Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-29T12:32:58.361449Z
Paper Citation Record · LEDGER
Plan Before Search: Search Agents Need Plan
As of 13 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 1 inbound Pith citation observation for arXiv:2605.28354.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T15:12:55.595577Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
4 of 4 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch4
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c02f2940-4b42-4169-bc94-a020ffefb6e5 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
Plan Before Search: Search Agents Need Plan DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T12:33:24.208465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4b59eee6-0bfa-4e6c-8914-2743a0ee761f · outbound
This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.
Plan Before Search: Search Agents Need Plan Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T12:33:24.213224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b6391241-ef50-4b53-b021-774880d1ee26 · outbound
This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.
Plan Before Search: Search Agents Need Plan R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T12:33:24.210705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a283f145-9bb5-4247-8a8a-606f201215bf · outbound
This paper cites Internvl-u: Democratizing unified multimodal models for understanding, reasoning, generation and editing.
Plan Before Search: Search Agents Need Plan Internvl-u: Democratizing unified multimodal models for understanding, reasoning, generation and editing
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T12:33:24.216183Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
Observation 73ba6961-f398-4673-9bbd-c3044db0fa32 · inbound
Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents cites this paper.
Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents Plan Before Search: Search Agents Need Plan
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T15:12:55.595577Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.