Paper Citation Record · LEDGER

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models

As of 9 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2506.15021.

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

pith.paper-citation-record.v1
2506.15021 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:15:36.766601Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

43 of 43 outbound references displayed

verified exact1
verified fuzzy21
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2f6ea8e5-91f9-4ed8-9bef-c1eb274cb3d3 · outbound

This paper cites Language models are unsupervised multitask learners, 2019.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Language models are unsupervised multitask learners, 2019

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:33.334830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0af794cf-7079-4352-a7e5-d592d01402d3 · outbound

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

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Training language models to follow instructions with human feedback

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.322815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 90d6d3ec-593f-416a-8798-084b6717f7dd · outbound

This paper cites Llama: Open and efficient foundation language models, 2023.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Llama: Open and efficient foundation language models, 2023

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:33.511413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1f89571-40c8-4ca5-b607-d318470bdebc · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:33.633471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 639c38ff-6208-4c90-84fb-8a2a24bda692 · outbound

This paper cites LIMA: Less is more for alignment.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models LIMA: Less is more for alignment

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:33.744767Z

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Observation 0eb732b7-d282-465f-b157-e4328d374676 · outbound

This paper cites HelpSteer2: Open-source dataset for training top-performing reward models.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models HelpSteer2: Open-source dataset for training top-performing reward models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:33.902602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fd366d3-1af2-4a23-ad42-b8e4bf24da9c · outbound

This paper cites From quantity to quality: Boosting LLM performance with self- guided data selection for instruction tuning.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models From quantity to quality: Boosting LLM performance with self- guided data selection for instruction tuning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.282741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 16735af5-2458-4c1f-bc96-46dad00fd616 · outbound

This paper cites Hashimoto, and Percy Liang.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Hashimoto, and Percy Liang

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.157194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bedcebf7-efaf-426a-8ff7-ff46c6e11a8e · outbound

This paper cites Vicky Zhao, Lili Qiu, and Dongmei Zhang.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Vicky Zhao, Lili Qiu, and Dongmei Zhang

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.257528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 97c019cf-d445-45f6-b6bb-9652cfd16282 · outbound

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

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Rho-1: Not All Tokens Are What You Need

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.227513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cd78126-291e-4e3c-b688-61f557d5c45b · outbound

This paper cites Hashimoto.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Hashimoto

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.244752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9a7c82d-7b1d-4682-8dae-9330c5afceed · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.294300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1082ad26-eb27-4d1b-b308-b60ee3b04d18 · outbound

This paper cites Attention is not Explanation.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Attention is not Explanation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.330401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 628978c8-1aec-4325-a7eb-6c18888c27ef · outbound

This paper cites Attention is not not Explanation.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Attention is not not Explanation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.354768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6017cb32-3d7d-4c4d-bdb4-0f4955bb9c55 · outbound

This paper cites LLMLingua: Com- pressing prompts for accelerated inference of large language models.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models LLMLingua: Com- pressing prompts for accelerated inference of large language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.217331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7f63348b-0052-462d-97f9-f161c45f6086 · outbound

This paper cites LongLLMLingua: Accelerating and enhancing LLMs in long context scenarios via prompt compression.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models LongLLMLingua: Accelerating and enhancing LLMs in long context scenarios via prompt compression

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.207781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7fdd8e2a-c1ce-47ee-a5df-0cf52bf60596 · outbound

This paper cites Learning to compress prompts with gist tokens.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Learning to compress prompts with gist tokens

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.197157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 05b5fa50-e0c3-4e43-8a37-10eb6ad32660 · outbound

This paper cites annotator rationales.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models annotator rationales

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.186302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 66934d10-90fc-4ec8-a4cf-8db5e56752a3 · outbound

This paper cites Rationale-augmented convolutional neural networks for text classification.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Rationale-augmented convolutional neural networks for text classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.164185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4013b4fe-c364-4c58-ba68-e5d6aa9d7bc1 · outbound

This paper cites Deriving Machine Attention from Human Rationales.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Deriving Machine Attention from Human Rationales

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.464838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 387780ae-0d4a-46cc-9162-03445a2aadc5 · outbound

This paper cites Token-level adaptive training for neural machine translation.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Token-level adaptive training for neural machine translation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.143166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 129e3a54-3c76-41a9-a705-a18d51502a8c · outbound

