Paper Citation Record · LEDGER

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

As of 15 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2509.08381.

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

pith.paper-citation-record.v1
2509.08381 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:44:00.382918Z

measured 11 of 11 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

11 of 11 outbound references displayed

verified exact2
verified fuzzy4
unresolved4
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 480b69a9-09e3-44c3-a206-97bc81f0557d · outbound

This paper cites Structured information extraction from scientific text with large language models,.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Structured information extraction from scientific text with large language models,

Reference 1

Resolution: malformed identifier; no resolver link, observed 2026-08-04T20:43:59.601783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38b700db-61a2-44b8-9f77-953009287af9 · outbound

This paper cites Get the best out of 1B LLMs: Insights from information extraction on clinical documents,.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Get the best out of 1B LLMs: Insights from information extraction on clinical documents,

Reference 2

Resolution: verified exact; doi, observed 2026-08-04T20:44:00.585371Z

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.

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

This paper cites JsonTuning: Towards Generalizable, Robust, and Controllable Instruction Tuning.

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

Observation 12a7fe92-9652-41f3-9cbf-3431718fc80d · outbound

This paper cites Instruction tuning for on-demand information extraction,.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Instruction tuning for on-demand information extraction,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:44:01.511056Z

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.

Observation 5f99ac5d-b92f-40bf-b271-dcbaec69c4a3 · outbound

This paper cites Advancing entity recognition in biomedicine via instruction-based approaches,.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Advancing entity recognition in biomedicine via instruction-based approaches,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:44:01.369949Z

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.

Observation 787fbc5e-9f43-41f5-8e3e-4a99d6dbf9b1 · outbound

This paper cites Breeze-7B Technical Report.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Breeze-7B Technical Report

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T20:44:00.002645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 966f9ff6-a1bb-4b6d-9d8b-4dc2fe259db0 · outbound

This paper cites InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T20:44:00.087316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af4af074-7110-4728-8bf4-65ad41a14062 · outbound

This paper cites LlamaFactory: Unified efficient fine-tuning of 100+ language models,.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model LlamaFactory: Unified efficient fine-tuning of 100+ language models,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:44:01.222988Z

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.

Observation a55c07cd-fdc5-45f6-86a5-c31a362a97e3 · outbound

This paper cites Learning to extract structured entities using language models,.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Learning to extract structured entities using language models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:44:00.964171Z

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.

Observation f7acb8b1-17cd-4e8c-a1d4-2cc602b2ea30 · outbound

This paper cites Qwen2.5 Technical Report.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Qwen2.5 Technical Report

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T20:44:00.382918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e31d9d94-7aa2-4803-a8f1-da450b4fe713 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T20:44:00.224276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.