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Paper Citation Record · LEDGER

Visualizing Loss Functions as Topological Landscape Profiles

As of 13 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2411.12136.

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

pith.paper-citation-record.v1
2411.12136 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:56:29.110415Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3def46d4-1292-4308-8fc6-0a60c54d7457 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Visualizing Loss Functions as Topological Landscape Profiles Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.100709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.100709Z digest=sha256:435f4a735947073a1b9800218c7ab42331d7adf0ba73a4e3d5ff316f9820b2a4

Observation 574b9102-28db-4e6b-baf6-4a79761df884 · outbound

This paper cites Evaluating Loss Landscapes from a Topology Perspective.

Visualizing Loss Functions as Topological Landscape Profiles Evaluating Loss Landscapes from a Topology Perspective

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-12T17:56:29.171140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T17:56:29.105379Z digest=sha256:0c528504c556162cd43da344cd2e5d76b610d3709225a913bff1a97d53071ec9

Observation b4f11cbc-2315-42ae-bfd1-4c0b10c50148 · outbound

This paper cites Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data.

Visualizing Loss Functions as Topological Landscape Profiles Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.110415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.110415Z digest=sha256:a895c63005c20f086be80fa83ebdcbcb235683de9f8a08eef268f2cfe4b00c70

Observation 68c4a537-4be2-43a7-b50b-124378ad1b97 · outbound

This paper cites Deep Model Merging: The Sister of Neural Network Interpretability -- A Survey.

Visualizing Loss Functions as Topological Landscape Profiles Deep Model Merging: The Sister of Neural Network Interpretability -- A Survey

Reference 1992

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.069253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.069253Z digest=sha256:8b5f7719fd69b64050ebe3e77ac9c30bb2d5049bcfe7c1f7d7d296ed5fddf93c

Observation 131c9ef2-66ab-418e-bb13-0c7c758590c0 · outbound

This paper cites Qualitatively characterizing neural network optimization problems.

Visualizing Loss Functions as Topological Landscape Profiles Qualitatively characterizing neural network optimization problems

Reference 2011

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.060027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.060027Z digest=sha256:db3cfe5c1c6a9a6b0cf0a528700c7dee378ca58c5669e5580887218a10b141e9

Observation 0e7640fb-138c-427e-ac0f-416a3109283f · outbound

This paper cites Challenges in Training PINNs: A Loss Landscape Perspective.

Visualizing Loss Functions as Topological Landscape Profiles Challenges in Training PINNs: A Loss Landscape Perspective

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.090140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.090140Z digest=sha256:9f60b6abda366eeaf457e1a11ee7fad25a5fca148deebf1c0e0739888cdd81f7

Observation c929ab59-8b31-4642-a55b-d1ceb4ce58b8 · outbound

This paper cites Cats and dogs.

Visualizing Loss Functions as Topological Landscape Profiles Cats and dogs

Reference 2013

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T17:56:29.325911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T17:56:29.085349Z digest=sha256:7dabab483fcf70020ca446b101f348c0f30174f9976148613c1079808bea60ec

Observation b3b2d976-42f5-46af-9c8b-caa1d1fccd44 · outbound

This paper cites An empirical analysis of the optimization of deep network loss surfaces.

Visualizing Loss Functions as Topological Landscape Profiles An empirical analysis of the optimization of deep network loss surfaces

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.064432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.064432Z digest=sha256:5be11c2d432b6ed13a89d1e07755bcee35e8857161c08824a6b285d7cc79e364

Observation e36fc0f0-f0d2-478f-9ce2-04a19d71d886 · outbound

This paper cites Adversarial Machine Learning at Scale.

Visualizing Loss Functions as Topological Landscape Profiles Adversarial Machine Learning at Scale

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.074844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.074844Z digest=sha256:6e4e2f58864a2952d52386c1161fd257a3d8d9d9408b47d2db00e1926f958c38

Observation 8535f33a-3b3a-4cdc-9721-fba3e00f96ef · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Visualizing Loss Functions as Topological Landscape Profiles RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.080194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.080194Z digest=sha256:8c4ee402d334aefdc51680eb26c35ca3561d31126781f7f3119475fb457b11b0

Observation da27c138-f609-4250-862c-c4836b3ea33e · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Visualizing Loss Functions as Topological Landscape Profiles BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.055193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.055193Z digest=sha256:4418bdaaeaea6f7db90953fbe1f59eaba153fab1ec7498eab2cf22cd0374d08c

Observation c29e08b4-e138-4371-98df-ef6c99f9ab10 · outbound

This paper cites Mitigating Memorization In Language Models.

Visualizing Loss Functions as Topological Landscape Profiles Mitigating Memorization In Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-12T17:56:29.095615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:56:29.095615Z digest=sha256:2da24ca83a305a7d3e9fefc9aae6b2490d196ec1904a8b8faaceacd4d80f2c0a

Pith citing papers

No inbound Pith citation observations are available.