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Paper Citation Record · LEDGER

Beyond Binary: Towards Fine-Grained LLM-Generated Text Detection via Role Recognition and Involvement Measurement

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.14259.

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

pith.paper-citation-record.v1
2410.14259 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 2026-08-08T21:12:22.682394Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:25:27.034936Z

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 e20029ae-7054-41e4-8093-15d124e15a64 · inbound

Survey on AI-Generated Media Detection: From Non-MLLM to MLLM cites this paper.

Survey on AI-Generated Media Detection: From Non-MLLM to MLLM Beyond Binary: Towards Fine-Grained LLM-Generated Text Detection via Role Recognition and Involvement Measurement

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-08T21:12:22.682394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:12:22.682394Z digest=sha256:23140b05f687bcdf1f1fbe6ec0c0f139f9bda62edb9a87f81e615d9896f0bf67

Observation da3e2e73-c631-43d8-831b-d29b04917aa7 · inbound

Do We Really Need GNNs with Explicit Structural Modeling? MLPs Suffice for Language Model Representations cites this paper.

Do We Really Need GNNs with Explicit Structural Modeling? MLPs Suffice for Language Model Representations Beyond Binary: Towards Fine-Grained LLM-Generated Text Detection via Role Recognition and Involvement Measurement

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:25:27.068381Z

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=2026-08-06T22:25:25.381101Z digest=sha256:b29aeb99edb97ac033df59c738d27308cf85a3adf4c26c96cbec02311e39b3d1