9 papers
AdaBoosting Text Prompts for Vision-Language Models
Seokhee Jin, Changhwan Sung, Sunung Mun +2
The classification accuracy of pretrained Vision-Language Models (VLMs) relies on the quality of the text prompts. Handcrafted templates and Large Language Model (LLM)-generated de…
Making Models Unmergeable via Scaling-Sensitive Loss Landscape
Minwoo Jang, Hoyoung Kim, Jabin Koo +1
The rise of model hubs has made it easier to access reusable model components, making model merging a practical tool for combining capabilities. Yet, this modularity also creates a…
Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences
Jabin Koo, Hoyoung Kim, Minwoo Jang +1
Federated Learning (FL) offers a privacy-preserving pathway for aligning Large Language Models (LLMs); however, existing frameworks typically enforce a monolithic reward model, ine…
MMTB: Evaluating Terminal Agents on Multimedia-File Tasks
Chiyeong Heo, Jaechang Kim, Junhyuk Kwon +4
Terminals provide a powerful interface for AI agents by exposing diverse tools for automating complex workflows, yet existing terminal-agent benchmarks largely focus on tasks groun…
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…
Active Prompt Learning with Vision-Language Model Priors
Hoyoung Kim, Seokhee Jin, Changhwan Sung +2
Vision-language models (VLMs) have demonstrated remarkable zero-shot performance across various classification tasks. Nonetheless, their reliance on hand-crafted text prompts for e…