Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Context Engineering for Multi-Agent LLM Code Assistants Using Elicit, NotebookLM, ChatGPT, and Claude Code
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2508.08322.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T15:05:51.665727Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T13:16:58.912659Z
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 7f94830f-688b-459a-9724-601893814e48 · inbound
Accuracy Is Speed: Towards Long-Context-Aware Routing for Distributed LLM Serving cites this paper.
Accuracy Is Speed: Towards Long-Context-Aware Routing for Distributed LLM Serving Context Engineering for Multi-Agent LLM Code Assistants Using Elicit, NotebookLM, ChatGPT, and Claude Code
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:17:37.457889Z
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 0447d97f-c30f-417d-95d0-2e45e4d04b91 · inbound
CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments cites this paper.
CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments Context Engineering for Multi-Agent LLM Code Assistants Using Elicit, NotebookLM, ChatGPT, and Claude Code
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T13:16:58.914042Z
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 dd4706c2-1fa0-4afc-b02c-479f386cf0a9 · inbound
CORVUS: Context Optimization and Reduction Via Underlying Synchronization for LLM Coding Agents cites this paper.
CORVUS: Context Optimization and Reduction Via Underlying Synchronization for LLM Coding Agents Context Engineering for Multi-Agent LLM Code Assistants Using Elicit, NotebookLM, ChatGPT, and Claude Code
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T15:05:51.665727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.