2 citations · 2 across the 7 of their papers we have counts for
10 papers
DyRA: Dynamic Residual Approximation for Efficient Matrix Multiplication in DNNs
Daewon Chae, Hyunwon Chung, Changwoo Lee +1
Large-scale foundation models achieve strong performance across diverse tasks, but their size makes inference costly, largely due to dense matrix multiplications. Prior work reduce…
AxisGuide: Grounding Robot Action Coordinate System in RGB Observations for Robust Visuomotor Manipulation
Jiyun Jang, Yujin Sung, Woosung Joung +5
Visuomotor manipulation policies trained via large-scale behavior cloning have achieved strong semantic scene understanding, yet often fail to reliably execute correct low-level ac…
SemanticControl: A Training-Free Approach for Handling Loosely Aligned Visual Conditions in ControlNet
Woosung Joung, Daewon Chae, Jinkyu Kim
ControlNet has enabled detailed spatial control in text-to-image diffusion models by incorporating additional visual conditions such as depth or edge maps. However, its effectivene…
Scene Graph-Guided Proactive Replanning for Failure-Resilient Embodied Agent
Che Rin Yu, Daewon Chae, Dabin Seo +3
When humans perform everyday tasks, we naturally adjust our actions based on the current state of the environment. For instance, if we intend to put something into a drawer but not…
Streaming Dense Voxel Representations for 3D Occupancy Prediction
Seokha Moon, Janghyun Baek, Yujin Jeong +5
In this paper, we explore dense voxel streaming for accurate and efficient 3D occupancy prediction. While dense voxel representations offer fine-grained spatial details and streami…
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models
Daewon Chae, June Suk Choi, Jinkyu Kim +1
Fine-tuning text-to-image diffusion models to maximize rewards has proven effective for enhancing model performance. However, reward fine-tuning methods often suffer from slow conv…
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data
Thomas Zeng, Shuibai Zhang, Shutong Wu +13
Process Reward Models (PRMs) have proven effective at enhancing mathematical reasoning for Large Language Models (LLMs) by leveraging increased inference-time computation. However,…
ENTP: Encoder-only Next Token Prediction
Ethan Ewer, Daewon Chae, Thomas Zeng +2
Next-token prediction is conventionally done using decoder-only Transformers with causal attention, as this approach allows for efficient reuse of keys and values. What if we were…
InstructBooth: Instruction-following Personalized Text-to-Image Generation
Daewon Chae, Nokyung Park, Jinkyu Kim +1
Personalizing text-to-image models using a limited set of images for a specific object has been explored in subject-specific image generation. However, existing methods often face…
Clustering-based Image-Text Graph Matching for Domain Generalization
Nokyung Park, Daewon Chae, Jeongyong Shim +3
Learning domain-invariant visual representations is important to train a model that can generalize well to unseen target task domains. Recent works demonstrate that text descriptio…