AI & ML
Call-Level Revision Contracts for LLM-Authored Workflows
arXiv cs.SE0 views
arXiv:2611.06967v1 Announce Type: new Abstract: Durable execution engines replay a recorded history and do not compare activity payloads. When a model repairs a workflow that failed partway through, it must either pay again for calls that succeeded or accept a recorded result whose payload changed. We define a revision contract for workflows whose orchestration code is written by a model. Each capability call carries a structural identity built from its callsite, its fanout position, and its occurrence count, and the identity stays stable under rewrites that leave the call in place, so committed identities form a frozen prefix. The frozen unit is the call expression, and the surrounding code stays writable. A static gate rejects a rewrite that would change a committed call before a container starts. A runtime digest stops a changed payload at a committed identity, and an occurrence ledger names a repeated paid payload. Under three assumptions, a candidate the gate accepts replays every committed call it invokes, executes only new work, and reports the identities it skips. No local identity is both relocation-invariant and free of wrong reuse, so callsite identity turns a relocation into a pre-spend stop. On media workflows, 22 gate-passed repairs replay 258 committed identities with no duplicate, and a live six-way fanout makes seven paid calls instead of twelve. A 12-task customer-support study applies the same identity, replay, and boundary checks on two models.
Source:https://arxiv.org/abs/2611.06967PreviousWhen Can Self-Play Fix a False Belief? Answer Keys, Pass Bands and Replacement Rules in an Execution-Grounded LoopNextAn LLM-Orchestrated Neuro-Symbolic Framework for Verifying Diagnostic Signal Reachability in Electronic Systems
Related posts
We tested memory retrieval on DolphinBench. Plain keyword search exposed our own regression.
0dev.to
Global stocks tumble as AI panic grips markets after Democrats' midterm success
0Hacker News
Turning GPT GIFs into a cat film: what smoothing fixed, and what it didn’t
0dev.to AI
I Stopped Writing a New API Client for Every AI Model
0dev.to AI
The smallest feature we shipped started a war (the friendly kind)
0dev.to AI
Authorized is not proven: what the FDA's AI device list does and doesn't tell you
0dev.to AI