2 citations · 5 across the 6 of their papers we have counts for
6 papers
Mini-Batch Optimization of Contrastive Loss
Jaewoong Cho, Kartik Sreenivasan, Keon Lee +7
Contrastive learning has gained significant attention as a method for self-supervised learning. The contrastive loss function ensures that embeddings of positive sample pairs (e.g.…
Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding
Seongjun Yang, Gibbeum Lee, Jaewoong Cho +2
This paper presents "Predictive Pipelined Decoding (PPD)," an approach that speeds up greedy decoding in Large Language Models (LLMs) while maintaining the exact same output as the…
Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
TaeHo Yoon, Kibeom Myoung, Keon Lee +3
Diffusion models have recently shown remarkable success in high-quality image generation. Sometimes, however, a pre-trained diffusion model exhibits partial misalignment in the sen…
Equal Experience in Recommender Systems
Jaewoong Cho, Moonseok Choi, Changho Suh
We explore the fairness issue that arises in recommender systems. Biased data due to inherent stereotypes of particular groups (e.g., male students' average rating on mathematics i…
Wasserstein GAN Can Perform PCA
Jaewoong Cho, Changho Suh
Generative Adversarial Networks (GANs) have become a powerful framework to learn generative models that arise across a wide variety of domains. While there has been a recent surge…
Two-Way Interference Channel Capacity: How to Have the Cake and Eat it Too
Changho Suh, Jaewoong Cho, David Tse
Two-way communication is prevalent and its fundamental limits are first studied in the point-to-point setting by Shannon [1]. One natural extension is a two-way interference channe…