Paper Citation Record · LEDGER

Value Residual Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2410.17897.

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

pith.paper-citation-record.v1
2410.17897 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:36:26.427861Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 55058e80-ee24-4e04-8b99-f1f6d20469a9 · inbound

FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation cites this paper.

FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation Value Residual Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T10:36:26.427861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b36f0623-f6f6-40b5-9f44-4e71f3429530 · inbound

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure cites this paper.

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure Value Residual Learning

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:52:41.251014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 78ec561b-e941-4b70-9877-9853e75da073 · inbound

GaussianGPT: Towards Autoregressive 3D Gaussian Scene Generation cites this paper.

GaussianGPT: Towards Autoregressive 3D Gaussian Scene Generation Value Residual Learning

Reference 77

Resolution: unresolved; no resolver link, observed 2026-07-13T17:23:44.758186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32e9d63e-48bb-4139-acdd-ee023628ca20 · inbound

Beyond N-gram: Data-Aware X-GRAM Extraction for Efficient Embedding Parameter Scaling cites this paper.

Beyond N-gram: Data-Aware X-GRAM Extraction for Efficient Embedding Parameter Scaling Value Residual Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-09T22:29:06.656850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ab086379-102e-4e55-8fe4-9a7347352ca3 · inbound

Most Transformer Modifications Still Do Not Transfer at 1-3B: A 2020-2026 Update to Narang et al. (2021) with Downstream Evaluation and a Noise Floor cites this paper.

Most Transformer Modifications Still Do Not Transfer at 1-3B: A 2020-2026 Update to Narang et al. (2021) with Downstream Evaluation and a Noise Floor Value Residual Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:19:42.065835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a7117e1-d1af-4d8c-9b64-52ceba65b84a · inbound

Do Value Vectors in Deep Layers Need Context from the Residual Stream? cites this paper.

Do Value Vectors in Deep Layers Need Context from the Residual Stream? Value Residual Learning

Reference 111

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:16:23.491814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 69a0b1ed-560f-4027-b8cd-135188bc46dd · inbound

Do Value Vectors in Deep Layers Need Context from the Residual Stream? cites this paper.

Do Value Vectors in Deep Layers Need Context from the Residual Stream? Value Residual Learning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T12:41:24.585284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa698068-f787-4388-8f47-f02c601ac28e · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers Value Residual Learning

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T23:32:46.740876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6182b72e-cb89-40e0-853e-931e813d968e · inbound

Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty cites this paper.

Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty Value Residual Learning

Reference 73

Resolution: malformed identifier; arxiv_id, observed 2026-07-04T18:40:02.639402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e3332ab5-80cd-4106-95bb-0ad3239f7e58 · inbound

Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty cites this paper.

Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty Value Residual Learning

Reference 74

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T21:17:23.795739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ce59e45b-da86-4834-964c-c04b5a410923 · inbound

Scaling Point-in-Time Language Models cites this paper.

Scaling Point-in-Time Language Models Value Residual Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T15:39:41.279102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bc3ab78-2a7c-4c0d-8524-7b9e5213dc6b · inbound

Role-Decoupled Attention Residuals: Separating Matching and Content Retrieval Across Depth cites this paper.

Role-Decoupled Attention Residuals: Separating Matching and Content Retrieval Across Depth Value Residual Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T00:37:19.608145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.