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Paper Citation Record · LEDGER

Is Transfer Learning Necessary for Protein Landscape Prediction?

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2011.03443.

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

pith.paper-citation-record.v1
2011.03443 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:49:54.436215Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:39:41.997875Z

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 9c745e85-d7c6-4eb1-a384-7f9f58541fcd · inbound

EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations cites this paper.

EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations Is Transfer Learning Necessary for Protein Landscape Prediction?

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T14:49:54.436215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:49:54.436215Z digest=sha256:937f035796cb0f9956dce2fa5e5201d133861b5c7d89431c99aa1d3deade3e7d

Observation b25a8d28-ca10-4e31-87dc-5733d663e756 · inbound

ProtCLIP: Function-Informed Protein Multi-Modal Learning cites this paper.

ProtCLIP: Function-Informed Protein Multi-Modal Learning Is Transfer Learning Necessary for Protein Landscape Prediction?

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T23:45:12.221383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:45:12.221383Z digest=sha256:8283a5ad2ab4e9f13df5626a7e5f0054427452b0c19d9c6975021241466c6f92

Observation 05919400-238e-401d-8b22-db4752602a3a · inbound

Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training cites this paper.

Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training Is Transfer Learning Necessary for Protein Landscape Prediction?

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T11:52:19.086609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:52:19.086609Z digest=sha256:3c25c9a47059852fb5c486cd9e8e408ed22bdd2045191d5c2170a626675c1621

Observation c068c3a9-a175-476d-9a38-49567e60483f · inbound

BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language cites this paper.

BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language Is Transfer Learning Necessary for Protein Landscape Prediction?

Reference 110

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:19:44.775269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T11:46:33.957076Z digest=sha256:df830bf5a03212823c0ef9f6f984920c09cd8410a42eb5bbc9e21cb8a507e236

Observation aa8d5112-cb12-4dc1-9afc-2871e9a4a73a · inbound

Enhancing Protein Representation Learning via Manifold Restore Mixing cites this paper.

Enhancing Protein Representation Learning via Manifold Restore Mixing Is Transfer Learning Necessary for Protein Landscape Prediction?

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:39:41.999231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T11:17:06.033965Z digest=sha256:4df6ec51c914a7e4311043ccd5a608d6e72dadb449a191e32400e42120636b3f