Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
Use This Via API or MCP
Signal Canvas is the citation-first public layer for turning one paper into a structured commercialization narrative. Use it to hand off into REST, MCP, Build Loop, and launch-pack execution without losing source lineage.
Use This Via API or MCP
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/f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data
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 f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data | Route /signal-canvas/f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-dataMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data",
"query_text": "Summarize $f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data",
"normalized_query": "2605.15417",
"route": "/signal-canvas/f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data",
"paper_ref": "f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 0
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: $f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
PDF: https://arxiv.org/pdf/2605.15417v1
Source count: 3
Coverage: 50%
Last proof check: 2026-05-18T20:31:45.547Z
Signal Canvas receipt window
/buildability/f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data
Subject: $f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
Verdict
Watch
Preparing verified analysis
Dimensions overall score 5.0
No public code linked for this paper yet.
CLAIM MAP
No public claim map is available for this paper yet.
Use an AI coding agent to implement this research.
Lightweight coding agent in your terminal.
Agentic coding tool for terminal workflows.
AI agent mindset installer and workflow scaffolder.
AI-first code editor built on VS Code.
Free, open-source editor by Microsoft.
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
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/f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data
Paper ref
f-trajectory-balance-a-loss-family-for-tuning-gflownets-generative-models-and-llms-with-off-and-on-policy-data
arXiv id
2605.15417
Generated at
2026-05-18T20:31:45.547Z
Evidence freshness
stale
Last verification
2026-05-18T20:31:45.547Z
Sources
3
References
0
Coverage
50%
Lineage hash
8409524eba2d7972c2e31b118bf293e3083d6252f5b22461f02c881f7095c2bd
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 / 3 sources / Verification pending
repo_url
references