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Yejin Lee

4 accepted papers

2025

AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection

EMNLP 2025

Implicit hate speech detection is challenging due to its subtlety and reliance on contextual interpretation rather than explicit offensive words. Current approaches rely on contrastive learning, which are shown to be effective on distinguishing hate and non-hate sentences. Humans, however, detect im

2024

CHAI: Clustered Head Attention for Efficient LLM Inference

ICML 2024poster

Large Language Models (LLMs) with hundreds of billions of parameters have transformed the field of machine learning. However, serving these models at inference time is both compute and memory intensive, where a single request can require multiple GPUs and tens of Gigabytes of memory. Multi-head atte…

2024

Frugal 3D Point Cloud Model Training via Progressive Near Point Filtering and Fused Aggregation

ECCV 2024poster

"The increasing demand on higher accuracy and the rapid growth of 3D point cloud datasets have led to significantly higher training costs for 3D point cloud models in terms of both computation and memory bandwidth. Despite this, research on reducing this cost is relatively sparse. This paper identif…

2023

Not All Neighbors Matter: Point Distribution-Aware Pruning for 3D Point Cloud

AAAI 2023technical

Applying deep neural networks to 3D point cloud processing has demonstrated a rapid pace of advancement in those domains where 3D geometry information can greatly boost task performance, such as AR/VR, robotics, and autonomous driving. However, as the size of both the neural network model and 3D poi…