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Paper Citation Record · LEDGER

Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.00667.

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

pith.paper-citation-record.v1
2402.00667 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 2026-08-06T06:34:29.942622+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T05:09:00.865375Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T12:33:45.173843Z

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 3474beb3-fef3-4f43-831f-ad399b6bce62 · inbound

Generalizable Video Quality Assessment via Weak-to-Strong Learning cites this paper.

Generalizable Video Quality Assessment via Weak-to-Strong Learning Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-22T16:11:45.638099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-22T16:10:32.702472Z digest=sha256:3751608d7c523cf2096b9fe8fd16c3f9e714d5b3eebc30b7a0f732ad8b51f3a1

Observation 3e24bd2b-863c-4e14-8ead-24717e341e0c · inbound

On the Blessing of Pre-training in Weak-to-Strong Generalization cites this paper.

On the Blessing of Pre-training in Weak-to-Strong Generalization Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning

Reference 118

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T18:36:08.662352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-08T14:59:19.883399Z digest=sha256:5933311fe47f5741362d33fa7d78e82093c0f0a59d81599c3e1d851a27d2b04f

Observation 4f63907e-7ca7-41bc-9f67-d9d60302dff0 · inbound

Weak-to-Strong Generalization via Direct On-Policy Distillation cites this paper.

Weak-to-Strong Generalization via Direct On-Policy Distillation Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning

Reference 95

Resolution
verified exact
local_arxiv, observed 2026-07-07T12:33:45.175341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-07T12:31:42.224094Z digest=sha256:c3aebb46ebd58ae0117a48f4a67877e19a60858c4142ea344dc7e2a70b32a6c0

Observation f24e9d31-ee6b-4b32-8a90-579283d1a286 · inbound

Weak-to-Strong Generalization via Direct On-Policy Distillation cites this paper.

Weak-to-Strong Generalization via Direct On-Policy Distillation Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning

Reference 91

Resolution
unresolved
no resolver link, observed 2026-07-11T07:01:56.628017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T07:01:56.628017Z digest=sha256:0fa7587181b300007ab7b66d6284183161b885e62cb7be52604dc3f9588fb636

Observation 6fc23b94-4035-4202-b7e2-31ad9f68e8d1 · inbound

Proxy Exploration and Reusable Guidance: A Modular LLM Post-Training Paradigm via Proxy-Guided Update Signals cites this paper.

Proxy Exploration and Reusable Guidance: A Modular LLM Post-Training Paradigm via Proxy-Guided Update Signals Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-14T05:09:00.865375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T05:09:00.865375Z digest=sha256:8bf0707087007b55d271f24e9810cff2045934a92b88edf88104f64f7befbfdc