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  3. Escaping the Context Bottleneck: Active Context Curation for
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Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

Stale7d agoPending verification refs / 3 sources / Verification pending
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Viability
0.0/10

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Verification pending

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Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning

stale
Proof freshness
stale
Proof status
unverified
Display score
6/10
Last proof check
2026-04-14
Score updated
2026-04-14
Score fresh until
2026-05-14
References
0
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

Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

Canonical ID escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning | Route /signal-canvas/escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning",
    "query_text": "Summarize Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning",
  "normalized_query": "2604.11462",
  "route": "/signal-canvas/escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning",
  "paper_ref": "escaping-the-context-bottleneck-active-context-curation-for-llm-agents-via-reinforcement-learning",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 0

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

PDF: https://arxiv.org/pdf/2604.11462v1

Source count: 3

Coverage: 50%

Last proof check: 2026-04-14T16:51:11.855Z

Paper Conversation

Citation-first answers with explicit evidence receipts, disagreement handling, commercialization framing, and next actions.

Paper Mode

Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

Overall score: 6/10
Lineage: b02cb693e5f5…
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Canonical Paper Receipt

Last verification: 2026-04-14T16:51:11.855Z

Freshness: stale

Proof: unverified

Repo: missing

References: 0

Sources: 3

Coverage: 50%

Missingness
  • - repo_url
  • - references
  • - proof_status
Unknowns
  • - proof verification has not been recorded yet

Mode Notes

  • Corpus mode searches the research corpus broadly.
  • Paper mode pins trust state to the canonical paper kernel.
  • Workspace mode blends saved sources, prior evidence queries, and linked papers.

Preparing verified analysis

Dimensions overall score 6.0

GitHub Code Pulse

No public code linked for this paper yet.

Claim map

No public claim map is available for this paper yet.

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.

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