Multi-class Classification
234 papers with code • 4 benchmarks • 12 datasets
Benchmarks
These leaderboards are used to track progress in Multi-class Classification
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Libraries
Use these libraries to find Multi-class Classification models and implementationsDatasets
CARER
SMM4H
CVE
SF-MASK
TII-SSRC-23
Latest papers
Boosting Prompt-Based Self-Training With Mapping-Free Automatic Verbalizer for Multi-Class Classification
yookyungkho/mav
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Recently, prompt-based fine-tuning has garnered considerable interest as a core technique for few-shot text classification task.
Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
We introduce Llama Guard, an LLM-based input-output safeguard model geared towards Human-AI conversation use cases.
Improving Bias Mitigation through Bias Experts in Natural Language Understanding
To mitigate the detrimental effect of the bias on the networks, previous works have proposed debiasing methods that down-weight the biased examples identified by an auxiliary model, which is trained with explicit bias labels.
Exponentially Convergent Algorithms for Supervised Matrix Factorization
Supervised matrix factorization (SMF) is a classical machine learning method that simultaneously seeks feature extraction and classification tasks, which are not necessarily a priori aligned objectives.
Auto deep learning for bioacoustic signals
giuliotosato/autokeras-bioacustic
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This study investigates the potential of automated deep learning to enhance the accuracy and efficiency of multi-class classification of bird vocalizations, compared against traditional manually-designed deep learning models.
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination
heimine/pnc_dln
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To the best of our knowledge, this is the first quantitative characterization of feature evolution in hierarchical representations of deep linear networks.
Learning Robust Sequential Recommenders through Confident Soft Labels
furyton/csrec
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CSRec contains a teacher module that generates high-quality and confident soft labels and a student module that acts as the target recommender and is trained on the combination of dense, soft labels and sparse, one-hot labels.
Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems
Recently, various studies have presented machine unlearning algorithms and evaluated their methods on several datasets.
Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms
facebookresearch/InvarianceUnitTests
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First, in the binary classification setup of Rosenfeld et al. (2021), we show that our first algorithm, ISR-Mean, can identify the subspace spanned by invariant features from the first-order moments of the class-conditional distributions, and achieve provable domain generalization with $d_s+1$ training environments.
Efficient Machine Learning Ensemble Methods for Detecting Gravitational Wave Glitches in LIGO Time Series
ds4ai-upb/ml4gw
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The phenomenon of Gravitational Wave (GW) analysis has grown in popularity as technology has advanced and the process of observing gravitational waves has become more precise.
