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Paper Citation Record · LEDGER

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2505.18488.

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

pith.paper-citation-record.v1
2505.18488 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:34:05.688455Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T05:59:28.574238Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

  • verified exact2
  • verified fuzzy17
  • unresolved16
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 593da6f7-c06c-4204-8ae3-4705e869abc8 · outbound

This paper cites JAX: composable transformations of Python+NumPy programs, 2018.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications JAX: composable transformations of Python+NumPy programs, 2018

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 86200cf7-bdff-4e0c-848c-77549305b4b9 · outbound

This paper cites Automatic annotation and evaluation of error types for grammatical error correction.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Automatic annotation and evaluation of error types for grammatical error correction

Reference 2

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source=pdf_text observed=2026-08-07T14:34:02.151068Z digest=sha256:d13e0435b0af14ffee48c9848989b195338c3168d322059fc59a887cfe935480

Observation 3cea0987-ca2e-4352-a5ca-b67be7329e8d · outbound

This paper cites Grammatical error correction: A survey of the state of the art.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Grammatical error correction: A survey of the state of the art

Reference 3

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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.

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Observation 2e18f9ef-51d8-47b9-b73f-6fb9b43013c3 · outbound

This paper cites Heterogeneous low-rank approximation for federated fine-tuning of on-device foundation models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Heterogeneous low-rank approximation for federated fine-tuning of on-device foundation models

Reference 4

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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.

source=pdf_text observed=2026-08-07T14:34:02.393754Z digest=sha256:f3052b17d055ee3a754f9a8bd829bc0057f4ff4fefa8eff8613665a8ce8319fd

Observation 694ee2d5-2812-44b0-9b52-dd1b171f0d6f · outbound

This paper cites (amplified) banded matrix factorization: A unified approach to private training.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications (amplified) banded matrix factorization: A unified approach to private training

Reference 5

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raw_fallback, observed 2026-08-07T14:34:09.126884Z

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.

source=pdf_text observed=2026-08-07T14:34:02.498530Z digest=sha256:c20fa93c7c96229930fb56867c9d4dd4085f7642ea1cae644af71ff927bc0754

Observation 8ce1c806-f3a2-4ad1-a9e4-2a4a6397dc3b · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Scaling Instruction-Finetuned Language Models

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:02.586471Z digest=sha256:e4b7d0c95d599db06215c8fd2ef3ec06bc15a578e2fc2a8218618e2b36d021b2

Observation b7f6044b-645a-4d5b-9097-39e727abf29b · outbound

This paper cites Federated learning in practice: reflections and projections.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Federated learning in practice: reflections and projections

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:09.013638Z

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.

source=pdf_text observed=2026-08-07T14:34:02.674487Z digest=sha256:b04d8366794efe9ebb043c55ea889a907e63ef6d5888d4d0e04fb4fc549372c3

Observation 284eea6d-2606-4289-b569-28e0315b0b1e · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Gemini: A Family of Highly Capable Multimodal Models

Reference 8

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Observation 2643e3e1-2b42-4c7f-97c1-3fd1225b8eb2 · outbound

This paper cites Apple intelligence foundation language models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Apple intelligence foundation language models

Reference 9

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no resolver link, observed 2026-08-07T14:34:02.934143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:02.934143Z digest=sha256:9e1435e615fee10d0e3c37bbd4f7d42260df1a70f978dd5ea84ca6319d2cd54b

Observation 0998e762-0463-4060-abb4-7a1d5a399188 · outbound

This paper cites Federated Learning for Mobile Keyboard Prediction.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Federated Learning for Mobile Keyboard Prediction

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:03.025591Z digest=sha256:44896d5d7dcb012af0937e7b9bc2b2fcb060f016b9eccf0b9f48e8602a00729b

Observation 1ca73f28-31e1-4f5c-9b77-40b46737b0c2 · outbound

This paper cites Pre-text: Training language models on private federated data in the age of llms.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Pre-text: Training language models on private federated data in the age of llms

Reference 11

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verified fuzzy
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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.

source=pdf_text observed=2026-08-07T14:34:03.142128Z digest=sha256:03f9ebb7ca4d445228340981b00cf76873f6d122892c04352098e9d5bfb3aef6

Observation 67e5822f-9eea-4b5a-9e6f-682726f83637 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Lora: Low-rank adaptation of large language models

Reference 12

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no resolver link, observed 2026-08-07T14:34:03.267550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:03.267550Z digest=sha256:3e617e2c8df0d42e2562a3420f1dad240a3d88a1391caed734b0460b0f2ebb27

Observation 15879489-9d1b-4ee6-8e02-780f01a964d5 · outbound

This paper cites User inference attacks on large language models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications User inference attacks on large language models

