/2401.11625v3
https://arxiv.org/pdf/2401.11625v3.pdf
https://github.com/edwardberman/shopt
true
true
true
jax
https://paperswithcode.com/paper/from-clip-to-dino-visual-encoders-shout-in
From CLIP to DINO: Visual Encoders Shout in Multi-modal Large Language Models
2310.08825
https://arxiv.org/abs/2310.08825v3
https://arxiv.org/pdf/2310.08825v3.pdf
https://github.com/yuchenliu98/comm
true
true
true
pytorch
https://paperswithcode.com/paper/metra-scalable-unsupervised-rl-with-metric
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction
2310.08887
https://arxiv.org/abs/2310.08887v2
https://arxiv.org/pdf/2310.08887v2.pdf
https://github.com/seohongpark/metra
true
true
false
tf
https://paperswithcode.com/paper/self-storm-deep-unrolled-self-supervised
Self-STORM: Deep Unrolled Self-Supervised Learning for Super-Resolution Microscopy
2403.16974
https://arxiv.org/abs/2403.16974v1
https://arxiv.org/pdf/2403.16974v1.pdf
https://github.com/yairbs/Self-STORM
true
false
true
pytorch
https://paperswithcode.com/paper/comparative-analysis-of-llama-and-chatgpt
Can Large Language Models Understand Molecules?
2402.00024
https://arxiv.org/abs/2402.00024v3
https://arxiv.org/pdf/2402.00024v3.pdf
https://github.com/sshaghayeghs/llama-vs-gpt
true
true
false
none
https://paperswithcode.com/paper/cosmos-web-the-over-abundance-and-physical
COSMOS-Web: The over-abundance and physical nature of "little red dots"--Implications for early galaxy and SMBH assembly
2406.10341
https://arxiv.org/abs/2406.10341v1
https://arxiv.org/pdf/2406.10341v1.pdf
https://github.com/hollisakins/akins24_cw
true
true
true
none
https://paperswithcode.com/paper/leveraging-adversarial-detection-to-enable
BreakHammer: Enhancing RowHammer Mitigations by Carefully Throttling Suspect Threads
2404.13477
https://arxiv.org/abs/2404.13477v2
https://arxiv.org/pdf/2404.13477v2.pdf
https://github.com/cmu-safari/breakhammer
true
true
true
none
https://paperswithcode.com/paper/crossmoco-multi-modal-momentum-contrastive
CrossMoCo: Multi-modal Momentum Contrastive Learning for Point Cloud
null
https://ieeexplore.ieee.org/abstract/document/10229841
https://ieeexplore.ieee.org/abstract/document/10229841
https://github.com/snehaputul/CrossMoCo
false
true
false
pytorch
https://paperswithcode.com/paper/apollo-unified-adapter-and-prompt-learning
APoLLo: Unified Adapter and Prompt Learning for Vision Language Models
2312.01564
https://arxiv.org/abs/2312.01564v1
https://arxiv.org/pdf/2312.01564v1.pdf
https://github.com/schowdhury671/APoLLo
false
false
false
pytorch
https://paperswithcode.com/paper/look-at-me-no-replay-surprisenet-anomaly
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning
2310.20052
https://arxiv.org/abs/2310.20052v1
https://arxiv.org/pdf/2310.20052v1.pdf
https://github.com/tachyonicclock/surprisenet-cikm-23
true
true
true
pytorch
https://paperswithcode.com/paper/histopathological-image-analysis-with-style
Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved Generalization
2310.20638
https://arxiv.org/abs/2310.20638v1
https://arxiv.org/pdf/2310.20638v1.pdf
https://github.com/vaibhav-khamankar/fusestyle
true
true
false
pytorch
https://paperswithcode.com/paper/bias-against-93-stigmatized-groups-in-masked
Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks
2306.05550
https://arxiv.org/abs/2306.05550v1
https://arxiv.org/pdf/2306.05550v1.pdf
https://github.com/mooniem/mlms_bias_stigmas
true
true
true
pytorch
https://paperswithcode.com/paper/prefix-tree-decoding-for-predicting-mass
Prefix-Tree Decoding for Predicting Mass Spectra from Molecules
2303.06470
https://arxiv.org/abs/2303.06470v3
https://arxiv.org/pdf/2303.06470v3.pdf
https://github.com/samgoldman97/ms-pred
true
true
true
pytorch
https://paperswithcode.com/paper/dataset-and-benchmark-for-urdu-natural-scenes
Dataset and Benchmark for Urdu Natural Scenes Text Detection, Recognition and Visual Question Answering
2405.12533
https://arxiv.org/abs/2405.12533v1
https://arxiv.org/pdf/2405.12533v1.pdf
https://github.com/hiba-meiruan/urdu-vqa-dataset-
true
true
true
none
https://paperswithcode.com/paper/mind-the-gap-between-prototypes-and-images-in
