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arXiv · 2605.11051

On Problems of Implicit Context Compression for Software Engineering Agents

Kirill Gelvan·Igor Slinko·Felix Steinbauer·Egor Bogomolov·Florian Kofler·Yaroslav Zharov
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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.

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Kirill Gelvan, Igor Slinko, Felix Steinbauer, Egor Bogomolov, Florian Kofler, Yaroslav Zharov. 2026-05-11. On Problems of Implicit Context Compression for Software Engineering Agents. https://arxiv.org/abs/2605.11051

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