HeyHomees Lab Notes · No. 9 · ByteDance · Published October 26, 2026
By HeyHomees Newsroom ·
In 30 seconds
- RSIHub provides a file-based framework that tracks every candidate’s lineage and scores
- It structures experiments into a seven-phase loop with nine operator stages, five required and four optional
- In the authors' evaluation the biggest pass@1 improvement was 13.5 percentage points
What is it?
RSIHub is an open-source framework for building, comparing, and extending agent-evolution methods on shared infrastructure. It lets researchers focus on evolution policies while keeping evaluation separate and results tied to candidates and conditions
How does it work?
Every recipe composes the same loop: select → rollout → analyze → mutate → guardrail → evaluate → absorb. Operators plug into nine named stages, five of which are required (select, rollout, mutate, gate, record) and four optional (analyze, validate, novelty, reflect). The framework owns the guardrail, evaluate, and parts of the loop, while recipes control the other phases
What does it need to run?
RSIHub runs each trial on Harbor, which provides container execution, trajectory capture, and per-task verification. Specific hardware or software requirements are not listed in the sources
By the numbers
- overall pass@1 gain: 13.5 percentage points
- loop phases: 7
- named operator stages: 9
- required stages: 5
- optional stages: 4
- paper acceptance month: 2026-10
The honest read
The reported 13.5 percentage-point pass@1 gain comes from the authors' own experiments on specific benchmarks (MiniSWE, Codex, Terminal Bench 2, τ³ Banking) under fixed model and evaluator configurations, so it does not demonstrate general performance across all tasks or models. The figures reflect internal evaluations; no external benchmarks or independent replications are provided. RSIHub’s value lies in its reproducible candidate lineage and shared infrastructure, but the sources do not disclose hardware requirements, licensing terms, or download size, limiting practical deployment information.
What we don't know yet
- Exact hardware or compute resources needed to run the framework
- The software license governing the code
- The download size or model parameter counts
Sources
- Paper (arXiv abstract) (primary)
- Code, GitHub
Researched and drafted with AI from the sources above; every figure is checked against them by code before it is published, and a line that fails is dropped.