CodeSync: Multi-Agent System for Programming Assistance and Deterministic Thinking
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Large language models (LLMs) have transformed programming and software development, but their non-deterministic nature poses challenges to reproducible program synthesis. This paper proposes a multi-agent system, CodeSync, designed to align LLMs with human-like reasoning by employing a facilitator agent to coordinate tasks, alongside sub-agents responsible for thinking, planning, execution, validation, and evaluation. Utilizing strict decoding and robust reasoning validation, CodeSync emulates human cognitive processes-receiving a cue, devising a plan, breaking it into steps, adapting based on outcomes, and iterating toward the goal. This collaborative architecture not only outperforms existing multi-agent systems but also excels with open-source models, as demonstrated by CodeSync's impressive scores of 87.4% on the HumanEval benchmark and 91.2% on the MBPP (Mostly Basic Python Problems) benchmark with Llama-4-maverick, thereby eliminating the need for a strong reasoning model within the architecture.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it