Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2601.03808.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-10T20:15:59.064352Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-10T20:17:33.744001Z
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 7a754496-c60e-4270-8ab4-00172105b97c · inbound
Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models cites this paper.
Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-08-06T02:01:35.592368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 41b38335-3a7c-47dd-8550-e5c78a6b0d40 · inbound
Towards Robust Training in NNGPT AutoML Pipeline: A Loss-Optimizer Pairing Selection Study cites this paper.
Towards Robust Training in NNGPT AutoML Pipeline: A Loss-Optimizer Pairing Selection Study From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-08-06T02:01:35.592368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a3f3d7a8-e7dc-43ce-bbb9-d643c860edca · inbound
Systematic Exploration of 4-Expert Heterogeneous Mixture-of-Experts via Automated Pipeline Search cites this paper.
Systematic Exploration of 4-Expert Heterogeneous Mixture-of-Experts via Automated Pipeline Search From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-08-06T02:01:35.592368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0a8b1f82-023a-4ff5-b556-55d017c617c8 · inbound
LEMUR 2: Unlocking Neural Network Diversity for AI cites this paper.
LEMUR 2: Unlocking Neural Network Diversity for AI From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-08-06T02:01:35.592368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ed2080dc-8f6f-4ede-8ca9-bebfbfc667a9 · inbound
Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures cites this paper.
Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures From Brute Force to Semantic Insight: Performance-Guided Data Transformation Design with LLMs
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-08-06T02:01:35.592368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.