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On Problems of Implicit Context Compression for Software Engineering Agents

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Computer Science > Software Engineering

arXiv:2605.11051 (cs)
[Submitted on 11 May 2026]

Title:On Problems of Implicit Context Compression for Software Engineering Agents

View a PDF of the paper titled On Problems of Implicit Context Compression for Software Engineering Agents, by Kirill Gelvan and 5 other authors
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Abstract:LLM-based Software Engineering agents face a critical bottleneck: context length limitations cause failures on complex, long-horizon tasks. One promising solution is to encode context as continuous embeddings rather than discrete tokens, enabling denser information storage. We apply the recently proposed In-Context Autoencoder for this purpose. While the method performs well on single-shot common-knowledge and code-understanding tasks, our experiments demonstrate that it fails on multi-step agentic coding tasks. In this paper, we explore this phenomenon and discuss possible factors contributing to this failure.
Subjects: Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2605.11051 [cs.SE]
  (or arXiv:2605.11051v1 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2605.11051
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Igor Slinko [view email]
[v1] Mon, 11 May 2026 14:47:07 UTC (930 KB)
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