Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
Use This Via API or MCP
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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/packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference
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 packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference | Route /signal-canvas/packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inferenceMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference",
"query_text": "Summarize PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference",
"normalized_query": "2603.25730",
"route": "/signal-canvas/packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference",
"paper_ref": "packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 8
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference
PDF: https://arxiv.org/pdf/2603.25730v1
Repository: https://github.com/ShandaAI/PackForcing
Source count: Pending verification
Coverage: 50%
Last proof check: 2026-03-27T20:30:26.644Z
Signal Canvas receipt window
/buildability/packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference
Subject: PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference
Verdict
Preparing verified analysis
Dimensions overall score 8.0
Mid tokens, which achieve a massive spatiotemporal compression (32x token reduction) via a dual-branch network fusing progressive 3D convolutions with low-resolution VAE re-encoding
Directly stated in abstract with specific numeric compression factor
partial
PackForcing can generate coherent 2-minute, 832x480 videos at 16 FPS on a single H200 GPU
Directly stated in abstract with specific technical specifications
partial
It achieves a bounded KV cache of just 4 GB
Directly stated in abstract with specific memory measurement
partial
enables a remarkable 24x temporal extrapolation (5s to 120s)
Directly stated in abstract with specific extrapolation factor
partial
Extensive results on VBench demonstrate state-of-the-art temporal consistency (26.07) and dynamic degree (56.25)
Directly stated in abstract with specific benchmark scores
partial
operating effectively either zero-shot or trained on merely 5-second clips
Directly stated in abstract but requires inference that 'short-video supervision' refers to 5-second clips
partial
we present PackForcing, a unified framework that efficiently manages the generation history through a novel three-partition KV-cache strategy
Directly stated in abstract and analysis with clear technical description
partial
The technology might face challenges in generalizing to all types of video content, especially highly complex or specialized genres
Stated in analysis caveats but presented as potential limitation rather than demonstrated finding
partial
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Xiaofeng Mao
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Shaohao Rui
Alaya Studio, Shanda AI Research Tokyo, Shanghai Innovation Institute
Kaining Ying
Alaya Studio, Shanda AI Research Tokyo, Fudan University
Bo Zheng
Alaya Studio, Shanda AI Research Tokyo
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Build Now
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/packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference
Paper ref
packforcing-short-video-training-suffices-for-long-video-sampling-and-long-context-inference
arXiv id
2603.25730
Generated at
2026-03-27T20:30:26.644Z
Evidence freshness
stale
Last verification
2026-03-27T20:30:26.644Z
Sources
0
References
0
Coverage
50%
Lineage hash
e226df83ab3cf3c932581887cce61ced5bb92bfb466aa69e8fa1290c3871d308
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.
Verification pending / evidence receipt incomplete
references
distribution_readiness_scores