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Paper Citation Record · LEDGER

Generative Job Recommendations with Large Language Model

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2307.02157.

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

pith.paper-citation-record.v1
2307.02157 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:20:29.301649Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T11:13:44.086811Z

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 b7bc9418-f257-4bcd-981d-5319a85aa2bd · inbound

The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit cites this paper.

The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit Generative Job Recommendations with Large Language Model

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T22:17:23.493640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:17:23.493640Z digest=sha256:0eefe721a7490c4fa5f2145d870a4cb7767f577a1c85fd3ceb034b6b29126b4f

Observation f5891ccd-c8bd-48ba-b6e1-c5dde53898fc · inbound

Unleashing the Power of Large Language Model for Denoising Recommendation cites this paper.

Unleashing the Power of Large Language Model for Denoising Recommendation Generative Job Recommendations with Large Language Model

Reference 104

Resolution
unresolved
no resolver link, observed 2026-08-07T22:50:53.908273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:50:53.908273Z digest=sha256:fd9046f76e6d72f202b722d52492f4f9a9e2412b46def750efe3bcafcacd26e7

Observation 73a4dec3-bb1e-4c5b-b1db-bc5f42ac70a2 · inbound

Active Large Language Model-based Knowledge Distillation for Session-based Recommendation cites this paper.

Active Large Language Model-based Knowledge Distillation for Session-based Recommendation Generative Job Recommendations with Large Language Model

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T15:24:21.889356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:24:21.889356Z digest=sha256:649510aed42bf17915bba5e4955a92c29149337e602fae086d5a0b2465e8508f

Observation 250ffa1c-6e01-4ae4-b7c2-d910ac8b49a4 · inbound

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects cites this paper.

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects Generative Job Recommendations with Large Language Model

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T19:20:29.301649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:20:29.301649Z digest=sha256:b76812dd564dc2f67dfc14e992ffe17fce7fea6e638370c47b44a494b4f43aa7

Observation 9ea70963-98ee-4616-b6ff-f8c2b4d45f3c · inbound

LLM-Driven Dual-Level Multi-Interest Modeling for Recommendation cites this paper.

LLM-Driven Dual-Level Multi-Interest Modeling for Recommendation Generative Job Recommendations with Large Language Model

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-06T17:27:36.164033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:27:36.164033Z digest=sha256:83eb0ced91472c6254cdda134dfbb4321927527228622e8890c8c7844ce1ae86

Observation 591a4167-3ef0-4ac3-acc9-eef050dd9543 · inbound

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics cites this paper.

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics Generative Job Recommendations with Large Language Model

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T16:51:37.608753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:37.608753Z digest=sha256:549b8ea6316365e5c5c21be816992bb0f6261a92c38e8b8bfe733837378a0da4

Observation 9161f236-129c-41fc-8e7b-66f654e5b77b · inbound

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation cites this paper.

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation Generative Job Recommendations with Large Language Model

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-05T11:13:44.141288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:13:42.955653Z digest=sha256:9a0a4a215a7313e1923a468dc7765a35f68e6773c538da8bdef775c2e3928d31