2 citations · 3 across the 3 of their papers we have counts for
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cs.AI2026
RetroPlanner: Multi-Route Expansion and Multi-Objective Reasoning for LLM-Based Retrosynthesis Planning
Ye Rin Kim, Yongjun Jeong, Seongjun Yun +4
Multi-step retrosynthesis planning is often considered solved once a route to purchasable starting materials is found, but such a route should also be practical in real-world chemi…
cs.AI2026
MolDesignBench: Evaluating LLM-based Agent for Scenario-grounded Molecular Design
Yongjun Jeong, Hanbum Ko, Ye Rin Kim +6
Real-world molecular design remains challenging for large language model (LLM)-based agents. It requires them to interpret design contexts, satisfy multiple constraints, identify i…
cs.AI2023★ 1 cited
Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?
Chanhui Lee, Juhyeon Kim, Yongjun Jeong +9
Scaling laws have allowed Pre-trained Language Models (PLMs) into the field of causal reasoning. Causal reasoning of PLM relies solely on text-based descriptions, in contrast to ca…