Pith. sign in

Paper Citation Record · LEDGER

Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.11957.

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

pith.paper-citation-record.v1
2305.11957 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:22:23.554782Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T10:22:33.147873Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b08df21c-8707-4c35-b996-5b8f0f760751 · inbound

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse cites this paper.

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-16T10:22:23.554782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:22:23.554782Z digest=sha256:ddb38d7406263e3a7bb6112cc15b2f762fcb70af50156485af2c2668a290e57c

Observation d84a2f45-d525-4d83-ae92-fade73376c76 · inbound

Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension cites this paper.

Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:22:33.151143Z

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.

source=pdf_text observed=2026-05-18T10:22:28.096542Z digest=sha256:51cf9008f0d3306c88a68e041fdcc3d54a2bbc5a6f8d59e5590eb508f8614324

Observation c4890556-5acb-4a73-bd05-204d4b003202 · inbound

Optimal Representations for Generalized Contrastive Learning with Imbalanced Datasets cites this paper.

Optimal Representations for Generalized Contrastive Learning with Imbalanced Datasets Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method

Reference 110

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:32:06.175096Z

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.

source=arxiv_source observed=2026-05-13T02:31:56.483055Z digest=sha256:29318852580665fb61615fc25925869af88c89cd50374b8993cd8e9cccfc66b1