Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring the Benefits of Training Expert Language Models over Instruction Tuning
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.03202.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:28:14.324045Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T12:28:15.146095Z
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 89543314-69cb-442c-9dfb-12e0d0d92f0e · inbound
Strategic Prompting for Conversational Tasks: A Comparative Analysis of Large Language Models Across Diverse Conversational Tasks cites this paper.
Strategic Prompting for Conversational Tasks: A Comparative Analysis of Large Language Models Across Diverse Conversational Tasks Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T12:28:15.150958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 497e9c6f-5d83-4e76-9456-011b7046179f · inbound
SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.
SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Reference 136
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:51:03.593157Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.