Paper Citation Record · LEDGER

Language Model Inversion

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2311.13647.

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

pith.paper-citation-record.v1
2311.13647 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 2026-08-06T06:34:29.942622+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:59:02.503431Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:38:58.164589Z

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 67848785-9880-4729-8fba-e2a0548ab204 · inbound

Approximating Language Model Training Data from Weights cites this paper.

Approximating Language Model Training Data from Weights Language Model Inversion

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T23:59:02.503431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a65503a7-cfc6-4c30-9bce-6425a725f1a5 · inbound

Cascade: Token-Sharded Private LLM Inference cites this paper.

Cascade: Token-Sharded Private LLM Inference Language Model Inversion

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:52.905233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc66222a-e0ec-4d50-ae97-cab50d9f8479 · inbound

What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests cites this paper.

What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests Language Model Inversion

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T17:21:33.687986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fb7d3d3-4ee1-4ac9-a2e0-96861b7229e3 · inbound

inversedMixup: Data Augmentation via Inverting Mixed Embeddings cites this paper.

inversedMixup: Data Augmentation via Inverting Mixed Embeddings Language Model Inversion

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T07:00:24.771917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c6b5bdc-065e-4104-96e3-e431b190ca69 · inbound

Why Trust Your Agent? Empirical Security Gains from TRiSM-Guided Agentic Workflows in Healthcare cites this paper.

Why Trust Your Agent? Empirical Security Gains from TRiSM-Guided Agentic Workflows in Healthcare Language Model Inversion

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T12:44:39.634808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 03fb7517-b72f-498d-b705-b49650eb5749 · inbound

Black-Box Inference of LLM Architectural Properties with Restrictive API Access cites this paper.

Black-Box Inference of LLM Architectural Properties with Restrictive API Access Language Model Inversion

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:38:58.166235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f24e6783-5e03-4c3b-b419-b8901de594a2 · inbound

Can Watermarking Techniques Help Prevent LLM Model Stealing? cites this paper.

Can Watermarking Techniques Help Prevent LLM Model Stealing? Language Model Inversion

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-14T09:13:20.561611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.