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RECAP: Regression Evaluation for Continual Adaptation of Prompts

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arXiv:2606. 06698v1 Announce Type: new Abstract: Production agentic systems routinely face evolving constraints and must comply from the very next interaction.

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Authors: Harsh Deshpande, Kushal Chawla, Sangwoo Cho, William Campbell
Released: 2026-06-08 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because RECAP: Regression Evaluation for Continual Adaptation of Prompts overlaps with 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)", clean result "Only continuous soft prefixes hit both EM axes at once on Qwen-2.5-7B-Instruct: discrete prompt searches split between the alignment objective and the distributional objective, and both discretizations of the soft prefix collapse (MODERATE confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)". Matching terms: under, eval, line, test, model, absent. Source: arxiv cs.LG (Machine Learning).
arXiv: 2606.06698

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