4 papers
CDLM: Consistency Diffusion Language Models For Faster Sampling
Minseo Kim, Chenfeng Xu, Coleman Hooper +5
Diffusion Language Models (DLMs) offer a promising parallel generation paradigm but suffer from slow inference due to numerous refinement steps and the inability to use standard KV…
Beyond Next-Token Prediction: A Performance Characterization of Diffusion versus Autoregressive Language Models
Minseo Kim, Coleman Hooper, Aditya Tomar +5
Large Language Models (LLMs) have achieved state-of-the-art performance on a broad range of Natural Language Processing (NLP) tasks, including document processing and code generati…
Federated Learning with Feedback Alignment
Incheol Baek, Hyungbin Kim, Minseo Kim +1
Federated Learning (FL) enables collaborative training across multiple clients while preserving data privacy, yet it struggles with data heterogeneity, where clients' data are not…
HE2C: A Holistic Approach for Allocating Latency-Sensitive AI Tasks across Edge-Cloud
Minseo Kim, Wei Shu, Mohsen Amini Salehi
The high computational, memory, and energy demands of Deep Learning (DL) applications often exceed the capabilities of battery-powered edge devices, creating difficulties in meetin…