5 papers
Communication-Efficient Module-Wise Federated Learning for Grasp Pose Detection in Cluttered Environments
Woonsang Kang, Joohyung Lee, Seungjun Kim +2
Grasp pose detection (GPD) is a fundamental capability for robotic autonomy, but its reliance on large, diverse datasets creates significant data privacy and centralization challen…
Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection
Taeheon Lim, Joohyung Lee, Kyungjae Lee +1
The Federated Learning (FL) approach enables effective learning across distributed systems, while preserving user data privacy. To date, research has primarily focused on addressin…
Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs
Anshumann, Mohd Abbas Zaidi, Akhil Kedia +5
Knowledge distillation can be a cost-effective technique to distill knowledge in Large Language Models, if the teacher output logits can be pre-computed and cached. However, succes…
Pathwise Explanation of ReLU Neural Networks
Seongwoo Lim, Won Jo, Joohyung Lee +1
Neural networks have demonstrated a wide range of successes, but their ``black box" nature raises concerns about transparency and reliability. Previous research on ReLU networks ha…
Multi-Reranker: Maximizing performance of retrieval-augmented generation in the FinanceRAG challenge
Joohyun Lee, Minji Roh
As Large Language Models (LLMs) increasingly address domain-specific problems, their application in the financial sector has expanded rapidly. Tasks that are both highly valuable a…