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:08.750981Z

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.

source=pdf_text observed=2026-08-07T14:34:03.403062Z digest=sha256:7c1fe91d51ca6486121f86a3126f76c4f635d1210cf6035e51a1abe5194c4c5a

Observation 66ce17f6-322d-475e-a918-552dcd5d40a0 · outbound

This paper cites Harnessing large-language models to generate private synthetic text.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Harnessing large-language models to generate private synthetic text

Reference 14

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unresolved
no resolver link, observed 2026-08-07T14:34:03.541612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:03.541612Z digest=sha256:6382bc19b4cdc105e107f555a52c4dac5fbc811df6b062f6e1b234297667a3c9

Observation 02742b9f-661b-4968-9f2f-a13425b18aea · outbound

This paper cites Gecko: Versatile Text Embeddings Distilled from Large Language Models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Gecko: Versatile Text Embeddings Distilled from Large Language Models

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:03.634036Z digest=sha256:5301f262cbad16d6d86404c5c56d56dacf1218991e7cd09a565ae9c98919b984

Observation 92a55cdb-cf6f-4beb-a012-df6871b57438 · outbound

This paper cites Data weighted training strategies for grammatical error correction.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Data weighted training strategies for grammatical error correction

Reference 16

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verified fuzzy
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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.

source=pdf_text observed=2026-08-07T14:34:03.777290Z digest=sha256:3f5d5d6f35174d052a9a924eb3d59ab09674638b1bf7fb1090cb3fc944163ac9

Observation 7ecf585a-65b5-4750-b6f6-1986de049449 · outbound

This paper cites Tuning language models by proxy.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Tuning language models by proxy

Reference 17

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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.

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Observation 13cfd7d2-0b65-4db4-83aa-4d4430dfa952 · outbound

This paper cites Proofread: Fixes all errors with one tap.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Proofread: Fixes all errors with one tap

Reference 18

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no resolver link, observed 2026-08-07T14:34:03.947864Z

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Unavailable: canonical work link unavailable.

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Observation bf3c986a-d252-4a2b-ae88-c0dc5e0caa04 · outbound

This paper cites A hassle-free algorithm for strong differential privacy in federated learning systems.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications A hassle-free algorithm for strong differential privacy in federated learning systems

Reference 19

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raw_fallback, observed 2026-08-07T14:34:08.368449Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:34:04.062945Z digest=sha256:20ddd2692cc0ddcaa549f438cf58fdfbe1e4896980651033617b21cca95d6c2e

Observation 2f65e6fa-bb89-4b13-b2db-7278420c6228 · outbound

This paper cites The llama 3 herd of models, 2024.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications The llama 3 herd of models, 2024

Reference 20

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raw_fallback, observed 2026-08-07T14:34:08.226668Z

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.

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Observation ca0fa702-90b5-4341-b5ed-2df30c2cce97 · outbound

This paper cites GPT-4 Technical Report.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications GPT-4 Technical Report

Reference 21

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source=pdf_text observed=2026-08-07T14:34:04.250036Z digest=sha256:d58e90f674de348b2ae06a53539fcdf7301fc3577f2838ea27e796b9b0df8bf9

Observation 18d8aaa9-d2b4-4833-894a-c18dedf6a3a0 · outbound

This paper cites Training language models to follow instructions with human feedback.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Training language models to follow instructions with human feedback

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:07.988299Z

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.

source=pdf_text observed=2026-08-07T14:34:04.298102Z digest=sha256:bac0b48c2f279aaf97eb5a2e541cfb502239d7b779d3738b793ba2e59b8ba744

Observation 1f47acb8-7b24-4bad-aedc-ebc4367a9e40 · outbound

This paper cites Mobile Keyboard Input Decoding with Finite-State Transducers.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Mobile Keyboard Input Decoding with Finite-State Transducers

Reference 23

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no resolver link, observed 2026-08-07T14:34:04.356232Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:04.356232Z digest=sha256:b8ce31d953453eebff225b4dbd566da7757ac701c4ab6719cae84f8784c67f99

Observation 9a97a7dc-38d2-4628-b95a-668324c55b92 · outbound

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

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:04.459078Z digest=sha256:af09d41d90046d28c84cd70038db3d66bca8d2e4b216a2b5b5fe511022c2355e

Observation d296e257-0476-41b9-ab67-bb22f86d84db · outbound

This paper cites Simulating Errors in Touchscreen Typing.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Simulating Errors in Touchscreen Typing

Reference 25

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local_arxiv, observed 2026-08-07T14:34:06.258750Z

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.

source=pdf_text observed=2026-08-07T14:34:04.537762Z digest=sha256:511d6359abb98ef57c1122b51fa6b7a445d62df2a80efd43ec12e5b79c0a7404

Observation 582d6041-d1f3-4995-b91c-3a990ccc7c2b · outbound

This paper cites Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption Models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption Models

Reference 26

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verified exact
local_arxiv, observed 2026-08-07T14:34:06.032408Z

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.

