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Paper Citation Record · LEDGER

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement

As of 17 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2607.18960.

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

pith.paper-citation-record.v1
2607.18960 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T13:54:05.024020Z

measured 29 of 29 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 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

29 of 29 outbound references displayed

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Outbound references

Observation b95a5126-7051-43c7-bcff-f81e33897d1f · outbound

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

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

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Observation 41c6742a-e423-46cc-93ac-efca76bf3314 · outbound

This paper cites A Survey on Data Selection for Language Models.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement A Survey on Data Selection for Language Models

Reference 2

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Observation de41c954-6a2b-4d73-94dd-c565d9f8b4e1 · outbound

This paper cites Prior work by the authors on trustworthy, cost-aware evaluation (anonymized for review), 2024.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Prior work by the authors on trustworthy, cost-aware evaluation (anonymized for review), 2024

Reference 3

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Observation 7e0b56ac-6dec-4c04-9d39-f750fa36888a · outbound

This paper cites an unresolved cited work.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-01T13:54:02.871204Z digest=sha256:504ebf72c4315283cde0e53bad4d8e5860d81e361003e478fcbcbcfa1e63ebb2

Observation fbf07f84-e4e4-41be-85f1-9f0fef4c3c2c · outbound

This paper cites Instruction Mining: Instruction Data Selection for Tuning Large Language Models.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Instruction Mining: Instruction Data Selection for Tuning Large Language Models

Reference 5

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Observation e614ccb0-5eb4-45e4-9b1f-8ebad73e9b4e · outbound

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

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement AlpaGasus: Training A Better Alpaca with Fewer Data

Reference 6

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source=pdf_text observed=2026-08-01T13:54:03.112678Z digest=sha256:d5eef0d064ba97f7c53955682eb7c665accea22c96552ba9d9edf02c8fd5924c

Observation 3df56901-6d62-4d81-8c96-2c2fe821f3df · outbound

This paper cites Free dolly: Introducing the world’s first truly open instruction-tuned LLM.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Free dolly: Introducing the world’s first truly open instruction-tuned LLM

Reference 7

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Observation 370e7085-f1ee-41d7-94ca-a432fc65aa2c · outbound

This paper cites Improving Factuality and Reasoning in Language Models through Multiagent Debate.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Improving Factuality and Reasoning in Language Models through Multiagent Debate

Reference 8

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source=pdf_text observed=2026-08-01T13:54:03.268339Z digest=sha256:1ab353955a1404e4ff2841182bc68c38a1b6794656f98ee4698ff4cc503dfb36

Observation 038affec-da2e-4b9d-b675-e50a39ff4282 · outbound

This paper cites Bootstrap methods: Another look at the jackknife.The Annals of Statistics, 7 (1):1–26, 1979.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Bootstrap methods: Another look at the jackknife.The Annals of Statistics, 7 (1):1–26, 1979

Reference 9

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source=pdf_text observed=2026-08-01T13:54:03.356611Z digest=sha256:5619ce52f5c495e4f77f423877c2615020cfcdc490857b241068fcfb47a9c500

Observation ebd6ebaa-1a70-40f7-93dc-4cc2bd63abbb · outbound

This paper cites Data Shapley: Equitable Valuation of Data for Machine Learning.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Data Shapley: Equitable Valuation of Data for Machine Learning

Reference 10

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Observation e249927a-13a6-4ebb-a407-85be2cedfa18 · outbound

This paper cites On Calibration of Modern Neural Networks.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement On Calibration of Modern Neural Networks

Reference 11

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Observation a19de177-05e0-40d5-b7ea-c07ddd24baa8 · outbound

This paper cites AI safety via debate.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement AI safety via debate

Reference 12

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source=pdf_text observed=2026-08-01T13:54:03.616526Z digest=sha256:8b910337dd98a3ec9f4f7daacf7d9e8604c59ec10784413ed9cdbe9d329dcc91

Observation d695697b-cfcf-4d00-9a02-1b2dcfd82b30 · outbound

This paper cites an unresolved cited work.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Unresolved cited work

Reference 13

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Observation 74e63264-5539-4f6c-b333-b19e91ad512f · outbound

This paper cites Deduplicating Training Data Makes Language Models Better.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Deduplicating Training Data Makes Language Models Better

Reference 14

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Observation 77b9def2-5c09-4433-9cca-407f5d1d7264 · outbound

This paper cites From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning

Reference 15

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Observation 6217ca62-c7a2-4254-bd40-b0f5091a4f82 · outbound

This paper cites Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning

Reference 16

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Observation fee19c79-4d2d-4247-867a-1eb3d023baaf · outbound

This paper cites What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning

Reference 17

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Observation 6b1b3ea1-4d22-4673-8109-42a6f2dd9b95 · outbound

This paper cites G- Eval: NLG evaluation using GPT-4 with better human alignment.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement G- Eval: NLG evaluation using GPT-4 with better human alignment

Reference 18

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Observation 2959688f-2eab-42c0-91fe-a0d86eaec9e9 · outbound

This paper cites #InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement #InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models

Reference 19

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Observation eaff4312-bd9b-4e3f-b71b-7ab7eae36275 · outbound

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

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Training language models to follow instructions with human feedback

Reference 20

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Observation 2e9fd5d5-910f-467f-a801-54427e977b73 · outbound

This paper cites Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 21

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Observation 19d2af3b-5f9f-4d0d-a703-6ab7e04dadf2 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 22

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source=pdf_text observed=2026-08-01T13:54:04.303172Z digest=sha256:3320e0b49c00039ffa773a1e60ea8ef39b5cb59fbd9ac3ef3a6d768edbacadcc

Observation 3f689e43-3a6a-4863-b4fc-d7417cdeb5d9 · outbound

This paper cites Sequential tests of statistical hypotheses.The Annals of Mathematical Statis- tics, 16(2):117–186, 1945.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Sequential tests of statistical hypotheses.The Annals of Mathematical Statis- tics, 16(2):117–186, 1945

Reference 23

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Observation 55145047-c47b-40e1-8c02-99ea9bb1876e · outbound

This paper cites Large Language Models are not Fair Evaluators.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Large Language Models are not Fair Evaluators

Reference 24

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Observation 3cdf685f-caba-40fc-9170-0b08af7ce6b6 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 25

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Observation ddeb428b-146e-445f-aff6-4c005300be4f · outbound

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

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Finetuned Language Models Are Zero-Shot Learners

Reference 26

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Observation e63d4bda-4454-415c-a0bb-8ea83f46789d · outbound

This paper cites an unresolved cited work.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Unresolved cited work

Reference 27

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source=pdf_text observed=2026-08-01T13:54:04.815061Z digest=sha256:9b051efb94d556d5ec56880660d161744906b3788f1305e36890ebf6d5165a9f

Observation 60d83086-a7ab-4fa3-b823-f143c2a8a699 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 28

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Observation 5352711e-912a-40b2-ab63-70f9e517d1cb · outbound

This paper cites LIMA: Less Is More for Alignment.

SFGA: A Statistics-First Gating Architecture with Adjudicative Escalation for Trustworthy SFT Data Procurement LIMA: Less Is More for Alignment

Reference 29

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Pith citing papers

No inbound Pith citation observations are available.