Paper Citation Record · LEDGER

Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2203.06904.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2203.06904 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:47:16.628672Z

measured 0 of 1 external citation measurements

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
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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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

Observation 2cd2324b-9b75-41ba-868f-85bd6457a73c · inbound

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter cites this paper.

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:16.628672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f2f099d-e45e-498f-978d-0f5dd9861fbe · inbound

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation cites this paper.

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T01:03:38.175326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abeddf7b-7e53-4746-9c12-1baa38dae98f · inbound

Sharp Generalization Bounds for Foundation Models with Asymmetric Randomized Low-Rank Adapters cites this paper.

Sharp Generalization Bounds for Foundation Models with Asymmetric Randomized Low-Rank Adapters Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T00:28:39.344281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67e36b4f-4bfb-4796-94a9-3423ad939ee1 · inbound

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs cites this paper.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:28.445295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cffd4b2-6780-4103-aa7f-85eca601f8e6 · inbound

Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models cites this paper.

Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T16:49:56.785510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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.