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Paper Citation Record · LEDGER

Evaluating Large Language Models for Document-grounded Response Generation in Information-Seeking Dialogues

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2309.11838.

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

pith.paper-citation-record.v1
2309.11838 v1

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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:25:34.092322Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:47:22.454415Z

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 58465320-cb08-4755-b440-d1ad0a1be661 · inbound

AlzheimerRAG: Multimodal Retrieval Augmented Generation for Clinical Use Cases using PubMed articles cites this paper.

AlzheimerRAG: Multimodal Retrieval Augmented Generation for Clinical Use Cases using PubMed articles Evaluating Large Language Models for Document-grounded Response Generation in Information-Seeking Dialogues

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T10:25:34.092322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:34.092322Z digest=sha256:bd735fdf8f4bd0697714c62b6ca7d871d39dcfb8a11d4e4edcf4a759d06add32

Observation 9c02f402-895e-46d1-90fd-5cb0672e0f6d · inbound

ModelForge: Using GenAI to Improve the Development of Security Protocols cites this paper.

ModelForge: Using GenAI to Improve the Development of Security Protocols Evaluating Large Language Models for Document-grounded Response Generation in Information-Seeking Dialogues

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:47:22.527183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T05:47:20.679895Z digest=sha256:3bbd00fc4ee14738203091e33e645fe749d8155ce9772368b4d6eb6e347116ad