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Paper Citation Record · LEDGER

Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2402.13064.

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

pith.paper-citation-record.v1
2402.13064 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:11.425233Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

6
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 31ef5c27-e38c-409e-ae2b-784d33696889 · inbound

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing cites this paper.

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 122

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:58:36.867815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-16T06:58:36.684583Z digest=sha256:22a6889341dc3e4455bbce8ead53dc93bf39e6e2666c1bf981a9a35b186514f7

Observation a5363019-76b0-4106-b145-e2e8ab7505a6 · inbound

On Domain-Adaptive Post-Training for Multimodal Large Language Models cites this paper.

On Domain-Adaptive Post-Training for Multimodal Large Language Models Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 27

Resolution
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no resolver link, observed 2026-08-12T05:56:46.767437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:56:46.767437Z digest=sha256:8dead220cfb72b39c72cfa8a95c0715b811e1e24f9e22bebb2d4910ec50bc606

Observation 75b51781-c29e-4c73-9188-0be6463c098a · inbound

Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models cites this paper.

Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T23:15:28.658554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:15:28.658554Z digest=sha256:4122999819ad6f967310e31f188b37b147b24f44ac8b9c3b8baf4e9437ae23bc

Observation 97e7064a-9418-43f8-a26a-526b3c3c1011 · inbound

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs cites this paper.

Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T13:19:18.856098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:19:18.856098Z digest=sha256:1d020672cedca215b3069eebf1471b5c9555750befdf9212bf189613040b3b26

Observation 65dee9d3-2a82-4d66-97b0-c95bde10bdf5 · inbound

Error-driven Data-efficient Large Multimodal Model Tuning cites this paper.

Error-driven Data-efficient Large Multimodal Model Tuning Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T11:18:32.254372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:18:32.254372Z digest=sha256:0c2446238ea5b3ec2292b64ca6cfb6fe98363074144fbd31bb9c3d04071e4d44

Observation ad0bbefc-fcc4-4f1d-9528-452f1ee06d59 · inbound

SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval cites this paper.

SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-11T05:44:00.074605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:44:00.074605Z digest=sha256:0029a1300580900df7061ca8c803b26d2e3a0d3eb3453ee2466defd737a0cb8a

Observation 6658b62d-5d68-4546-95a3-41aced3d8cd2 · inbound

Dynamic Skill Adaptation for Large Language Models cites this paper.

Dynamic Skill Adaptation for Large Language Models Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T00:46:46.160435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T00:46:46.160435Z digest=sha256:e8306d94265092f76fb864b9aab115f1c42c80b68ca40dca4f4a7d90c65c103e

Observation ad83ca62-2faf-4322-a6ce-f1663ac1092c · inbound

CDS: Knowledge Component-Driven Data Synthesis Guided by Cognitive Diagnosis Theory cites this paper.

CDS: Knowledge Component-Driven Data Synthesis Guided by Cognitive Diagnosis Theory Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 30

Resolution
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no resolver link, observed 2026-08-10T20:44:16.961286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:44:16.961286Z digest=sha256:14ed4740bee67504240af62ee85512f4c91b570722645a9a6bb5c53fcf8030e4

Observation cc3e0641-29de-4be8-840d-f60605e50ff6 · inbound

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas cites this paper.

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T14:21:24.299738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:21:24.299738Z digest=sha256:dc29c6f5ffa23fec16b91000626c755e990dd5ca95120999c42a5662f33141dc

Observation 7eb51fd3-ac6b-4258-a53e-044a59a13164 · inbound

BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation cites this paper.

BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-09T17:09:15.310446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:09:15.310446Z digest=sha256:e380e8a9e74bb11654455737dc4318ec233537cdcd4a5c36973aead7372a70cd

Observation 88bc9405-a1a7-4593-9702-1da4fb289031 · inbound

Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis cites this paper.

Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T00:35:28.348980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T00:35:28.348980Z digest=sha256:38955368b5579cf2f895e86d147cf1e3644cecbcb5577913e6ac74658a81be7a

Observation 7204a90f-386b-4166-93dd-62ddf431492e · inbound

BitNet b1.58 2B4T Technical Report cites this paper.

BitNet b1.58 2B4T Technical Report Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T12:40:11.425233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:40:11.425233Z digest=sha256:d488ebb6869a5209304cbeedbe0eb2e0fd123969010098b8ba86c39acb018be0

Observation 2006ae02-6ebc-4302-bcd2-01a55b8db215 · inbound

Instruction-Tuning Data Synthesis from Scratch via Web Reconstruction cites this paper.

Instruction-Tuning Data Synthesis from Scratch via Web Reconstruction Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:39.036534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:25:39.036534Z digest=sha256:da84d3d7e575e756e8dfd37011ac62180f4fce96f3fdde823ae0993e52eb5bde

Observation a04222cf-3500-4a2b-9b50-43e16e5584c2 · inbound

Not All Documents Are What You Need for Extracting Instruction Tuning Data cites this paper.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 2000

Resolution
unresolved
no resolver link, observed 2026-08-15T20:43:13.814947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:43:13.814947Z digest=sha256:ff902fd2ab37fbfb6de0a99208651f6d1be2d0d5dc28435458d840a8ed13ba5d

Observation 0fe56072-f9ae-47de-be6a-3ad2ccabe180 · inbound

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training cites this paper.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-07T15:36:06.387394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.387394Z digest=sha256:295491cba6584472a252bf09e7a7b02875313a075166a1c47ca12ba8b67da8b4

Observation 704475c2-887a-4818-b96d-c4cba4812de1 · inbound

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition cites this paper.

From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:56.193027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:55:56.193027Z digest=sha256:695f43de5121c681a0dd1cdf16ea5d4dfa5d6454ec92dcc1117e6dba1cbf4306

Observation ec0fa2b8-00f5-47c1-92a2-f2e344fc4838 · inbound

LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions cites this paper.

LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 21

Resolution
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no resolver link, observed 2026-08-07T15:08:01.395403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:08:01.395403Z digest=sha256:f4008e428bb96311ef7c721593266d7381c12cd1aa185a0c67edbe65d9766f1c

Observation b790690c-61ee-415c-9f9a-b3c4f5c578f9 · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 233

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:13.339084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:13.339084Z digest=sha256:ba1b8f18924970aaa2e83fc34cfac129460835360ea81d2fd8f0a6d442ed909c

Observation dcb59c4d-3e81-407a-8581-e3209625dafb · inbound

Towards Efficient and Effective Alignment of Large Language Models cites this paper.

Towards Efficient and Effective Alignment of Large Language Models Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-07T04:55:42.739229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:55:42.739229Z digest=sha256:74454095dd5ce8a1829055e82bdf3a82e6b5d8a8c11124d10dcd6bdf101e65a9

Observation 3cd5493f-36d7-4ae2-8303-85f2a30d3ae6 · inbound

ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated Data cites this paper.

ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated Data Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T21:45:08.835776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:45:08.835776Z digest=sha256:c711b0ec86879bb2e3978b58e9e81a82ce4789f20fae15842a58fd400afa94a7

Observation 4c64e082-2e08-45e6-9d38-ef2059504d45 · inbound

A Penalty Goes a Long Way: Measuring Lexical Diversity in Synthetic Texts Under Prompt-Influenced Length Variations cites this paper.

A Penalty Goes a Long Way: Measuring Lexical Diversity in Synthetic Texts Under Prompt-Influenced Length Variations Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T15:46:27.777433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:46:27.777433Z digest=sha256:ebbf441f2660e8cffd71d5d5f41a23247883b2e930b07bf5e507fac29e7386ee

Observation 38c95821-9801-48c7-af24-261acf5f0d59 · inbound

Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation cites this paper.

