RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents

RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents

stale

Proof freshness: stale
Proof status: unverified
Display score: 4/10
Last proof check: 2026-05-18
Score updated: 2026-05-18
Score fresh until: 2026-06-17
References: 0
Source count: 4
Coverage: 67%

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 recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents | Route /signal-canvas/recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents",
    "query_text": "Summarize RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents",
  "normalized_query": "2605.16045",
  "route": "/signal-canvas/recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents",
  "paper_ref": "recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents",
  "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: RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents

PDF: https://arxiv.org/pdf/2605.16045v1

Repository: https://github.com/CaiusDai/RecMem

Source count: 4

Coverage: 67%

Last proof check: 2026-05-18T20:32:13.331Z

Signal Canvas receipt window

Not build-ready: RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents

/buildability/recmem-recurrence-based-memory-consolidation-for-efficient-and-effective-long-running-llm-agents

Ignoreblocked

Subject: RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents

Verdict

RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents

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