A local Llama 3.2 3B model preprocesses multilingual coding prompts via translation and structural rewriting, cutting prompt tokens 34-47% and total tokens up to 18.8% while preserving accuracy on OMH-Polyglot benchmark.
Compressing code context for llm-based issue resolution
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A survey that organizes existing work on LLM-based agents around code as the central harness, structured in three layers of interfaces, mechanisms, and multi-agent scaling, with applications across domains and listed open challenges.
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Code as Agent Harness
A survey that organizes existing work on LLM-based agents around code as the central harness, structured in three layers of interfaces, mechanisms, and multi-agent scaling, with applications across domains and listed open challenges.