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cs.AI2026
TactiNavi: Serving and Revising an LLM Game Coach with Explicit Strategy Conditions
Qi Liu, Xiaoyang Yuan, Zhuomeng Zhang +9
A deployed LLM coaching agent answers requests whose correct response depends on player state and game version, so advice that is right for one player can be wrong for the next. We…
cs.AI2026
DAAF: From Failure Localization to Editable System Assets in LLM Agents
Xiaoyang Yuan, Qi Liu, Yubin Ruan +9
Deployed LLM agents increasingly rely on persistent, versioned system assets such as routing rules, knowledge segments, prompt instructions, and reusable skills. Failure-localizati…
cs.AI2026
State-Grounded Conditioning: Wrapping User-Facing LLM Agents Where Direction Depends on Live State
Qi Liu, Xiaoyang Yuan, Yubin Ruan +8
We introduce State-Grounded Conditioning (SGC), a design principle for user-facing LLM agents that must condition on live user state (game state, session history, live inventory),…