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20232026
most citedThe Role of Teacher Calibration in Knowledge Distillation

3 citations · 5 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Point-to-Point: Sparse Motion Guidance for Controllable Video Editing

Yeji Song, Jaehyun Lee, Mijin Koo +2

Accurately preserving motion while editing a subject remains a core challenge in video editing tasks. Existing methods often face a trade-off between edit and motion fidelity, as t…

cs.CL2025

Unlocking the Potential of Diffusion Language Models through Template Infilling

Junhoo Lee, Seungyeon Kim, Nojun Kwak

Diffusion Language Models (DLMs) have emerged as a promising alternative to Autoregressive Language Models, yet their inference strategies remain limited to prefix-based prompting…

cs.LG2025

Deep Edge Filter: Return of the Human-Crafted Layer in Deep Learning

Dongkwan Lee, Junhoo Lee, Nojun Kwak

We introduce the Deep Edge Filter, a novel approach that applies high-pass filtering to deep neural network features to improve model generalizability. Our method is motivated by o…

cs.LG2025★ 3 cited

The Role of Teacher Calibration in Knowledge Distillation

Suyoung Kim, Seonguk Park, Junhoo Lee +1

Knowledge Distillation (KD) has emerged as an effective model compression technique in deep learning, enabling the transfer of knowledge from a large teacher model to a compact stu…

cs.CV2025

What's Making That Sound Right Now? Video-centric Audio-Visual Localization

Hahyeon Choi, Junhoo Lee, Nojun Kwak

Audio-Visual Localization (AVL) aims to identify sound-emitting sources within a visual scene. However, existing studies focus on image-level audio-visual associations, failing to…