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20162024
most citedDeep CNNs along the Time Axis with Intermap Pooling for Robustness to Spectral Variations

8 citations · 20 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL20247 cited

HyperCLOVA X Technical Report

Kang Min Yoo, Jaegeun Han, Sookyo In +393

We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…

cs.CL2024

Calibrating Large Language Models Using Their Generations Only

Dennis Ulmer, Martin Gubri, Hwaran Lee +2

As large language models (LLMs) are increasingly deployed in user-facing applications, building trust and maintaining safety by accurately quantifying a model's confidence in its p…

cs.CL20235 cited

KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Application

Hwaran Lee, Seokhee Hong, Joonsuk Park +3

Large language models (LLMs) learn not only natural text generation abilities but also social biases against different demographic groups from real-world data. This poses a critica…

cs.CL2023

SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created Through Human-Machine Collaboration

Hwaran Lee, Seokhee Hong, Joonsuk Park +10

The potential social harms that large language models pose, such as generating offensive content and reinforcing biases, are steeply rising. Existing works focus on coping with thi…

cs.CL20168 cited

Deep CNNs along the Time Axis with Intermap Pooling for Robustness to Spectral Variations

Hwaran Lee, Geonmin Kim, Ho-Gyeong Kim +2

Convolutional neural networks (CNNs) with convolutional and pooling operations along the frequency axis have been proposed to attain invariance to frequency shifts of features. How…