1 citations · 1 across the 9 of their papers we have counts for
9 papers
ChimeraLoRA: Multi-Head LoRA-Guided Synthetic Datasets
Hoyoung Kim, Minwoo Jang, Jabin Koo +2
Beyond general recognition tasks, specialized domains and fine-grained settings often encounter data scarcity, especially for tail classes. To obtain less biased and more reliable…
Emergence of Text Readability in Vision Language Models
Jaeyoo Park, Sanghyuk Chun, Wonjae Kim +2
We investigate how the ability to recognize textual content within images emerges during the training of Vision-Language Models (VLMs). Our analysis reveals a critical phenomenon:…
KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction
Jang-Hyun Kim, Jinuk Kim, Sangwoo Kwon +3
Transformer-based large language models (LLMs) cache context as key-value (KV) pairs during inference. As context length grows, KV cache sizes expand, leading to substantial memory…
LongProLIP: A Probabilistic Vision-Language Model with Long Context Text
Sanghyuk Chun, Sangdoo Yun
Recently, Probabilistic Language-Image Pre-Training (ProLIP) has been proposed to tackle the multiplicity issue of vision-language (VL) tasks. Despite their success in probabilisti…
Probabilistic Language-Image Pre-Training
Sanghyuk Chun, Wonjae Kim, Song Park +1
Vision-language models (VLMs) embed aligned image-text pairs into a joint space but often rely on deterministic embeddings, assuming a one-to-one correspondence between images and…
Large-Scale Targeted Cause Discovery via Learning from Simulated Data
Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun +2
We propose a novel machine learning approach for inferring causal variables of a target variable from observations. Our focus is on directly inferring a set of causal factors witho…
HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts
Wonjae Kim, Sanghyuk Chun, Taekyung Kim +2
In an era where the volume of data drives the effectiveness of self-supervised learning, the specificity and clarity of data semantics play a crucial role in model training. Addres…
Toward Interactive Regional Understanding in Vision-Large Language Models
Jungbeom Lee, Sanghyuk Chun, Sangdoo Yun
Recent Vision-Language Pre-training (VLP) models have demonstrated significant advancements. Nevertheless, these models heavily rely on image-text pairs that capture only coarse an…
Compressed Context Memory For Online Language Model Interaction
Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun +1
This paper presents a context key/value compression method for Transformer language models in online scenarios, where the context continually expands. As the context lengthens, the…