Paper Citation Record · LEDGER

Synthetic Dialogue Dataset Generation using LLM Agents

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2401.17461.

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

pith.paper-citation-record.v1
2401.17461 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 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:08:57.496779Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T17:02:24.240613Z

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 1ada69b1-80bf-4472-a7eb-d6e712f7677b · inbound

DeepThink: Aligning Language Models with Domain-Specific User Intents cites this paper.

DeepThink: Aligning Language Models with Domain-Specific User Intents Synthetic Dialogue Dataset Generation using LLM Agents

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T19:08:57.496779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 220944f6-2a3a-4268-b3af-10d298f7bd51 · inbound

Measuring Diversity in Synthetic Datasets cites this paper.

Measuring Diversity in Synthetic Datasets Synthetic Dialogue Dataset Generation using LLM Agents

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T04:54:50.557083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 779e10bb-b056-4eaa-afea-d535442dcd85 · inbound

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration cites this paper.

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration Synthetic Dialogue Dataset Generation using LLM Agents

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:52.790878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab493dd5-e709-427f-b346-f5071158885a · inbound

DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images cites this paper.

DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images Synthetic Dialogue Dataset Generation using LLM Agents

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:58.827943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f3562d8-d76f-428c-b6fc-862e55cf20a0 · inbound

Separation Logic of Generic Resources via Sheafeology cites this paper.

Separation Logic of Generic Resources via Sheafeology Synthetic Dialogue Dataset Generation using LLM Agents

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T05:22:28.669764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 927e7aa8-7667-4a07-b965-6b988d96385a · inbound

DiscussLLM: Teaching Large Language Models When to Speak cites this paper.

DiscussLLM: Teaching Large Language Models When to Speak Synthetic Dialogue Dataset Generation using LLM Agents

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:10:42.323259Z

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.

Observation 0078284d-ed96-4856-91de-475d2c58f8f0 · inbound

UniD$^3$: A Knowledge Graph-Enhanced RAG Framework for Drug-Disease Discovery and Reasoning cites this paper.

UniD$^3$: A Knowledge Graph-Enhanced RAG Framework for Drug-Disease Discovery and Reasoning Synthetic Dialogue Dataset Generation using LLM Agents

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:02:24.241995Z

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.