Mind the Gap Between Prototypes and Images in Cross-domain Finetuning
2410.12474
https://arxiv.org/abs/2410.12474v2
https://arxiv.org/pdf/2410.12474v2.pdf
https://github.com/tmlr-group/CoPA
true
true
true
tf
https://paperswithcode.com/paper/aligning-llms-with-domain-invariant-reward
Aligning LLMs with Domain Invariant Reward Models
2501.00911
https://arxiv.org/abs/2501.00911v1
https://arxiv.org/pdf/2501.00911v1.pdf
https://github.com/portal-cornell/dial
true
true
true
pytorch
https://paperswithcode.com/paper/data-driven-study-of-composition-dependent
Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys
2402.12520
https://arxiv.org/abs/2402.12520v1
https://arxiv.org/pdf/2402.12520v1.pdf
https://github.com/sinazadeh/phase-compatibility-model-niti
true
true
false
none
https://paperswithcode.com/paper/universal-representation-learning-from
Universal Representation Learning from Multiple Domains for Few-shot Classification
2103.13841
https://arxiv.org/abs/2103.13841v1
https://arxiv.org/pdf/2103.13841v1.pdf
https://github.com/tmlr-group/CoPA
false
false
true
tf
https://paperswithcode.com/paper/meta-dataset-a-dataset-of-datasets-for
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
1903.03096
https://arxiv.org/abs/1903.03096v4
https://arxiv.org/pdf/1903.03096v4.pdf
https://github.com/tmlr-group/CoPA
false
false
true
tf
https://paperswithcode.com/paper/unleashing-the-creative-mind-language-model
Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving
2311.00694
https://arxiv.org/abs/2311.00694v2
https://arxiv.org/pdf/2311.00694v2.pdf
https://github.com/lz1oceani/llm-as-hierarchical-policy
true
true
true
none
https://paperswithcode.com/paper/event-causality-is-key-to-computational-story
Event Causality Is Key to Computational Story Understanding
2311.09648
https://arxiv.org/abs/2311.09648v2
https://arxiv.org/pdf/2311.09648v2.pdf
https://github.com/insundaycathy/event-causality-extraction
true
true
true
pytorch
https://paperswithcode.com/paper/chemplaskin-a-general-purpose-program-for
ChemPlasKin: a general-purpose program for unified gas and plasma kinetics simulations
2405.04224
https://arxiv.org/abs/2405.04224v1
https://arxiv.org/pdf/2405.04224v1.pdf
https://github.com/ShaoX96/ChemPlasKin
true
false
true
none
https://paperswithcode.com/paper/distributed-statistical-machine-learning-in
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
1705.05491
http://arxiv.org/abs/1705.05491v2
http://arxiv.org/pdf/1705.05491v2.pdf
https://github.com/bladesteam/blades
false
false
true
pytorch
https://paperswithcode.com/paper/smaller-language-models-are-capable-of
Smaller Language Models are capable of selecting Instruction-Tuning Training Data for Larger Language Models
2402.10430
https://arxiv.org/abs/2402.10430v1
https://arxiv.org/pdf/2402.10430v1.pdf
https://github.com/dheeraj7596/small2large
true
true
true
pytorch
https://paperswithcode.com/paper/hierspeech-bridging-the-gap-between-semantic
HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis
2311.12454
https://arxiv.org/abs/2311.12454v2
https://arxiv.org/pdf/2311.12454v2.pdf
https://github.com/sh-lee-prml/hierspeechpp
true
true
true
pytorch
https://paperswithcode.com/paper/readme-bridging-medical-jargon-and-lay
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP
2312.15561
https://arxiv.org/abs/2312.15561v5
https://arxiv.org/pdf/2312.15561v5.pdf
https://github.com/seasonyao/noteaid-readme
true
true
false
none
https://paperswithcode.com/paper/unsupervised-discovery-of-interpretable-3
Unsupervised discovery of Interpretable Visual Concepts
2309.00018
https://arxiv.org/abs/2309.00018v2
https://arxiv.org/pdf/2309.00018v2.pdf
https://github.com/carolmazini/unsupervised-ivc
true
true
false
pytorch
https://paperswithcode.com/paper/wear-a-multimodal-dataset-for-wearable-and
WEAR: An Outdoor Sports Dataset for Wearable and Egocentric Activity Recognition
2304.05088
https://arxiv.org/abs/2304.05088v4
https://arxiv.org/pdf/2304.05088v4.pdf
https://github.com/mariusbock/wear
true
false
true
pytorch
https://paperswithcode.com/paper/bridging-the-gap-between-domain-specific
