1 citations · 2 across the 6 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.LG2026
MAPLE: A Multi-Axis Parametric Knowledge Extraction Lens for LLM Evaluation
Minsuh Joo, Youna Kim, Choonghyun Park +2
LLMs absorb vast knowledge from training data, yet their inherently probabilistic nature offers no guarantee that this knowledge will surface in their outputs. To bridge this gap,…
cs.AI2026
LUMOS: Tracing Parametric Knowledge from Training Data to Behavioral Outputs in LLMs
Seoyeon Ye, Gayoung Kim, Jiyoung Hong +2
Current analyses of LLMs' parametric knowledge are largely output-centric, drawing conclusions about what a model knows without verifying what it was actually trained on. This leav…
cs.CV2026
A More Word-like Image Tokenization for MLLMs
Hyun Lee, Hyemin Jeong, Yejin Kim +4
Modern multimodal large language models (MLLMs) typically keep the language model fixed and train a visual projector that maps the pixels into a sequence of tokens in its embedding…