Yangyang Feng, Jianle Gan, Zhuoyan Feng, Chengwei Qin · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31521 · open-access PDF
Preferensi individu sering menjadi terlihat hanya setelah implementasi, ketika seorang pengguna menerima satu keputusan atau membatalkannya demi yang lain. antarmuka tip-style membuat umpan balik ini eksplisit dengan mengidentifikasi tindakan yang dipilih dan, di bawah pembatalan, keputusan yang menggantikannya. Kami mempelajari bagaimana konsekuensi ini bertahan di atas permintaan seperti Keputusan-Level Continual Learning from Typed Feedback (Jev-DLC). Jev-DLC memperlakukan setiap koreksi sebagai bukti keduanya tentang identitas tindakan yang berulang dan hubungan yang diarahkan antara pilihan yang disukai dan ditolak.
Machine translation (Meta M2M100); the English original follows.
Individual preferences often become visible only after deployment, when a user accepts one decision or revokes it in favor of another. Jev-style typed interfaces make this feedback explicit by identifying the selected action and, under revocation, the decision it replaces. We study how these consequences persist across requests as Decision-Level Continual Learning from Typed Feedback (Jev-DLC). Jev-DLC treats each correction as both evidence about a recurring action identity and a directed relation between the preferred and rejected choices. It preserves these signals in complementary bounded
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