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Observation f3f79d0a-f524-47f9-8efc-abf3329f467b · outbound

This paper cites Synthesizing privacy- preserving text data via finetuning without finetuning billion-scale llms.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Synthesizing privacy- preserving text data via finetuning without finetuning billion-scale llms

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:07.840904Z

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.

source=pdf_text observed=2026-08-07T14:34:04.742388Z digest=sha256:f8a7c027a0be8d76a2e183ddcc5e8abfb47f056fa84bafe51a07a6e0cbc241f3

Observation 38233443-b442-4b9d-b6b3-20f8edac88a1 · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Finetuned Language Models Are Zero-Shot Learners

Reference 28

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no resolver link, observed 2026-08-07T14:34:04.858666Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:04.858666Z digest=sha256:800a338685f6790f5266898923a042bc3b5fec0fe0e000867ccd94bac1b4621b

Observation ee27af1e-9f1b-45c6-ae44-5825f6beae7e · outbound

This paper cites Emergent Abilities of Large Language Models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Emergent Abilities of Large Language Models

Reference 29

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no resolver link, observed 2026-08-07T14:34:05.033753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:05.033753Z digest=sha256:9a9b1149797d1cfa39e340dd818e0e99b78cc489a8106542f14905a3624eccd6

Observation 2c6a3855-d7c8-4032-85cd-5f28374694e7 · outbound

This paper cites Prompt public large language models to synthesize data for private on-device applications.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Prompt public large language models to synthesize data for private on-device applications

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:07.684628Z

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.

source=pdf_text observed=2026-08-07T14:34:05.141449Z digest=sha256:115fb5e717e179ae5f7dd083e4cfe3c21bfc85151fdc3c099197ce804aa490e3

Observation f89f320a-1bdc-4b29-a59b-ac7b50c6f699 · outbound

This paper cites Differentially private synthetic data via foundation model apis 2: Text.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Differentially private synthetic data via foundation model apis 2: Text

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:07.338349Z

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.

source=pdf_text observed=2026-08-07T14:34:05.233295Z digest=sha256:4bcf2284453d89286bba52a4b186be60974b223e0085e6479e1487f325c9c896

Observation fd02c8af-b4bc-4e51-a15d-1eefca51f100 · outbound

This paper cites Federated learning of gboard language models with differential privacy.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Federated learning of gboard language models with differential privacy

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:07.122300Z

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.

source=pdf_text observed=2026-08-07T14:34:05.372881Z digest=sha256:5fe73e9438f615f7fbfdcbe63ff2eb3cce10fa2307c6ce65497183137d6f5694

Observation 94e1427f-00a9-4e10-a4d3-455fd20a3cf3 · outbound

This paper cites Privacy-preserving instructions for aligning large language models.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Privacy-preserving instructions for aligning large language models

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T14:34:06.855829Z

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.

source=pdf_text observed=2026-08-07T14:34:05.491094Z digest=sha256:098cf9f9eb2778c56024c8f80c72117a422fbab1f5d98777e0f1d2cbbfd136a7

Observation a1093cfc-1c46-4b03-aec3-7361b259e4eb · outbound

This paper cites Synthetic text generation with differential privacy: A simple and practical recipe.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Synthetic text generation with differential privacy: A simple and practical recipe

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:34:06.665284Z

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.

source=pdf_text observed=2026-08-07T14:34:05.588772Z digest=sha256:ae8d6a99401a3a03b11aa1c8532f1c58b315ee42259b31d4ab86aac08c485584

Observation 8b67bda6-6649-49ba-900a-fd5613af59bc · outbound

This paper cites Towards an On-device Agent for Text Rewriting.

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications Towards an On-device Agent for Text Rewriting

Reference 35

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unresolved
no resolver link, observed 2026-08-07T14:34:05.688455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:05.688455Z digest=sha256:2b58b14467b485f752ef26d4c5a13dd6f7bcb70fc7655d63d1489fb2ffd11e84

Pith citing papers

Observation 639e12c0-b0d7-48a7-a377-343db4683012 · inbound

MAPLE: Metadata Augmented Private Language Evolution cites this paper.

MAPLE: Metadata Augmented Private Language Evolution Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications

Reference 18

Resolution
unresolved
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