Bridging the Gap Between Domain-specific Frameworks and Multiple Hardware Devices
2405.12491
https://arxiv.org/abs/2405.12491v1
https://arxiv.org/pdf/2405.12491v1.pdf
https://github.com/benchcouncil/bridger
true
true
false
none
https://paperswithcode.com/paper/mm-sap-a-comprehensive-benchmark-for
MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception
2401.07529
https://arxiv.org/abs/2401.07529v3
https://arxiv.org/pdf/2401.07529v3.pdf
https://github.com/yhwmz/mm-sap
true
true
true
none
https://paperswithcode.com/paper/asgir-audio-spectrogram-transformer-guided
ASGIR: Audio Spectrogram Transformer Guided Classification And Information Retrieval For Birds
2407.18927
https://arxiv.org/abs/2407.18927v1
https://arxiv.org/pdf/2407.18927v1.pdf
https://github.com/mainsample1234/as-gir
true
true
false
pytorch
https://paperswithcode.com/paper/gohberg-semencul-estimation-of-toeplitz
Gohberg-Semencul Estimation of Toeplitz Structured Covariance Matrices and Their Inverses
2311.14995
https://arxiv.org/abs/2311.14995v1
https://arxiv.org/pdf/2311.14995v1.pdf
https://github.com/beneboeck/toep-cov-estimation
true
true
false
none
https://paperswithcode.com/paper/a-self-attentive-model-for-knowledge-tracing
A Self-Attentive model for Knowledge Tracing
1907.06837
https://arxiv.org/abs/1907.06837v1
https://arxiv.org/pdf/1907.06837v1.pdf
https://github.com/nanzhaogang/contrib/tree/master/application/a-self-attentive-model-for-knowledge-tracing
false
false
false
mindspore
https://paperswithcode.com/paper/zo-adamu-optimizer-adapting-perturbation-by
ZO-AdaMU Optimizer: Adapting Perturbation by the Momentum and Uncertainty in Zeroth-order Optimization
2312.15184
https://arxiv.org/abs/2312.15184v1
https://arxiv.org/pdf/2312.15184v1.pdf
https://github.com/mathisall/zo-adamu
true
true
false
pytorch
https://paperswithcode.com/paper/grokformer-graph-fourier-kolmogorov-arnold
GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers
2411.17296
https://arxiv.org/abs/2411.17296v1
https://arxiv.org/pdf/2411.17296v1.pdf
https://github.com/GGA23/GrokFormer
true
false
false
pytorch
https://paperswithcode.com/paper/fine-tuning-language-models-with-just-forward-1
Fine-Tuning Language Models with Just Forward Passes
2305.17333
https://arxiv.org/abs/2305.17333v3
https://arxiv.org/pdf/2305.17333v3.pdf
https://github.com/mathisall/zo-adamu
false
false
true
pytorch
https://paperswithcode.com/paper/sfpnet-sparse-focal-point-network-for
SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds
2407.11569
https://arxiv.org/abs/2407.11569v1
https://arxiv.org/pdf/2407.11569v1.pdf
https://github.com/Cavendish518/SFPNet
true
true
true
pytorch
https://paperswithcode.com/paper/towards-non-robocentric-dynamic-landing-of
Towards Non-Robocentric Dynamic Landing of Quadrotor UAVs
2401.11445
https://arxiv.org/abs/2401.11445v1
https://arxiv.org/pdf/2401.11445v1.pdf
https://github.com/hkpolyu-uav/alan
true
true
false
none
https://paperswithcode.com/paper/couler-unified-machine-learning-workflow
Couler: Unified Machine Learning Workflow Optimization in Cloud
2403.07608
https://arxiv.org/abs/2403.07608v1
https://arxiv.org/pdf/2403.07608v1.pdf
https://github.com/couler-proj/couler
true
true
true
none
https://paperswithcode.com/paper/the-mass-profiles-of-dwarf-galaxies-from-dark
The mass profiles of dwarf galaxies from Dark Energy Survey lensing
2311.14659
https://arxiv.org/abs/2311.14659v1
https://arxiv.org/pdf/2311.14659v1.pdf
https://github.com/aamon/dwarf-lensing
true
true
true
none
https://paperswithcode.com/paper/rapid-training-of-deep-neural-networks
Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping
2110.01765
https://arxiv.org/abs/2110.01765v1
https://arxiv.org/pdf/2110.01765v1.pdf
https://github.com/ml-jku/convex-init
false
false
true
pytorch
https://paperswithcode.com/paper/wav2vec-2-0-a-framework-for-self-supervised
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
2006.11477
https://arxiv.org/abs/2006.11477v3
https://arxiv.org/pdf/2006.11477v3.pdf
https://github.com/sh-lee-prml/hierspeechpp
false
false
true
pytorch