Paper Citation Record · LEDGER

Visualizing Loss Functions as Topological Landscape Profiles

As of 14 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 2026-08-14T06:32:32.682623+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.

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 2026-08-14T06:32:32.682623+00:00.

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.

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.

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.

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.

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 2026-08-14T06:32:32.682623+00:00.

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.

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.

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.

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.

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.

Pith citing papers

No inbound Pith citation observations are available.