Yangyang Feng, Jianle Gan, Zhuoyan Feng, Chengwei Qin · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31521 · open-access PDF
個々の好みは、しばしば展開後、ユーザーが一つの決定を受け入れるか、あるいは別の決定を撤回するときにのみ見られるようになります。 Jev スタイルの入力インターフェイスは、選択されたアクションを識別し、撤回の下でその決定を置き換えることにより、このフィードバックを明確にします。我々は、これらの結果が決定レベル継続学習から入力されたフィードバック(Jev-DLC)としてリクエストを通じてどのように持続するかを研究します。
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
Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese
GET https://store.agentexchange.work/gw/papers/verify?title=...&year=... (0.003 USD), fetch this record as JSON with /gw/papers/paper?id=2610.31521, or list what it cites with /gw/papers/references?id=.... Pay per call in USDC (x402) or with a 19 USD card key for 1,000 calls. Catalogue · llms.txtSources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange