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Paper Citation Record · LEDGER

Multi-Level Explanations for Generative Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.14459.

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

pith.paper-citation-record.v1
2403.14459 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:54:43.920282Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T07:22:09.147343Z

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 687a419e-c8a8-44a2-ac82-18e33a174bae · inbound

Context Attribution with Multi-Armed Bandit Optimization cites this paper.

Context Attribution with Multi-Armed Bandit Optimization Multi-Level Explanations for Generative Language Models

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-19T07:22:09.150404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T07:21:20.893732Z digest=sha256:151223b8623a23f8dc7c405c4a9332ec9890cdc7928b6b3b1b1d43ea36fa1aec

Observation 9a86b994-4c0d-433b-b73c-b1bb872263ab · inbound

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data cites this paper.

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data Multi-Level Explanations for Generative Language Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T21:54:43.920282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:54:43.920282Z digest=sha256:d96a94781c11638c549e641a20395a6f1a946dca92f4d6799eb7aaaf32d1d5b3