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Paper Citation Record · LEDGER

SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.00705.

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

pith.paper-citation-record.v1
2405.00705 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:29:51.840118Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T05:30:57.992280Z

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 ee02d567-0c4a-4801-a476-73ce511b2991 · inbound

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers cites this paper.

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Reference 141

Resolution
unresolved
no resolver link, observed 2026-08-07T22:50:33.169978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:50:33.169978Z digest=sha256:f504f4c5b2f2519738c77a78940975ae5e7b3dfc34612223e19905701a5e48ca

Observation 8b18540f-092d-4e81-87f4-e2e39a77f0f1 · inbound

Data-efficient LLM Fine-tuning for Code Generation cites this paper.

Data-efficient LLM Fine-tuning for Code Generation SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T12:29:51.840118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:29:51.840118Z digest=sha256:66e44a80910cf68edc81d6dc78a5af3f0ac5bb6de250c0ce9d669266d8456431

Observation 1f160d64-1e72-4064-b628-117ebb2a9a36 · inbound

RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection cites this paper.

RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T23:12:38.822550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:12:38.822550Z digest=sha256:518426c4a368709cd98df475013219c76f03fc2b8006bc8bcb784e2b28ebc0e2

Observation def35665-110c-4315-bc72-3b3b762c6ca1 · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Reference 168

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:13.155938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:13.155938Z digest=sha256:b57c9b05d47b7b33d3e64d50c1e57e43fbf04b5077020a8a0f916e78cfd8b87e

Observation 95a37907-86cf-491c-a877-0a13910a9711 · inbound

SCAR: Shapley Credit Assignment for More Efficient RLHF cites this paper.

SCAR: Shapley Credit Assignment for More Efficient RLHF SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:02:49.299000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:49.299000Z digest=sha256:42024e7e0889d7d761f4bd48d9d8197b543fdf6b3cc3933552bb0bf68117f3f0

Observation 0f3faee7-99a9-4154-964e-3c6e4440aef2 · inbound

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization cites this paper.

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Reference 28

Resolution
malformed identifier
arxiv_id, observed 2026-05-11T05:30:57.994716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T18:06:46.131725Z digest=sha256:b30390f5872d1ebc1fc22a142abf0832eb04bd1aa60d8e00d919755544975df4