$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
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Page Freshness
Signal Canvas proof surface
Canonical route: /signal-canvas/r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reduction
- Proof freshness
- fresh
- Proof status
- unverified
- Display score
- 6/10
- Last proof check
- 2026-04-22
- Score updated
- 2026-04-22
- Score fresh until
- 2026-05-22
- References
- 0
- Source count
- 3
- Coverage
- 50%
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
Canonical ID r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reduction | Route /signal-canvas/r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reduction
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reductionMCP example
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}Evidence Receipt
Route status: buildingClaims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: $R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
PDF: https://arxiv.org/pdf/2604.18995v1
Source count: 3
Coverage: 50%
Last proof check: 2026-04-22T02:15:23.327Z
Signal Canvas receipt window
Watch and verify: $R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
/buildability/r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reduction
Subject: $R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
Verdict
Watch
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Time to first demo
Insufficient data
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Compute envelope
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Evidence ids
Receipt path
/buildability/r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reduction
Paper ref
r-2-dllm-accelerating-diffusion-large-language-models-via-spatio-temporal-redundancy-reduction
arXiv id
2604.18995
Freshness
Generated at
2026-04-22T02:15:23.327Z
Evidence freshness
fresh
Last verification
2026-04-22T02:15:23.327Z
Sources
3
References
0
Coverage
50%
Hash state
Lineage hash
146237c9fabb97bb438b73da347fd3d41e1caacb16955e41bd8cf2ea07bfc91f
Canonical opportunity-kernel lineage hash.
Signature state
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.
Blockers
- Missing: repo_url
- Missing: references
- Missing: proof_status
- Unknown: proof verification has not been recorded yet
Pending verification refs / 3 sources / Verification pending
repo_url
references
Paper Conversation
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$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
Canonical Paper Receipt
Last verification: 2026-04-22T02:15:23.327ZFreshness: fresh
Proof: unverified
Repo: missing
References: 0
Sources: 3
Coverage: 50%
- - repo_url
- - references
- - proof_status
- - proof verification has not been recorded yet
Preparing verified analysis
Dimensions overall score 6.0
GitHub Code Pulse
No public code linked for this paper yet.
Key claims
Startup potential card
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