collaborators

5 papers

cs.CL2026

Dual Mechanisms of Value Expression: Intrinsic vs. Prompted Values in Large Language Models

Jongwook Han, Jongwon Lim, Injin Kong +1

Large language models can express values in two main ways: (1) intrinsic expression, reflecting the model's inherent values learned during training, and (2) prompted expression, el…

cs.LG2026

Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models

Injin Kong, Hyoungjoon Lee, Yohan Jo

Post-training pretrained autoregressive models (ARMs) into masked diffusion models (MDMs) has emerged as a cost-effective way to overcome the limitations of sequential generation.…

cs.CL2026

Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement

Injin Kong, Hyoungjoon Lee, Yohan Jo

Continuous diffusion language models lag behind autoregressive transformers, partly because diffusion is applied in spaces poorly suited to language denoising and token recovery. W…

cs.CV2026

Can MLLMs Reason About Visual Persuasion? Evaluating the Efficacy and Faithfulness of Reasoning

Naeun Lee, Hyunjong Kim, Sunghwan Choi +2

Despite strong performance of Multimodal Large Language Models (MLLMs) on multimodal tasks, predicting whether and why an image is persuasive remains challenging. We first show tha…

cs.CL2025

Style Extraction on Text Embeddings Using VAE and Parallel Dataset

InJin Kong, Shinyee Kang, Yuna Park +2

This study investigates the stylistic differences among various Bible translations using a Variational Autoencoder (VAE) model. By embedding textual data into high-dimensional vect…