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Paper Citation Record · LEDGER

Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.13225.

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

pith.paper-citation-record.v1
2305.13225 v2

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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:02:43.954586Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T06:11:49.560070Z

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 8c87462a-526d-4037-bceb-13fce9d3ae03 · inbound

EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers cites this paper.

EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance

Reference 132

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:11:49.561635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-16T06:11:49.475825Z digest=sha256:b98fbd053294078ec2f95948e7652a21e5613b1d24895e0199e682cdafe5741e

Observation 89ba842a-c833-45cb-abee-a2b99b18a442 · inbound

LLMCL-GEC: Advancing Grammatical Error Correction with LLM-Driven Curriculum Learning cites this paper.

LLMCL-GEC: Advancing Grammatical Error Correction with LLM-Driven Curriculum Learning Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T14:02:43.954586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:02:43.954586Z digest=sha256:b18fe6fa0e2469db073b490a3d9d1278bde637ce7ee5a2b0bf4020c574df1505

Observation ed55f536-5a76-4541-ba7a-ddc55df54962 · inbound

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices cites this paper.

EdgeLoRA: An Efficient Multi-Tenant LLM Serving System on Edge Devices Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-06T20:59:03.569899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:59:03.569899Z digest=sha256:36fb43cee5d84eeec386b8db39e6c16b0480f4343394da1246c3b6d419b09868

Observation 1cda2649-5cec-4ce0-b17a-0fab48d8815b · inbound

Integrating gender inclusivity into large language models via instruction tuning cites this paper.

Integrating gender inclusivity into large language models via instruction tuning Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T16:31:10.091046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:31:10.091046Z digest=sha256:a5f1f76f95c0c2857c60952e8966b8270cf2a9387e8e4d1014b0c0b145b17a37

Observation 2fda0d49-3a94-4a34-91f5-0784f35c0eb3 · inbound

Harnessing Rule-Based Reinforcement Learning for Enhanced Grammatical Error Correction cites this paper.

Harnessing Rule-Based Reinforcement Learning for Enhanced Grammatical Error Correction Multi-Task Instruction Tuning of LLaMa for Specific Scenarios: A Preliminary Study on Writing Assistance

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T16:17:17.033042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:17:17.033042Z digest=sha256:bffd65bd5f3e926667f2aa3454bf59d5cb5be29763857117fdc94759fd6070f2