Paper Citation Record · LEDGER

Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models

As of 13 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 2 inbound Pith citation observations for arXiv:2412.18715.

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

pith.paper-citation-record.v1
2412.18715 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:35:35.903435Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:58:22.355461Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:40:02.802529Z

Reference resolution

5 of 5 outbound references displayed

verified exact1
verified fuzzy2
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18e8c334-d9ac-436e-960e-21bd3b734086 · outbound

This paper cites an unresolved cited work.

Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-11T04:35:36.059776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 95164e66-b846-435a-a090-f06d3e54cb0d · outbound

This paper cites The two main types of collaborative filtering are User-based Collaborative Filtering and Item-based Collaborative Filtering, as shown in <Figure 1>[8].

Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models The two main types of collaborative filtering are User-based Collaborative Filtering and Item-based Collaborative Filtering, as shown in <Figure 1>[8]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:35:36.042216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 35685993-9fd8-470d-86a1-1c96cbaf4cd5 · outbound

This paper cites The experiments utilized two publicly available datasets, MovieLens 1M and Netflix Prize, along with a real-world e-commerce user behavior dataset.

Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models The experiments utilized two publicly available datasets, MovieLens 1M and Netflix Prize, along with a real-world e-commerce user behavior dataset

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:35:36.024760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 42887f73-307b-4306-ad2e-e69bc4501a05 · outbound

This paper cites Multi-modal clothing recommendation model based on large model and VAE enhancement.

Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models Multi-modal clothing recommendation model based on large model and VAE enhancement

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-11T04:35:36.007839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cb045269-f5f6-4503-a8a2-54e63ad1b5ee · outbound

This paper cites DRAL: Deep Reinforcement Adaptive Learning for Multi-UAVs Navigation in Unknown Indoor Environment.

Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models DRAL: Deep Reinforcement Adaptive Learning for Multi-UAVs Navigation in Unknown Indoor Environment

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T04:35:35.903435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5dac6316-1df1-4956-b271-4ec2a192a275 · inbound

Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving cites this paper.

Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:58:22.355461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0301b5c2-af28-471e-901b-a15ae06e0fc6 · inbound

Dialogue to Discovery: Attribute-Aware Preference Elicitation for Conversational Product Search Assistants cites this paper.

Dialogue to Discovery: Attribute-Aware Preference Elicitation for Conversational Product Search Assistants Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-04T18:40:02.804077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.