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20222026
most citedThe Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

151 citations · 171 across the 11 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023

HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning

Yongjin Yang, Joonkee Kim, Yujin Kim +3

With the proliferation of social media, accurate detection of hate speech has become critical to ensure safety online. To combat nuanced forms of hate speech, it is important to id…

cs.CL2023★ 2 cited

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions

Taehyeon Kim, Joonkee Kim, Gihun Lee +1

While instruction-tuned language models have demonstrated impressive zero-shot generalization, these models often struggle to generate accurate responses when faced with instructio…

eess.IV2023★ 151 cited

The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

Jun Ma, Ronald Xie, Shamini Ayyadhury +37

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…

cs.LG2023★ 1 cited

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

Hojoon Lee, Hanseul Cho, Hyunseung Kim +5

In Reinforcement Learning (RL), enhancing sample efficiency is crucial, particularly in scenarios when data acquisition is costly and risky. In principle, off-policy RL algorithms…

cs.LG2023

Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning

Jihwan Oh, Joonkee Kim, Minchan Jeong +1

The multi-agent setting is intricate and unpredictable since the behaviors of multiple agents influence one another. To address this environmental uncertainty, distributional reinf…