most citedLANTERN++: Enhancing Relaxed Speculative Decoding with Static Tree Drafting for Visual Auto-regressive Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2025

ReviewScore: Misinformed Peer Review Detection with Large Language Models

Hyun Ryu, Doohyuk Jang, Hyemin S. Lee +16

Peer review serves as a backbone of academic research, but in most AI conferences, the review quality is degrading as the number of submissions explodes. To reliably detect low-qua…

cs.AI2025

Reasoning Model is Stubborn: Diagnosing Instruction Overriding in Reasoning Models

Doohyuk Jang, Yoonjeon Kim, Chanjae Park +2

Large language models have demonstrated remarkable proficiency in long and complex reasoning tasks. However, they frequently exhibit a problematic reliance on familiar reasoning pa…

cs.CV20251 cited

LANTERN++: Enhancing Relaxed Speculative Decoding with Static Tree Drafting for Visual Auto-regressive Models

Sihwan Park, Doohyuk Jang, Sungyub Kim +2

Speculative decoding has been widely used to accelerate auto-regressive (AR) text generation. However, its effectiveness for visual AR models remains limited due to token selection…

cs.CV2024

Med-PerSAM: One-Shot Visual Prompt Tuning for Personalized Segment Anything Model in Medical Domain

Hangyul Yoon, Doohyuk Jang, Jungeun Kim +1

Leveraging pre-trained models with tailored prompts for in-context learning has proven highly effective in NLP tasks. Building on this success, recent studies have applied a simila…

cs.CV2024

LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding

Doohyuk Jang, Sihwan Park, June Yong Yang +5

Auto-Regressive (AR) models have recently gained prominence in image generation, often matching or even surpassing the performance of diffusion models. However, one major limitatio…