Failure-Aware Long-Form Translation: Design and Implementation of a Recoverable LLM Translation System
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Computer Science > Computation and Language
Title:Failure-Aware Long-Form Translation: Design and Implementation of a Recoverable LLM Translation System
Abstract:A long-form translation request can succeed at the API layer and still produce an unusable result. The output may be empty, truncated, filtered, dominated by source or prompt material, or interrupted after producing text worth keeping. This report describes a recovery protocol developed for a deployed translation system with heterogeneous inputs and provider APIs. It delays the first visible release behind a 64-character window, validates the assembled output, and uses typed stream events to distinguish replacement from continuation. Interrupted work is retained only when a paragraph or sentence prefix can be re-derived from the source. Further attempts follow a stable model order and a shared deadline before entering a provenance-marked fallback path. A sanitized companion artifact implements the protocol and passes 38 public tests. Its fixed cases reproduce all 14 configured completion labels, contain four early-invalid prefixes before any of their 235 characters become visible, retain 31 boundary-safe characters across four interrupted streams, and satisfy the attempt, event, and provenance rules in two end-to-end scenarios. These results are executable checks of the published control flow. Translation quality and detector performance on naturally occurring outputs require a different evaluation.
| Comments: | 9 pages, 2 figures. A sanitized reference implementation is included as ancillary material |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2608.09187 [cs.CL] |
| (or arXiv:2608.09187v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.09187
arXiv-issued DOI via DataCite (pending registration)
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Ancillary files (details):
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- README.md
- evaluation-results.json
- evaluation_cases.json
- failure_aware_translation/__init__.py
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