Paper Citation Record · LEDGER

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.21119.

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

pith.paper-citation-record.v1
2506.21119 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:43:57.676619Z

measured 38 of 38 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact0
verified fuzzy14
unresolved24
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation abbaafb5-47ca-4e6e-8204-6edc4b75d414 · outbound

This paper cites Language models are unsupervised multitask learners,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Language models are unsupervised multitask learners,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:54.496122Z

Source-reported events for the cited work

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Observation 07a9e4c5-cdec-4ed7-a0b1-9fe7e053b84d · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:54.555315Z

Source-reported events for the cited work

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Observation 8ad8ccb0-ea1b-4375-b9d7-2afeb9c10006 · outbound

This paper cites Language models are few-shot learners,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Language models are few-shot learners,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:59.277860Z

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 d4ac90af-af9f-4e87-aecd-174b63fbf6a4 · outbound

This paper cites What does bert learn about the structure of language?.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models What does bert learn about the structure of language?

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:59.171646Z

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 3bb52e1d-1e0c-48df-9426-8c374e29671d · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Parameter-efficient transfer learning for nlp,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:59.080451Z

Source-reported events for the cited work

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Observation 28330c3b-b41b-4d09-a427-46dc4e59961a · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 6

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Source-reported events for the cited work

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Observation 30cedd7f-f3fa-4203-b5d9-d128ae3ce4e7 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:54.942510Z

Source-reported events for the cited work

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Observation bbcf38d5-472a-430a-a371-4672daac4cd2 · outbound

This paper cites A fully progressive approach to single-image super-resolution,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models A fully progressive approach to single-image super-resolution,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.959448Z

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 344cb963-e5ee-4e3e-984e-95b0f026f74e · outbound

This paper cites Cascade ef-gan: Progressive facial expres- sion editing with local focuses,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Cascade ef-gan: Progressive facial expres- sion editing with local focuses,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.893600Z

Source-reported events for the cited work

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Observation 4ad88754-a7ae-44f7-a5d3-c5c22a59157d · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.153780Z

Source-reported events for the cited work

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Observation 102cdc13-1f51-4980-b90c-c43aacbf7044 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.238949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 092f8973-323d-4d37-8e73-58e90505cbaa · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.309762Z

Source-reported events for the cited work

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Observation 68d0b7a0-6bc3-4b68-bc00-a4e26238e82a · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.395121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ba9485f-680a-4e58-ab44-3f863d6d6278 · outbound

This paper cites Transformers: State-of-the-art natural language processing,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Transformers: State-of-the-art natural language processing,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.803014Z

Source-reported events for the cited work

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Observation 540795af-bf38-4a4d-ad66-f2bb2bb438d0 · outbound

This paper cites Parameter-Efficient Transfer Learning with Diff Pruning.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Parameter-Efficient Transfer Learning with Diff Pruning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.559780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a849b09e-cb07-4129-9624-7a31dcf34253 · outbound

This paper cites Semi-supervised sequence learning,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Semi-supervised sequence learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.717111Z

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 888ecb68-2034-4121-94ce-223274090a19 · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Universal Language Model Fine-tuning for Text Classification

Reference 17

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Source-reported events for the cited work

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Observation d03f7099-3624-40fe-937a-35c325fa38b9 · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.838312Z

Source-reported events for the cited work

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Observation 87f0ca40-2f52-4ab4-a0a5-6d7f0f36c035 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:55.933587Z

Source-reported events for the cited work

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Observation aeaabf64-8447-4ba7-bfc7-c8eb9975c8a3 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 20

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Source-reported events for the cited work

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Observation fb516b74-a77b-4e23-bfec-6586408d4daa · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:56.122231Z

Source-reported events for the cited work

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Observation 657b5f7f-bbe0-4ff8-8fe8-1d5169a95163 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to- text transformer,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Exploring the limits of transfer learning with a unified text-to- text transformer,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.615961Z

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 a57bced4-5871-47f7-ab5c-06b8c8a85b68 · outbound

This paper cites LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:56.321335Z

Source-reported events for the cited work

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Observation 20309761-7744-4cec-a52f-8d48e61ff41e · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:56.429128Z

Source-reported events for the cited work

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Observation 0845c449-6ef0-47dc-926c-c39b1b25ddcf · outbound

This paper cites Qlora: Efficient fine- tuning of quantized llms,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Qlora: Efficient fine- tuning of quantized llms,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.523578Z

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 e1e9e9c6-d05f-4fc0-afcc-ce558b722729 · outbound

This paper cites Efficient fine-tuning of bert models on the edge,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Efficient fine-tuning of bert models on the edge,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.427281Z

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 ae79f3b4-2bb1-4f47-9bf3-611533647027 · outbound

This paper cites KronA: Parameter Efficient Tuning with Kronecker Adapter.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models KronA: Parameter Efficient Tuning with Kronecker Adapter

Reference 27

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Observation 77be7424-62ea-4223-9e45-eff2d9152b24 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 28

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Observation e91bdede-7018-40cb-b6cb-d4e37e1cbb0d · outbound

This paper cites Gpt under- stands, too,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Gpt under- stands, too,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.360184Z

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 bdd604d9-f30a-41d6-b851-712dc5ac77a0 · outbound

This paper cites DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:56.984753Z

Source-reported events for the cited work

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Observation 61e1fc3e-2278-4268-84bd-8b3801a2f69a · outbound

This paper cites Pre-trained models for natural language processing: A survey,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Pre-trained models for natural language processing: A survey,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.247631Z

Source-reported events for the cited work

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Observation c0c91efa-4d49-4eb9-84c3-dc29f7e3c41a · outbound

This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Sparsegpt: Massive language models can be accurately pruned in one-shot,

Reference 32

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Source-reported events for the cited work

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Observation e97925db-e852-4d2f-8edd-c1ab04d79807 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models A Simple and Effective Pruning Approach for Large Language Models

Reference 33

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Source-reported events for the cited work

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Observation 484685a3-1924-4953-847d-9ed7f5478ec7 · outbound

This paper cites Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.108206Z

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 36bfd8de-f8c2-4a01-ab36-f0d3724f9906 · outbound

This paper cites LLM-FP4: 4-Bit Floating-Point Quantized Transformers.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:57.403719Z

Source-reported events for the cited work

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Observation c7f62867-610e-4667-afb2-589ecf686dbb · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:57.511902Z

Source-reported events for the cited work

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Observation 82774ef6-98a6-4c22-984d-658b7ba796ba · outbound

This paper cites Deep residual learning for image recog- nition,.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Deep residual learning for image recog- nition,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:43:58.024900Z

Source-reported events for the cited work

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Observation 452e4000-a90a-450a-965c-a47a6691813d · outbound

This paper cites Layer Normalization.

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models Layer Normalization

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T22:43:57.676619Z

Source-reported events for the cited work

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Pith citing papers

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