Paper Citation Record · LEDGER

Not All Documents Are What You Need for Extracting Instruction Tuning Data

As of 18 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2505.12250.

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

pith.paper-citation-record.v1
2505.12250 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:43:13.915044Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T12:48:30.924487Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T12:53:26.618560Z

Reference resolution

33 of 33 outbound references displayed

verified exact0
verified fuzzy1
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6602906-e52b-469d-9360-3531d8c39332 · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Not All Documents Are What You Need for Extracting Instruction Tuning Data SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.729971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3e62473-1d49-418c-a973-4dac8af74417 · outbound

This paper cites Program Synthesis with Large Language Models.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Program Synthesis with Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.748582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5b57ee1-54fe-42c7-824f-30dc34475484 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Evaluating Large Language Models Trained on Code

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.768551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5da0c9f9-434d-4b76-8567-cd104eba8285 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Training Verifiers to Solve Math Word Problems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.773958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b9de5a-888c-4c8c-8195-7ea457761618 · outbound

This paper cites The Llama 3 Herd of Models.

Not All Documents Are What You Need for Extracting Instruction Tuning Data The Llama 3 Herd of Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.784157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efcfbaf0-3e11-40bf-8c54-2069454a7871 · outbound

This paper cites Studying Large Language Model Generalization with Influence Functions.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Studying Large Language Model Generalization with Influence Functions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.789007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7241653-a153-4b9b-9628-d8f0e3441ec0 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Not All Documents Are What You Need for Extracting Instruction Tuning Data DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.794290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a08b84f6-1a06-409b-a874-bd08c80ecf11 · outbound

This paper cites Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.804403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 281f4d2e-11e3-4cd5-9fdb-b943e2a4a8e1 · outbound

This paper cites Crafting papers on machine learning.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Crafting papers on machine learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.809858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5750203d-54c9-4eb2-8be6-ebd140ff359a · outbound

This paper cites Rho-1: Not All Tokens Are What You Need.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Rho-1: Not All Tokens Are What You Need

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.820166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0dfc9cf-7d47-4759-9fb4-a67dacc76436 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

Not All Documents Are What You Need for Extracting Instruction Tuning Data WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.825867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0acbe243-223f-4f19-bf2c-5c8fe7b26eff · outbound

This paper cites When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale.

Not All Documents Are What You Need for Extracting Instruction Tuning Data When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.831274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4aa3767-e7a4-420c-a326-c2d832f2b2a4 · outbound

This paper cites an unresolved cited work.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:43:14.580714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 50eabc75-ed45-45f3-a43d-0353e15d3acc · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Not All Documents Are What You Need for Extracting Instruction Tuning Data DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.852956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c9a5681-c30a-4ed6-918c-1e4a80c69ad5 · outbound

This paper cites Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.858496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddb9dc0f-883d-4c83-9b94-21abf8613e4d · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Not All Documents Are What You Need for Extracting Instruction Tuning Data WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.869758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55ac9f04-d03d-42a6-af2b-c57328337921 · outbound

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

Not All Documents Are What You Need for Extracting Instruction Tuning Data Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.875206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f183bb08-936b-4da9-887b-22236c49e377 · outbound

This paper cites Qwen2.5 Technical Report.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Qwen2.5 Technical Report

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.881546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b88b24ed-2e3f-4ef0-a154-751d457ae736 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Not All Documents Are What You Need for Extracting Instruction Tuning Data MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.886766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4780d297-bb0f-4226-b312-8b81f5c1bbb3 · outbound

This paper cites MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models.

Not All Documents Are What You Need for Extracting Instruction Tuning Data MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.892154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c2dbf9d-1174-4c2b-98c8-bc82d436a3ff · outbound

This paper cites Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical Texts.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical Texts

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.903540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62a37cc4-9c2d-4d70-8a2e-4995827c4c8f · outbound

This paper cites Considering that the clustering results are easily affected by the parameters of clustering algorithms, we use different methods to select proper parameters.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Considering that the clustering results are easily affected by the parameters of clustering algorithms, we use different methods to select proper parameters

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:43:14.563275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f23d346a-21f6-465c-94ea-b62ffe20a6b6 · outbound

This paper cites an unresolved cited work.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:43:14.544331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d373bef5-b3e9-49a7-b232-780d62e39dfd · outbound

This paper cites Self-QA: Unsupervised Knowledge Guided Language Model Alignment.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Self-QA: Unsupervised Knowledge Guided Language Model Alignment

Reference 1996

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.897474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models.

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.

Observation 8e4ab66a-2763-4ed9-b765-d4a2c446974f · outbound

This paper cites Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.864143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e8b0ae8-25fd-4128-b1a1-9d061fe38468 · outbound

This paper cites AI-Assisted Generation of Difficult Math Questions.

Not All Documents Are What You Need for Extracting Instruction Tuning Data AI-Assisted Generation of Difficult Math Questions

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.847537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b39e715-7f62-4c5c-b4de-2839579c4149 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Measuring Mathematical Problem Solving With the MATH Dataset

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.799420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60fea339-bbba-4fcc-b85f-a87c3d3439ef · outbound

This paper cites AlpaGasus: Training A Better Alpaca with Fewer Data.

Not All Documents Are What You Need for Extracting Instruction Tuning Data AlpaGasus: Training A Better Alpaca with Fewer Data

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.762660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daa31a0f-cf37-4fa5-9cf9-2fa2b4a55f59 · outbound

This paper cites Language Models are Few-Shot Learners.

Not All Documents Are What You Need for Extracting Instruction Tuning Data Language Models are Few-Shot Learners

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.756689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e3fc2b0-9796-4ad8-8050-eb19a62fd705 · outbound

This paper cites The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only.

Not All Documents Are What You Need for Extracting Instruction Tuning Data The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.836838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd7d9ed1-0974-4372-8bc9-55cb8e5f4373 · outbound

This paper cites GPT-4 Technical Report.

Not All Documents Are What You Need for Extracting Instruction Tuning Data GPT-4 Technical Report

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.739986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b011e138-f35b-4cae-8503-7d02baf12a3c · outbound

This paper cites SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation.

Not All Documents Are What You Need for Extracting Instruction Tuning Data SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T20:43:13.779375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d05f04ab-5809-490b-a9e4-0349294d8cbb · inbound

DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation cites this paper.

DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation Not All Documents Are What You Need for Extracting Instruction Tuning Data

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:53:26.620895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.