Paper Citation Record · LEDGER

Robust Invariant Representation Learning by Distribution Extrapolation

As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2505.16126.

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

pith.paper-citation-record.v1
2505.16126 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:15:43.961516Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T06:56:05.310135Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:26:45.996326Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy1
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d24c3d09-f9e1-4dcc-80bc-91d78e9a4908 · outbound

This paper cites Invariant Risk Minimization Games.

Robust Invariant Representation Learning by Distribution Extrapolation Invariant Risk Minimization Games

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.871823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ab95e93-9f95-4585-bad4-e873d43c4fab · outbound

This paper cites Invariant Risk Minimization.

Robust Invariant Representation Learning by Distribution Extrapolation Invariant Risk Minimization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.886549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 977d81d6-8fa3-4385-89b6-e0dd11d36e7c · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

Robust Invariant Representation Learning by Distribution Extrapolation Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.929345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90b1bb96-9272-44dc-8cc4-743e7b9aeda0 · outbound

This paper cites an unresolved cited work.

Robust Invariant Representation Learning by Distribution Extrapolation Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:15:44.503565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fdf68f7e-7bba-45f3-915c-dd1fcb3c612d · outbound

This paper cites an unresolved cited work.

Robust Invariant Representation Learning by Distribution Extrapolation Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:15:44.481291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6b0304dd-d2c3-4978-b1de-c63f08001859 · outbound

This paper cites test-domain validation set.

Robust Invariant Representation Learning by Distribution Extrapolation test-domain validation set

Reference 224

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:15:44.434735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a1f1c4ef-cc3e-487d-a309-dc5655ca3c9f · outbound

This paper cites Out-of-Distribution Generalization via Risk Extrapolation (REx).

Robust Invariant Representation Learning by Distribution Extrapolation Out-of-Distribution Generalization via Risk Extrapolation (REx)

Reference 1991

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.916798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 875dcf57-1c49-46fa-81ce-1d28b5d9d79f · outbound

This paper cites Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.

Robust Invariant Representation Learning by Distribution Extrapolation Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.896239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a73c5a0-cc0c-4f57-be1d-0a89fc38d80e · outbound

This paper cites In Search of Lost Domain Generalization.

Robust Invariant Representation Learning by Distribution Extrapolation In Search of Lost Domain Generalization

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.910367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f843a123-1de4-4705-8307-bd94209d0a86 · outbound

This paper cites The Effectiveness of Data Augmentation in Image Classification using Deep Learning.

Robust Invariant Representation Learning by Distribution Extrapolation The Effectiveness of Data Augmentation in Image Classification using Deep Learning

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.922723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7f21376-1be8-4057-a5e2-5858b60736b7 · outbound

This paper cites Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.

Robust Invariant Representation Learning by Distribution Extrapolation Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.880306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a431c7f-b8c0-4a50-8653-2565ebf2ed2e · outbound

This paper cites doi: 10.1016/j.engappai.2022.105151.

Robust Invariant Representation Learning by Distribution Extrapolation doi: 10.1016/j.engappai.2022.105151

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.903951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3dbffcb-24fb-4205-ad80-b67635e6353c · outbound

This paper cites What Is Missing in IRM Training and Evaluation? Challenges and Solutions.

Robust Invariant Representation Learning by Distribution Extrapolation What Is Missing in IRM Training and Evaluation? Challenges and Solutions

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T15:15:44.117357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation ec4a2efb-66c7-4967-9965-d93b878e28fe · inbound

Invariant Gradient Alignment for Robust Reasoning Distillation cites this paper.

Invariant Gradient Alignment for Robust Reasoning Distillation Robust Invariant Representation Learning by Distribution Extrapolation

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:26:45.997887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.