Icon$^{2}$: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T16:26:28.168263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:26:28.168263Z digest=sha256:96541650c385108ca8206479dc71bf4029211ed20d879c7e2934ebf8d76ed1e6

Observation 8d0b2850-2a9e-456a-98cc-6f8d8e6047de · inbound

Dynamic Context Evolution for Scalable Synthetic Data Generation cites this paper.

Dynamic Context Evolution for Scalable Synthetic Data Generation Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:45:49.278427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-10T18:21:39.397025Z digest=sha256:7940d6a80df8b17aa32406ea6303ce921347ad8f43d948a15ac9bcf69927474a

Observation bb9bc8b7-9e48-47fb-95fe-e9f26490fb67 · inbound

SkillGen: Verified Inference-Time Agent Skill Synthesis cites this paper.

SkillGen: Verified Inference-Time Agent Skill Synthesis Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:17:23.031201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T06:14:28.614825Z digest=sha256:0a93c0e31f4fb0f6f4a9f8be82c9d94e6c126491775ed7450f6d5d7e328765e9

Observation 96a6c1b8-71c8-4d23-ac3a-2d140935a916 · inbound

Natural Language Access Control (NLAC): From Help Desk Requests to Structured Policies cites this paper.

Natural Language Access Control (NLAC): From Help Desk Requests to Structured Policies Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-06-27T23:11:23.350215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T23:06:28.344952Z digest=sha256:d832d1af95cfe55b63e8378658afa607d0f4458d4979bb35060d592371eabf9f

Observation f1225e66-6fc0-42f7-b2a3-e2e141698b3a · inbound

NexForge: Scaling Agent Capabilities through Requirement-Driven Task Synthesis for LLMs cites this paper.

NexForge: Scaling Agent Capabilities through Requirement-Driven Task Synthesis for LLMs Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 2

Resolution
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no resolver link, observed 2026-08-02T03:19:10.315673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T03:19:10.315673Z digest=sha256:1b02aadfb93e4a7acd5efec20efbab9c86e8310e21dc5a3ce2937318e57110e1

Observation 751755c6-17ab-4f26-bf4f-a0fe7c843f44 · inbound

NexForge: Scaling Agent Capabilities through Requirement-Driven Task Synthesis for LLMs cites this paper.

NexForge: Scaling Agent Capabilities through Requirement-Driven Task Synthesis for LLMs Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T01:44:29.310845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T01:44:29.310845Z digest=sha256:9b4ea69a11b8119ddf0436f2c26828c620d30ad58934a780854ed578ae752541

Observation 14c5d5b0-4ade-4836-ac70-db729f8f6741 · inbound

GLAN-QnA-KR: A Seedless Taxonomy-Driven Korean Instruction Corpus cites this paper.

GLAN-QnA-KR: A Seedless Taxonomy-Driven Korean Instruction Corpus Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 7

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unresolved
no resolver link, observed 2026-08-02T14:15:04.912225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:15:04.912225Z digest=sha256:7aa189097cf4c8606c731fd4a17d7500d8060e8756f56e5be811d1e13e1108e3

Observation e5bc8b1f-e35b-47da-ac07-0b7270d488f7 · inbound

Search Hardness-Aware LLM-Based Problem Formulation for Expensive Simulation-Driven Design cites this paper.

Search Hardness-Aware LLM-Based Problem Formulation for Expensive Simulation-Driven Design Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 16

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unresolved
no resolver link, observed 2026-08-01T08:09:44.836796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T08:09:44.836796Z digest=sha256:c0d96188d07e2642f9d1fab5ee1c35d4c870a34592e9dfa0032f5b90c7dee125

Observation 2a521d71-510a-40a0-b92c-d0ab076ca402 · inbound

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs cites this paper.

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 35

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no resolver link, observed 2026-08-01T08:29:25.473575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T08:29:25.473575Z digest=sha256:cce75c3c292e0e94cbae493a5926a8c708a4a9a90071a071d7d3fdcab4df7368