Paper Citation Record · LEDGER

Progressive Depth Up-scaling via Optimal Transport

As of 20 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 2 inbound Pith citation observations for arXiv:2508.08011.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.08011 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:47:23.819767Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:52:06.128962Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-16T22:03:36.056391Z

Reference resolution

5 of 5 outbound references displayed

verified exact0
verified fuzzy0
unresolved4
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6dc6ed43-6b12-4690-ae43-df7f0f8bfae5 · outbound

This paper cites Llama-3-Nanda-10B-Chat: An Open Generative Large Language Model for Hindi.

Progressive Depth Up-scaling via Optimal Transport Llama-3-Nanda-10B-Chat: An Open Generative Large Language Model for Hindi

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T21:47:23.570483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ba179b-6f77-4264-9e2d-2a3ea654519a · outbound

This paper cites The Llama 3 Herd of Models.

Progressive Depth Up-scaling via Optimal Transport The Llama 3 Herd of Models

Reference 2019

Resolution: malformed identifier; no resolver link, observed 2026-08-05T21:47:23.693492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a209826c-7a5a-4844-8650-ae2af4a1eb5f · outbound

This paper cites an unresolved cited work.

Progressive Depth Up-scaling via Optimal Transport Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-05T21:47:23.970538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 69aba07d-1ebd-47ff-bc73-3ab3df3f82e4 · outbound

This paper cites The Computational Limits of Deep Learning.

Progressive Depth Up-scaling via Optimal Transport The Computational Limits of Deep Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T21:47:23.819767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c909d5c-ca11-4ac9-a960-b88595d1d454 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Progressive Depth Up-scaling via Optimal Transport Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2936

Resolution: unresolved; no resolver link, observed 2026-08-05T21:47:23.626269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation f24fcd5f-35fa-4a79-97a3-5dc398e9da13 · inbound

MIDUS: Memory-Infused Depth Up-Scaling cites this paper.

MIDUS: Memory-Infused Depth Up-Scaling Progressive Depth Up-scaling via Optimal Transport

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:03:36.058583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation adb721f3-7838-4d0b-b54b-cb5e3b9e4a11 · inbound

StateBridge: Training-free Hidden-state Alignment for Latent Communication in LLM Multi-Agent Systems cites this paper.

StateBridge: Training-free Hidden-state Alignment for Latent Communication in LLM Multi-Agent Systems Progressive Depth Up-scaling via Optimal Transport

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T13:52:06.128962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.