58 citations · 179 across the 32 of their papers we have counts for
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cs.AI2026
Router Prior Bias: Preserving Base Routing Structure in MoE Post-Training
Jaedeok Lee, Keonwoo Kim, Dongyoon Han +3
Mixture-of-Experts (MoE) pretraining relies on an auxiliary load-balancing loss (LBL) to drive per-expert utilization toward uniformity. Post-training inherits a different situatio…
cs.AI2026
VisualScratchpad: Inference-time Visual Concepts Analysis in Vision Language Models
Hyesu Lim, Jinho Choi, Taekyung Kim +3
High-performing vision language models still produce incorrect answers, yet their failure modes are often difficult to explain. To make model internals more accessible and enable s…
cs.AI2025
What Defines Good Reasoning in LLMs? Dissecting Reasoning Steps with Multi-Aspect Evaluation
Heejin Do, Jaehui Hwang, Dongyoon Han +2
Evaluating large language models (LLMs) on final-answer correctness is the dominant paradigm. This approach, however, provides a coarse signal for model improvement and overlooks t…