[Agent] Evolving Procedural Memory from User Traffic for Agentic Graphic Design: weight update 없이 skill bank를 키워 그래픽 디자인 에이전트를 진화
[Agent] Evolving Procedural Memory from User Traffic for Agentic Graphic Design
Recent posts
[Agent] MENTOR: Teacher-Optimized Reward로 Tool-Use를 SLM에 distill하는 on-policy RL
[Agent] MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation
Agent Distillation
title: “[Agent] Agent Distillation: CoT가 아니라 ‘행동’을 증류해서 0.5B 모델을 도구 쓰는 에이전트로 만들기”
[VLM] CommerceVibe: 이커머스 크리에이티브를 실행 가능한 HTML/CSS 코드로 생성하는 Dual-Feedback RL
[VLM] CommerceVibe: Learning to Design E-Commerce Creatives as Executable Visual Code via Dual-Feedback Reinforcement Learning
[LLM] On-Policy Self-Distillation: 하나의 LLM이 스스로의 teacher가 되어 추론을 가르치기
[LLM] On-Policy Self-Distillation for Large Language Models