The authors combine Latent Observations, Hard Actions (LOHA) with Anchored Context Distillation (ACD).
Compressing old tool outputs cuts coding-agent context with modest accuracy loss
A hybrid layout preserves recent observations as exact text while encoding older tool outputs as compact learned representations.
Top University
Zhensheng Zou (Peking University) · Guoqing Wang (Peking University) · Dan Hao (Peking University)
Research Digest··2 min read
Zou, Wang and Hao introduce a context scheme for software-engineering agents that compresses older tool observations into soft tokens while retaining the agent’s actions and recent observations as text.
Why this paper
From Peking University · Part of Agent Harness Optimization, now 67 papers
In one line
Older tool observations can be compressed into soft tokens without losing action-critical detail, as long as recent observations and the agent's own turns stay in text.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ✓Reports numbers on named benchmarks (2 benchmarks)
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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