Dynamic Dual-Granularity Skill Bank for Agentic RL

Dynamic Dual-Granularity Skill Bank for Agentic RL | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/dynamic-dual-granularity-skill-bank-for-agentic-rl

stale

Proof freshness: stale
Proof status: unverified
Display score: 4/10
Last proof check: 2026-03-31
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 12
Source count: 3
Coverage: 50%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID dynamic-dual-granularity-skill-bank-for-agentic-rl | Route /signal-canvas/dynamic-dual-granularity-skill-bank-for-agentic-rl

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/dynamic-dual-granularity-skill-bank-for-agentic-rl

MCP example

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    "mode": "paper",
    "paper_ref": "dynamic-dual-granularity-skill-bank-for-agentic-rl",
    "query_text": "Summarize Dynamic Dual-Granularity Skill Bank for Agentic RL"
  }
}

source_context

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  "query": "Dynamic Dual-Granularity Skill Bank for Agentic RL",
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  "paper_ref": "dynamic-dual-granularity-skill-bank-for-agentic-rl",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 8

References: 12

Proof: Verification pending

Freshness state: computing

Source paper: Dynamic Dual-Granularity Skill Bank for Agentic RL

PDF: https://arxiv.org/pdf/2603.28716v1

Source count: 3

Coverage: 50%

Last proof check: 2026-03-31T20:21:25.702Z

Signal Canvas receipt window

Not build-ready: Dynamic Dual-Granularity Skill Bank for Agentic RL

/buildability/dynamic-dual-granularity-skill-bank-for-agentic-rl

Ignoreblocked

Subject: Dynamic Dual-Granularity Skill Bank for Agentic RL

Verdict

Ignore

Verdict is Ignore because current viability and proof state do not clear the buildability gate.

Time to first demo

Insufficient data

No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.

Compute envelope

Structured compute envelope

Insufficient data

No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.

Evidence ids

Preparing verified analysis

GitHub Code Pulse

No public code linked for this paper yet.

Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
D2Skill achieves 10–20 point gains in success rate over skill-free baselines (GRPO)
Implicationpartial
Directly stated in abstract with specific numeric range and supported by results table showing gains of 15.7-18.8 points.
Verificationpartial
partial
Evidencepartial
organizes reusable experience into task skills for high-level guidance and step skills for fine-grained interaction support.
Implicationpartial
Explicitly stated as core method contribution in multiple sections of the paper.
Verificationpartial
partial
Evidencepartial
skills expanded through reflection and maintained via utility-guided retrieval and pruning
Implicationpartial
Directly stated as a core method contribution and described in the framework diagram.
Verificationpartial
partial
Evidencepartial
D2Skill acquires and maintains its skill bank using only training-time experience, while still achieving better performance
Implicationpartial
Explicitly stated comparison with SkillRL method, highlighting D2Skill's advantage.
Verificationpartial
partial
Evidencepartial
D2Skill reaches 92.2 on ALFWorld, nearly matching GRPO trained for longer
Implicationpartial
Specific numeric result stated in the analysis section, though exact context details are limited.
Verificationpartial
partial
Evidencepartial
both dual-granularity skill modeling and dynamic skill maintenance are critical to these gains
Implicationpartial
Directly stated in abstract as conclusion from ablations and analyses.
Verificationpartial
partial
Evidencepartial
performance gap between the two groups is used to construct hindsight signals for policy optimization and skill utility updates
Implicationpartial
Explicitly described as core training mechanism in method section and framework diagram.
Verificationpartial
partial
Evidencepartial
the learned skills exhibit higher utility, transfer across evaluation settings
Implicationpartial
Stated in abstract as finding from analyses, though specific evidence quotes are limited.
Verificationpartial
partial

Author intelligence and commercialization panels stay hidden until the proof receipt is verified, cites at least 3 references, includes at least 2 sources, and clears 50% coverage. The paper narrative and citation surfaces remain public while verification is pending.

Dynamic Dual-Granularity Skill Bank for Agentic RL

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