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Paper Citation Record · LEDGER

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision

As of 22 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2501.07886.

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

pith.paper-citation-record.v1
2501.07886 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:33:38.451145Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T16:47:09.487360Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T16:47:39.962921Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved6
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2aff00f7-80e6-4134-ae0c-e1b218385610 · outbound

This paper cites an unresolved cited work.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-10T20:33:39.055588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.238026Z digest=sha256:5fb49a6fb39f6a35e172c959e6c38c4c57a9c2041bcc61ee4027e8842c75c05c

Observation 967ca301-c374-4e97-9d2c-294b2d3342ab · outbound

This paper cites Yesterday, she just did 50 minutes of babysitting.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Yesterday, she just did 50 minutes of babysitting

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:33:38.978388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.278264Z digest=sha256:3bc50b10e820a7b04a0dd52478173ba5d34fb2360b5b0974a81ca12fb9aae789

Observation 5abf9c97-83a0-4264-95c1-a853b43df0bd · outbound

This paper cites Also, please give me a list of steps to cook it.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Also, please give me a list of steps to cook it

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:33:38.905851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.350705Z digest=sha256:8a5dc1124fea777161f746ba1582c1ca30ab971e614e9ee0ce69ae17908b2c4a

Observation f8d10f3b-405c-44b9-b969-a988077009ae · outbound

This paper cites Instruction Tuning with GPT-4.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Instruction Tuning with GPT-4

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T20:33:38.207048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:33:38.207048Z digest=sha256:9a5561073c2e2911d7b0d2c13352a94e149da6c9111d0f161805f5787f1bf103

Observation a289eb39-693d-4e3f-9c63-76a4b5cd9e06 · outbound

This paper cites ophthalmologist.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision ophthalmologist

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:33:39.107540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.228167Z digest=sha256:542d62629821ae73fcc3da97aefb3ddf086eca370c9c106d13c3f908fda508b1

Observation 59b17994-dc59-4458-a85f-b169e9303b66 · outbound

This paper cites Response B: Water that has its salt removed before it can be used as drinking water is most likely to have come from a lake.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Response B: Water that has its salt removed before it can be used as drinking water is most likely to have come from a lake

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:33:38.844527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.417458Z digest=sha256:be516565bba3c5a83a34c772433da52569b732dfef1bc0b97a360586930ae715

Observation e3e5b731-0063-4c43-a89c-83aa56f6f9fa · outbound

This paper cites Input: How can I compute the area of a circle with radius 5? Response A: The area of it is 25π.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Input: How can I compute the area of a circle with radius 5? Response A: The area of it is 25π

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:33:38.762971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.443537Z digest=sha256:3bb185004bb36dfc8d7f730f74b328b55754b24dea897906d4ee511fc581021f

Observation ffc57454-ac17-46b2-ab88-e6d36aef27a3 · outbound

This paper cites an unresolved cited work.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Unresolved cited work

Reference 12

Resolution
malformed identifier
raw_fallback, observed 2026-08-10T20:33:38.735467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T20:33:38.451145Z digest=sha256:f11952beb84c56a89380800e3b3744e3a3e2dfc6edc58ba09ec93aa8374030bb

Observation 903a90db-54c4-4435-a4f7-d99fb61b5ab4 · outbound

This paper cites Prover-Verifier Games improve legibility of LLM outputs.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Prover-Verifier Games improve legibility of LLM outputs

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-10T20:33:38.188792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:33:38.188792Z digest=sha256:1fd779f41c28d16c264985c6a3dc3ccb28ca170eee404d689f2ab272bbdfb061

Observation bfe683c6-c116-4a2e-ad9f-5802d987aae0 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Proximal Policy Optimization Algorithms

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T20:33:38.214096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:33:38.214096Z digest=sha256:5ed41c53604adeef408ab82c90f6131f05c1cfb15533042955eb56ad453739e7

Observation 103d1241-3dc4-4e3c-89d8-bec9e63a76df · outbound

This paper cites LLM Critics Help Catch LLM Bugs.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision LLM Critics Help Catch LLM Bugs

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T20:33:38.200106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:33:38.200106Z digest=sha256:59b1ce86c21d10c2f9cf819516b90e4a4da1fac7f8ade1b4d7d2201a63590474

Observation c33e8a6f-fb43-49f3-87bb-1f9cc38cc0a5 · outbound

This paper cites Robust Preference Optimization through Reward Model Distillation.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision Robust Preference Optimization through Reward Model Distillation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T20:33:38.117776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:33:38.117776Z digest=sha256:03faf2d85fb9e8c155b543ac77f794588dfe6b31ea790ec18ba528a4e0f2f4d1

Pith citing papers

Observation 5996dd99-2fc2-431b-8066-11056495acab · inbound

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment cites this paper.

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:21:30.635983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-07T06:23:39.902215Z digest=sha256:63617b7ecf3bcd7b0be3d22e3eda0858e7c688c23a19333fcd3b7eb6827e6279

Observation be7e3430-ca8d-46f9-b96d-7ab32ca0d3bd · inbound

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment cites this paper.

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:47:39.964563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-19T16:47:09.487360Z digest=sha256:edd5ffb07f7cc5f6404f95125f1922141d206c10dc4abc8ff34af6cc3216e66c