Morning Edition · Tuesday, July 28, 2026Published at 1:47 AM EDT · New York
CORVUS Attacks the Bloated Context Trails That Slow LLM Coding Agents
The method targets the append-only trajectory that accumulates reasoning, tool calls, and results, aiming to cut context cost without losing the information an agent needs.
A paper titled CORVUS addresses a concrete problem in large language model (LLM) coding agents. The conventional append-only trajectory concatenates every reasoning step, tool call, and result into an ever-growing context. That design ties…
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Part of a tracked trend
The Inference-Cost Efficiency Race
Techniques that cut tokens generated and KV-cache memory per query will keep compressing the marginal cost of serving reasoning models, making inference efficiency a recurring competitive axis alongside raw capability.
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