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Paper Citation Record · LEDGER

JsonTuning: Towards Generalizable, Robust, and Controllable Instruction Tuning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.02953.

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

pith.paper-citation-record.v1
2310.02953 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:25:58.912299Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-04T20:44:00.750789Z

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 cb0d6aaa-66ed-44d5-8ecf-1846e07330e3 · inbound

SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution cites this paper.

SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution JsonTuning: Towards Generalizable, Robust, and Controllable Instruction Tuning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T21:25:58.912299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:25:58.912299Z digest=sha256:90e79d4024f3ce84f40bf5ac5e62da1605a822f40356fc0af5f2b1b3df75b5dc

Observation 26b963d0-a186-443b-b28b-d305450ca9b3 · inbound

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model cites this paper.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model JsonTuning: Towards Generalizable, Robust, and Controllable Instruction Tuning

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-04T20:44:00.806998Z

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=2026-08-04T20:43:59.763424Z digest=sha256:a024df63c001dfc76362aba5a6694628e846961cf240d5da5ead06d72a206e33