Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2203.06904.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T10:14:32.903421Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T04:07:36.843758Z
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 3d2d8b35-1dff-40bc-8d22-718cad24271a · inbound
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model cites this paper.
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T08:41:04.794104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9c58cbcd-becb-45ba-9000-8b79233b7f35 · inbound
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection cites this paper.
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T23:51:50.295166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3d4d83ba-78bb-467c-8921-669f0845d63e · inbound
A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.
A Survey on the Memory Mechanism of Large Language Model based Agents Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T07:21:39.949513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 33ad3137-b31c-4fa1-898f-fbada4110ecf · inbound
A Survey on Large Language Models for Code Generation cites this paper.
A Survey on Large Language Models for Code Generation Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 67
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:18:06.720369Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation dffb9ab2-0397-4a0a-a3f2-46e14e130260 · inbound
LLaVA-Video: Video Instruction Tuning With Synthetic Data cites this paper.
LLaVA-Video: Video Instruction Tuning With Synthetic Data Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 133
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T23:20:32.777912Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 36b48c1e-5e44-40a9-99ee-1f69131f7d3e · inbound
K-Merge: Online Continual Merging of Adapters for On-device Large Language Models cites this paper.
K-Merge: Online Continual Merging of Adapters for On-device Large Language Models Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T09:47:23.181611Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94e8d8f0-c119-4162-8047-6c05e020b722 · inbound
Visual prompting reimagined: The power of the Activation Prompts cites this paper.
Visual prompting reimagined: The power of the Activation Prompts Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:45:53.688717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9fa8380c-cf61-44ce-a8c9-915998e5724b · inbound
TLoRA: Task-aware Low Rank Adaptation of Large Language Models cites this paper.
TLoRA: Task-aware Low Rank Adaptation of Large Language Models Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 52
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T09:48:48.118759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 3e53810a-03a4-46cd-8ceb-505435c7e206 · inbound
Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation cites this paper.
Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:40:58.663635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cdb7376a-4ea3-4307-9d07-fdce6a8a9b3a · inbound
Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation cites this paper.
Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T23:53:51.976530Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 212b0dda-f5c0-45a6-9b4b-2be0b3596628 · inbound
Soft Specialists: $\alpha$-R\'enyi Ensembles for Uncertainty-Aware LLM Post-Training cites this paper.
Soft Specialists: $\alpha$-R\'enyi Ensembles for Uncertainty-Aware LLM Post-Training Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T15:23:32.966360Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation ee65e143-de76-4677-877d-1d7f50175b41 · inbound
Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey cites this paper.
Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T04:07:36.845177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 26adb54c-cd6b-459f-9d31-3e65b6c3fd3a · inbound
Z-PEFT: Zero-shot Backdoor Detection in Parameter-Efficient Fine-Tuning via Canonical Spectral Signatures cites this paper.
Z-PEFT: Zero-shot Backdoor Detection in Parameter-Efficient Fine-Tuning via Canonical Spectral Signatures Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T10:14:32.903421Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.