3 papers
cs.AI2026
ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding
Keuntae Kim, Beomseok Lee, Hyunwoo Kim +1
Vision Language Models (VLMs) achieve strong reasoning with Chain-of-Thought (CoT) prompting but incur high sequential-generation cost, error accumulation, and limited self-correct…
cs.AI2026
Thinking Diffusion: Penalize and Guide Visual-Grounded Reasoning in Diffusion Multimodal Language Models
Keuntae Kim, Mingyu Kang, Yong Suk Choi
Diffusion large language models (dLLMs) are emerging as promising alternatives to autoregressive (AR) LLMs. Recently, this paradigm has been extended to multimodal tasks, leading t…
cs.CL2025
CLAWS:Creativity detection for LLM-generated solutions using Attention Window of Sections
Keuntae Kim, Eunhye Jeong, Sehyeon Lee +2
Recent advances in enhancing the reasoning ability of large language models (LLMs) have been remarkably successful. LLMs trained with reinforcement learning (RL) for reasoning demo…