Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T20:44:00.382918Z
Paper Citation Record · LEDGER
As of 8 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T20:44:00.382918Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
11 of 11 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 480b69a9-09e3-44c3-a206-97bc81f0557d · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38b700db-61a2-44b8-9f77-953009287af9 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 26b963d0-a186-443b-b28b-d305450ca9b3 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 12a7fe92-9652-41f3-9cbf-3431718fc80d · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 5f99ac5d-b92f-40bf-b271-dcbaec69c4a3 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 787fbc5e-9f43-41f5-8e3e-4a99d6dbf9b1 · outbound
Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Breeze-7B Technical Report
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 966f9ff6-a1bb-4b6d-9d8b-4dc2fe259db0 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af4af074-7110-4728-8bf4-65ad41a14062 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a55c07cd-fdc5-45f6-86a5-c31a362a97e3 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f7acb8b1-17cd-4e8c-a1d4-2cc602b2ea30 · outbound
Low-Resource Fine-Tuning for Multi-Task Structured Information Extraction with a Billion-Parameter Instruction-Tuned Model Qwen2.5 Technical Report
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e31d9d94-7aa2-4803-a8f1-da450b4fe713 · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.