Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.11417.
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 2026-08-07T14:46:02.191493Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T01:46:26.878352Z
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 2f493e84-cfa3-421a-aeb8-3ff8ab0d795b · inbound
Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting cites this paper.
Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:46:02.191493Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a932015-6f65-4061-84e5-e35e7bc2591b · inbound
ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning cites this paper.
ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:23:35.169522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8afc4e61-db51-4ecc-be45-a4c3bdbaa20d · inbound
MetaTT: A Global Tensor-Train Adapter for Parameter-Efficient Fine-Tuning cites this paper.
MetaTT: A Global Tensor-Train Adapter for Parameter-Efficient Fine-Tuning LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:05:00.491232Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed4888d8-8219-4983-8862-dc14a6c801fa · inbound
Quantum-inspired tensor networks in machine learning models cites this paper.
Quantum-inspired tensor networks in machine learning models LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
Reference 143
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T14:10:29.100838Z
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 278469c8-79ae-491c-9f78-84637b81321c · inbound
Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression cites this paper.
Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
Reference 50
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T01:46:26.880351Z
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.