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SkillChain: Closing the Loop on Skill Evolution for Image-Based E-Commerce AI Assistants

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arXiv:2606. 12984v1 Announce Type: new Abstract: Image-based AI assistants are now deployed at production scale on e-commerce platforms, where a single uploaded image can trigger fundamentally different user intents: product search, style recommendation, visual encyclopedia, or utility tool calls, each demanding its own response format, tool invocation, and domain knowledge.

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Authors: Yimin Hu, Mengtao Xu, Hao Guo, Yuheng Song, Xiaoyong Zhu, Bo Zheng
Released: 2026-06-12 (27d ago)
Topic: Related to current project
Relation to my work: Read next because SkillChain: Closing the Loop on Skill Evolution for Image-Based E-Commerce AI Assistants overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: strong, alignment, eval, assistant, line, without, chain, stage. Source: arxiv cs.CL (NLP).
arXiv: 2606.12984

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