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Paper Citation Record · LEDGER

Spurious Feature Diversification Improves Out-of-distribution Generalization

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.17230.

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

pith.paper-citation-record.v1
2309.17230 v2

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 2026-08-23T06:30:58.430688+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:55:13.860473Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T01:03:57.922805Z

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 d9f3d4ec-cfa5-40b9-8788-4841e330076c · inbound

Video-Text Dataset Construction from Multi-AI Feedback: Promoting Weak-to-Strong Preference Learning for Video Large Language Models cites this paper.

Video-Text Dataset Construction from Multi-AI Feedback: Promoting Weak-to-Strong Preference Learning for Video Large Language Models Spurious Feature Diversification Improves Out-of-distribution Generalization

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T13:31:10.736454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:31:10.736454Z digest=sha256:d945b6f95d3f4c0a619d8c675997c46d03cb3258e6715bfeab8e58ffa2863ec2

Observation 96fbe0d2-f1e5-4ee2-a6ba-f0f65aecc7c0 · inbound

Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods cites this paper.

Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods Spurious Feature Diversification Improves Out-of-distribution Generalization

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T11:40:09.899709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:40:09.899709Z digest=sha256:2928c41709f6a4ac7813ad056b2c75ac101ac492427499be165fce91201139c3

Observation 6d2f5151-84d7-480d-9bb1-bac74c918a94 · inbound

Learning Causality for Modern Machine Learning cites this paper.

Learning Causality for Modern Machine Learning Spurious Feature Diversification Improves Out-of-distribution Generalization

Reference 40

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T01:03:58.044151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T01:03:50.050508Z digest=sha256:af3fb7b4484b44afc889cd0a3755790963d6bcf9e14c8c4569f210a1abe74abb

Observation ef7c91a6-7714-45f7-84c4-ec3ad290b026 · inbound

SDD: Self-Degraded Defense against Malicious Fine-tuning cites this paper.

SDD: Self-Degraded Defense against Malicious Fine-tuning Spurious Feature Diversification Improves Out-of-distribution Generalization

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T17:55:13.860473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:55:13.860473Z digest=sha256:c99dba562d4aedaf6df88b39b9cf772b6cbb553485c0b3b0aa47cd7282324b31

Observation aa981351-cdd1-4906-8b72-001ca6833084 · inbound

Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling cites this paper.

Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling Spurious Feature Diversification Improves Out-of-distribution Generalization

Reference 281

Resolution
unresolved
no resolver link, observed 2026-08-03T01:06:24.853310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:06:24.853310Z digest=sha256:20d65039a4e41866b95a50d9ee341ec6ac050b062e26d74fba0f39b4b60d86f3