3 citations · 5 across the 12 of their papers we have counts for
21 papers
N-Gram Memories at Two Bits: Quantizing Lookup Tables in Large Language Models
Donghoon Han, Minseop Jung, Dong Woo Kwak +2
Conditional memory expands language-model capacity through selective lookup, but the full embedding table must remain available for every possible input. We introduce Conditional P…
Policy-Aligned Predictive Verification for Adaptive VLA Action-Chunk Execution
Minkyu Kim, Junhoo Lee, Seungyeon Kim +4
Vision-language-action (VLA) policies generate action sequences that reduce repeated inference, but deciding how much of each sequence to execute is critical to task success. Exist…
ManiFusion: Unlocking the High-Throughput Generation via Superposition in Manifold Space
Minkyu Kim, Baekseung Kim, Junhoo Lee +2
Diffusion models achieve high-quality image generation but remain computationally expensive due to iterative denoising across many timesteps. Existing acceleration methods mainly r…
Clean Data Can Still Carry Backdoors: Support-Persistent Backdoors for Model Reuse
Junhoo Lee, Baekseung Kim, Seungyeon Kim +1
Traditional backdoor attacks inject artificial trigger patterns into training data, causing models to misclassify triggered inputs while maintaining normal behavior on clean sample…
Two Companion -Series Identities and Their Combinatorics
Haijun Li, Chenwei Wang
In this paper, we evaluate two companion -series recently suggested for investigation by Andrews and El Bachraoui in the concluding remarks of their work. From these evaluations…
Discriminative Score Function: Turning Pretrained Models into Functional Generative Priors
Junhoo Lee, Hyeonjin Kim, Sangbum Han +1
Discriminative models are trained with task-specific objectives such as classification, detection, or representation learning, yet their practical utility depends on generalizing b…
ACRO: Actor-Critic Rollout Orchestration
Junhoo Lee, Seungyeon Kim, Baekseung Kim +4
Executing a vision-language-action (VLA) policy involves deciding when to continue an attempt and when to intervene to improve its chances of success. We introduce ACRO, an Actor--…
Recursive Harness Distillation across Agents for Robot Manipulation
Seungyeon Kim, Junhoo Lee, Minkyu Kim +2
A central goal in robotics is to enable manipulation across changing tasks and environments. Vision-language-action (VLA) models provide broad manipulation capabilities but can str…
LandingAgent: A Reference-Annotated Dataset and Agentic Generation Framework for Landing Pages
Injun Baek, HyeongSeok Lee, Yearim Kim +2
Landing pages are goal-oriented web interfaces that must communicate a target-specific value proposition while organizing information flow, visual hierarchy, and calls to action (C…
CSF: Black-box Fingerprinting via Compositional Semantics for Text-to-Image Models
Junhoo Lee, Mijin Koo, Nojun Kwak
Text-to-image models are commercially valuable assets often distributed under restrictive licenses, but such licenses are enforceable only when violations can be detected. Existing…
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…
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…
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…
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…
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…
Practical Dataset Distillation Based on Deep Support Vectors
Hyunho Lee, Junhoo Lee, Nojun Kwak
Conventional dataset distillation requires significant computational resources and assumes access to the entire dataset, an assumption impractical as it presumes all data resides o…
Coreset Selection for Object Detection
Hojun Lee, Suyoung Kim, Junhoo Lee +2
Coreset selection is a method for selecting a small, representative subset of an entire dataset. It has been primarily researched in image classification, assuming there is only on…
Do not think about pink elephant!
Kyomin Hwang, Suyoung Kim, JunHoo Lee +1
Large Models (LMs) have heightened expectations for the potential of general AI as they are akin to human intelligence. This paper shows that recent large models such as Stable Dif…
Deep Support Vectors
Junhoo Lee, Hyunho Lee, Kyomin Hwang +1
Deep learning has achieved tremendous success. However, unlike SVMs, which provide direct decision criteria and can be trained with a small dataset, it still has significant weakne…
Any-Way Meta Learning
Junhoo Lee, Yearim Kim, Hyunho Lee +1
Although meta-learning seems promising performance in the realm of rapid adaptability, it is constrained by fixed cardinality. When faced with tasks of varying cardinalities that w…
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
JunHoo Lee, Jayeon Yoo, Nojun Kwak
In this paper, we hypothesize that gradient-based meta-learning (GBML) implicitly suppresses the Hessian along the optimization trajectory in the inner loop. Based on this hypothes…