Paper Citation Record · LEDGER

Studying LLM Performance on Closed- and Open-source Data

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.15100.

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

pith.paper-citation-record.v1
2402.15100 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:25:31.398583Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T09:16:48.853265Z

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 9ecca2f2-f854-4ee6-ac7a-ef07f7e585a3 · inbound

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry cites this paper.

RAG or Fine-tuning? A Comparative Study on LCMs-based Code Completion in Industry Studying LLM Performance on Closed- and Open-source Data

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:25:31.398583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f9714e3-0296-486c-b346-01af923d3944 · inbound

Can LLMs Generate User Stories and Assess Their Quality? cites this paper.

Can LLMs Generate User Stories and Assess Their Quality? Studying LLM Performance on Closed- and Open-source Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T15:46:35.536355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7e353a7-f422-4f03-bfc9-5de6b5858eb9 · inbound

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat cites this paper.

A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat Studying LLM Performance on Closed- and Open-source Data

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T14:35:29.458093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa09c197-404e-4d5f-a884-8eb608a39789 · inbound

Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation cites this paper.

Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation Studying LLM Performance on Closed- and Open-source Data

Reference 104

Resolution: unresolved; no resolver link, observed 2026-08-05T23:24:23.878719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce01d0c2-70ad-42b8-82e3-42765c014f1a · inbound

Empirical Study of Code Large Language Models for Binary Security Patch Detection cites this paper.

Empirical Study of Code Large Language Models for Binary Security Patch Detection Studying LLM Performance on Closed- and Open-source Data

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T04:37:02.568833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33651842-d4b9-4515-8fe2-718ecbd9afe5 · inbound

Large Language Models for Multi-Lingual Equivalent Mutant Detection: An Extended Empirical Study cites this paper.

Large Language Models for Multi-Lingual Equivalent Mutant Detection: An Extended Empirical Study Studying LLM Performance on Closed- and Open-source Data

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-02T09:16:48.854631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.