Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SLIM: Let LLM Learn More and Forget Less with Soft LoRA and Identity Mixture
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.07739.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:48.455012Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T17:24:32.052217Z
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 65958e08-eb0c-4c09-a375-0adab7e4ff0d · inbound
CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval cites this paper.
CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval SLIM: Let LLM Learn More and Forget Less with Soft LoRA and Identity Mixture
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T17:24:32.057293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 037ce48a-3109-4390-a1c1-71674653c25c · inbound
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models SLIM: Let LLM Learn More and Forget Less with Soft LoRA and Identity Mixture
Reference 209
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:59:48.455012Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d359c03a-7aad-4982-9c5a-49b1d273e160 · inbound
Continual Learning for Generative AI: From LLMs to MLLMs and Beyond cites this paper.
Continual Learning for Generative AI: From LLMs to MLLMs and Beyond SLIM: Let LLM Learn More and Forget Less with Soft LoRA and Identity Mixture
Reference 73
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:40:22.014455Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.