Paper Citation Record · LEDGER

Automatic Instruction Evolving for Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.00770.

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

pith.paper-citation-record.v1
2406.00770 v1

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 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:35:28.528765Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7dd0dc24-a682-41df-b699-7505a5f572c2 · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods Automatic Instruction Evolving for Large Language Models

Reference 289

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:08:35.898787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8d52b6c0-cdc4-497d-b59f-da3a69a31420 · inbound

Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis cites this paper.

Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis Automatic Instruction Evolving for Large Language Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-09T00:35:28.528765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b8f76b3-7278-4b7b-962c-88c3e9f66f7c · inbound

Mediator: Memory-efficient LLM Merging with Less Parameter Conflicts and Uncertainty Based Routing cites this paper.

Mediator: Memory-efficient LLM Merging with Less Parameter Conflicts and Uncertainty Based Routing Automatic Instruction Evolving for Large Language Models

Reference 7261

Resolution: unresolved; no resolver link, observed 2026-08-09T00:07:44.792827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebd7f217-1e0d-4803-a695-f19d2304d9f0 · inbound

Tag-Evol: Achieving Efficient Instruction Evolving via Tag Injection cites this paper.

Tag-Evol: Achieving Efficient Instruction Evolving via Tag Injection Automatic Instruction Evolving for Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:07.348623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9481148-d000-40ae-bcf3-a1f670d2b072 · inbound

Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence cites this paper.

Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence Automatic Instruction Evolving for Large Language Models

Reference 127

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:25:54.207272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 31adfb6e-eb10-4382-8105-8bca9cc74a01 · inbound

Automated IEP Generation from Traditional Chinese Parent-Teacher Interviews via Corpus-Grounded Feature Diffusion cites this paper.

Automated IEP Generation from Traditional Chinese Parent-Teacher Interviews via Corpus-Grounded Feature Diffusion Automatic Instruction Evolving for Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:57:30.696226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.