Paper Citation Record · LEDGER

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency

As of 10 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2502.01651.

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

pith.paper-citation-record.v1
2502.01651 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:45:50.591465Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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 exact1
verified fuzzy2
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 33f969ac-c781-472d-a499-4cb34f51ef14 · outbound

This paper cites Multi-threaded tests were conducted with varying thread counts to explore the impact of parallel processing on performance.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Multi-threaded tests were conducted with varying thread counts to explore the impact of parallel processing on performance

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:45:50.938018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9e0ee917-01b1-4923-b2ef-0ef2020a64b9 · outbound

This paper cites an unresolved cited work.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:45:50.924877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5bae4995-705a-4057-a65b-1c402e5686e7 · outbound

This paper cites Collected results were meticulously analyzed to discern and compare the performance characteristics of each implementation.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Collected results were meticulously analyzed to discern and compare the performance characteristics of each implementation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:45:50.913405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ac1bc9dd-d4e4-49b0-b585-2ce573bf2d2e · outbound

This paper cites Selecting Informative Contexts Improves Language Model Finetuning.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Selecting Informative Contexts Improves Language Model Finetuning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T22:45:50.561497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daea3ec4-70b1-4775-a0a1-1631e8e484c6 · outbound

This paper cites LlamaTune: Sample-Efficient DBMS Configuration Tuning.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency LlamaTune: Sample-Efficient DBMS Configuration Tuning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T22:45:50.567255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4875c56-8467-4025-a76b-e7f86aeaeffa · outbound

This paper cites Inference-Time Intervention: Eliciting Truthful Answers from a Language Model.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Inference-Time Intervention: Eliciting Truthful Answers from a Language Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T22:45:50.571819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad98f93f-380e-49ee-87fc-95c357b598f3 · outbound

This paper cites an unresolved cited work.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:45:50.901049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 93ea5bfe-1094-419a-ab08-7db7b053ebf7 · outbound

This paper cites an unresolved cited work.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:45:50.889623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 713c39bf-9cf5-4600-8ef9-3c674d827215 · outbound

This paper cites an unresolved cited work.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:45:50.877935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d767dd46-3d3b-4572-9b37-204b97f954dd · outbound

This paper cites Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T22:45:50.587342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66da2bfd-880e-4020-a1f5-44c39c633ef1 · outbound

This paper cites an unresolved cited work.

Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency Unresolved cited work

Reference 11

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T22:45:50.822213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.