Evidence Receipt. Related Resources.
SAGE: Multi-Agent Self-Evolution for LLM Reasoning
Compared to this week’s papers
Verification pending
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Page Freshness
Signal Canvas proof surface
Canonical route: /signal-canvas/sage-multi-agent-self-evolution-for-llm-reasoning
- Proof freshness
- stale
- Proof status
- unverified
- Display score
- 8/10
- Last proof check
- 2026-04-02
- Score updated
- 2026-04-02
- Score fresh until
- 2026-05-02
- References
- 0
- Source count
- 0
- Coverage
- 17%
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
SAGE: Multi-Agent Self-Evolution for LLM Reasoning
Canonical ID sage-multi-agent-self-evolution-for-llm-reasoning | Route /signal-canvas/sage-multi-agent-self-evolution-for-llm-reasoning
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/sage-multi-agent-self-evolution-for-llm-reasoningMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "sage-multi-agent-self-evolution-for-llm-reasoning",
"query_text": "Summarize SAGE: Multi-Agent Self-Evolution for LLM Reasoning"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "SAGE: Multi-Agent Self-Evolution for LLM Reasoning",
"normalized_query": "2603.15255",
"route": "/signal-canvas/sage-multi-agent-self-evolution-for-llm-reasoning",
"paper_ref": "sage-multi-agent-self-evolution-for-llm-reasoning",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Preparing verified analysis
Dimensions overall score 8.0
GitHub Code Pulse
No public code linked for this paper yet.
Claim map
- Evidencepartial
improving the Qwen-2.5-7B model by 8.9% on LiveCodeBench
ImplicationpartialExplicitly stated in the abstract with specific numeric results.
Verificationpartialpartial
- Evidencepartial
and 10.7% on OlympiadBench.
ImplicationpartialExplicitly stated in the abstract with specific numeric results.
Verificationpartialpartial
- Evidencepartial
a closed-loop framework where four agents: Challenger, Planner, Solver, and Critic, co-evolve from a shared LLM backbone
ImplicationpartialDirectly stated in the abstract describing the framework components.
Verificationpartialpartial
- Evidencepartial
using only a small seed set.
ImplicationpartialStrongly supported by abstract statement about using 'only a small seed set' and context about reducing human dependency.
Verificationpartialpartial
- Evidencepartial
The Critic scores and filters both generated questions and plans to prevent curriculum drift
ImplicationpartialDirectly stated function of the Critic agent in the abstract.
Verificationpartialpartial
- Evidencepartial
Across mathematics and code-generation benchmarks, SAGE delivers consistent gains across model scales
ImplicationpartialDirectly stated in abstract but without specific numeric evidence for all model scales.
Verificationpartialpartial
- Evidencepartial
whose correctness is determined by external verifiers.
ImplicationpartialExplicitly stated in the abstract and reinforced in caveats.
Verificationpartialpartial
- Evidencepartial
Risk of curriculum drift if the Critic agent fails to maintain quality control
ImplicationpartialExplicitly stated in the caveats section of the analysis.
Verificationpartialpartial
Startup potential card
Related Resources
- Agents(glossary)
