72 citations · 330 across the 48 of their papers we have counts for
9 papers · 1 filter
Understanding the Effects of Distractors on Reasoning Vision-Language Models
Jiyun Bae, Hyunjong Ok, Sangwoo Mo +1
How does irrelevant information (i.e., distractors) affect test-time scaling in vision-language models (VLMs)? Prior work on text-only language models has shown that textual distra…
Neural Weight Compression for Language Models
Jegwang Ryu, Minkyu Kim, Seungjun Shin +3
Efficient compression of language model weights is increasingly critical as model scale and deployment grow. Yet, most existing methods rely on handcrafted transforms and heuristic…
Activation Quantization of Vision Encoders Needs Prefixing Registers
Seunghyeon Kim, Taesun Yeom, Jinho Kim +3
Large pretrained vision encoders are central to multimodal intelligence, powering applications from on-device vision processing to vision-language models. Since these applications…
AuditoryBench++: Can Language Models Understand Auditory Knowledge without Hearing?
Hyunjong Ok, Suho Yoo, Hyeonjun Kim +1
Even without directly hearing sounds, humans can effortlessly reason about auditory properties, such as pitch, loudness, or sound-source associations, drawing on auditory commonsen…
ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
Seonghwan Park, Jaehyeon Jeong, Yongjun Kim +2
Recent studies have introduced various approaches for prompt-tuning black-box vision-language models, referred to as black-box prompt-tuning (BBPT). While BBPT has demonstrated con…
On the Internal Representations of Graph Metanetworks
Taesun Yeom, Jaeho Lee
Weight space learning is an emerging paradigm in the deep learning community. The primary goal of weight space learning is to extract informative features from a set of parameters…
Speculative End-Turn Detector for Efficient Speech Chatbot Assistant
Hyunjong Ok, Suho Yoo, Jaeho Lee
Spoken dialogue systems powered by large language models have demonstrated remarkable abilities in understanding human speech and generating appropriate spoken responses. However,…
Imagine to Hear: Auditory Knowledge Generation can be an Effective Assistant for Language Models
Suho Yoo, Hyunjong Ok, Jaeho Lee
Language models pretrained on text-only corpora often struggle with tasks that require auditory commonsense knowledge. Previous work addresses this problem by augmenting the langua…
Prompt-based Depth Pruning of Large Language Models
Juyun Wee, Minjae Park, Jaeho Lee
Depth pruning aims to reduce the inference cost of a large language model without any hardware-specific complications, by simply removing several less important transformer blocks.…