Top Papers
GPT4All: An Ecosystem of Open Source Compressed Language Models
nomic-ai/gpt4all
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It is our hope that this paper acts as both a technical overview of the original GPT4All models as well as a case study on the subsequent growth of the GPT4All open source ecosystem.
Politeness Transfer: A Tag and Generate Approach
fighting41love/funNLP
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ACL 2020
This paper introduces a new task of politeness transfer which involves converting non-polite sentences to polite sentences while preserving the meaning.
CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
fighting41love/funNLP
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TACL 2020
To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.
MaskNet: Introducing Feature-Wise Multiplication to CTR Ranking Models by Instance-Guided Mask
We also turn the feed-forward layer in DNN model into a mixture of addictive and multiplicative feature interactions by proposing MaskBlock in this paper.
Ranked #8 on
Click-Through Rate Prediction
on Criteo
A ConvNet for the 2020s
keras-team/keras
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CVPR 2022
The "Roaring 20s" of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification model.
Ranked #1 on
Classification
on InDL
RegNet: Self-Regulated Network for Image Classification
keras-team/keras
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The ResNet and its variants have achieved remarkable successes in various computer vision tasks.
Ranked #3 on
Medical Image Classification
on NCT-CRC-HE-100K
Adapting Large Language Model with Speech for Fully Formatted End-to-End Speech Recognition
openai/whisper
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Most end-to-end (E2E) speech recognition models are composed of encoder and decoder blocks that perform acoustic and language modeling functions.
Improving the Cluster Structure Extracted from OPTICS Plots
Density-based clustering is closely associated with the two algorithms DBSCAN and OPTICS.
Scikit-learn: Machine Learning in Python
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
In this work we introduce a new optimisation method called SAGA in the spirit of SAG, SDCA, MISO and SVRG, a set of recently proposed incremental gradient algorithms with fast linear convergence rates.
