Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Route this paper proof surface into REST, MCP, or developer workflows while preserving the same evidence receipt and related-resource context.
Page Freshness
Canonical route: /signal-canvas/infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain | Route /signal-canvas/infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/infomem-training-long-context-memory-agents-with-answer-conditioned-information-gainMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain",
"query_text": "Summarize InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain",
"normalized_query": "2606.03329",
"route": "/signal-canvas/infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain",
"paper_ref": "infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain
PDF: https://arxiv.org/pdf/2606.03329v1
Repository: https://github.com/GenSouKa1/InfoMem
Source count: 4
Coverage: 83%
Last proof check: 2026-06-03T20:32:59.739Z
Signal Canvas receipt window
/buildability/infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain
Subject: InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain
Verdict
Build Now
Preparing verified analysis
Dimensions overall score 7.0
{"file name": "input.pdf", "number of pages": 17, "author": "Tiancheng Han; Yong Li; Wuzhou Yu; Qiaosheng Zhang; Wenqi Shao"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Verdict is Build Now because viability and implementation proof cleared the Wave 1 scaffold thresholds.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain
Paper ref
infomem-training-long-context-memory-agents-with-answer-conditioned-information-gain
arXiv id
2606.03329
Generated at
2026-06-03T20:32:59.739Z
Evidence freshness
fresh
Last verification
2026-06-03T20:32:59.739Z
Sources
4
References
0
Coverage
83%
Lineage hash
2f8df8a4911060340410dc9dab74283c7350f648b2bc4ed706c3465cebc5b2ca
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 4 sources / Verification pending
references