This paper cites Re-weighting tokens: A simple and effective active learning strategy for named entity recognition.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Re-weighting tokens: A simple and effective active learning strategy for named entity recognition

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.115977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8e081174-01a3-4617-a931-699e27312db1 · outbound

This paper cites Not all tokens are what you need for pretraining.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Not all tokens are what you need for pretraining

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.052021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 35f638b4-407a-4229-83cb-773a97ec2c73 · outbound

This paper cites Does distributionally robust super- vised learning give robust classifiers? InInternational Conference on Machine Learning, pages 2029–2037.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Does distributionally robust super- vised learning give robust classifiers? InInternational Conference on Machine Learning, pages 2029–2037

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:39.010417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85731c0f-a266-40f5-ab77-a69ad2613c42 · outbound

This paper cites an unresolved cited work.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:15:38.984312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 515f7b46-6fea-40a8-aac8-340b8a84413c · outbound

This paper cites Distributionally robust losses against mixture covariate shifts.Under review, 2(1), 2019.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Distributionally robust losses against mixture covariate shifts.Under review, 2(1), 2019

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.915776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 178c12d1-c44a-4be2-8d2e-60cafa9060b2 · outbound

This paper cites Distribu- tionally robust logistic regression.Advances in neural information processing systems, 28, 2015.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Distribu- tionally robust logistic regression.Advances in neural information processing systems, 28, 2015

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.895202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a424a0b5-85a1-420a-9016-ab5ae0ee3c9e · outbound

This paper cites Variance-based regularization with convex objectives.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Variance-based regularization with convex objectives

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.880501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ee7ba7e4-15c7-4871-b17c-2133a14198f9 · outbound

This paper cites Hashimoto, and Percy Liang.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Hashimoto, and Percy Liang

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.863893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 84d85cf8-f229-4083-951b-0de24866c02f · outbound

This paper cites Compressing context to enhance inference efficiency of large language models.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Compressing context to enhance inference efficiency of large language models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.692811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9fdfc146-cab3-4569-aeb3-834d57ce1071 · outbound

This paper cites The Llama 3 Herd of Models.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models The Llama 3 Herd of Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:35.164840Z

Source-reported events for the cited work

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Observation 73a37d50-11c8-43e7-ac2f-b64813b90a97 · outbound

This paper cites Measuring massive multitask language understanding.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Measuring massive multitask language understanding

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:35.315441Z

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Unavailable: canonical work link unavailable.

Observation 6fe631a6-8938-4a29-99ed-70c8e4489aae · outbound

This paper cites MathQA: Towards interpretable math word problem solving with operation-based formalisms.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models MathQA: Towards interpretable math word problem solving with operation-based formalisms

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.445334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4514aa4f-339a-409f-bf46-6e236c49719f · outbound

This paper cites Think you have solved question answering? try arc, the ai2 reasoning challenge, 2018.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Think you have solved question answering? try arc, the ai2 reasoning challenge, 2018

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:35.615301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dca10006-b001-4e18-b4b9-e92bee60695c · outbound

This paper cites Can a suit of armor conduct electricity? a new dataset for open book question answering.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Can a suit of armor conduct electricity? a new dataset for open book question answering

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:35.755536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21b93b94-1700-4a91-83f5-c07973240670 · outbound

This paper cites an unresolved cited work.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Unresolved cited work

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:35.886334Z

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Unavailable: canonical work link unavailable.

Observation 0f7393c6-7966-4dae-ad50-6c1f481668e7 · outbound

This paper cites TruthfulQA: Measuring how models mimic human falsehoods.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models TruthfulQA: Measuring how models mimic human falsehoods

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:38.135311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2cdaf1e-283b-42cc-a19d-62ef6dae26a4 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Instruction-Following Evaluation for Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:36.225308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60e51883-83da-48d0-9cd7-c798f130e249 · outbound

This paper cites Decoupled weight decay regularization.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Decoupled weight decay regularization

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:36.340118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29619589-8854-4785-ac52-7b86065bf2c1 · outbound

This paper cites Nemirovski, A.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Nemirovski, A

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:37.897717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 70a7fca3-e630-46bc-bfa8-27532168b84b · outbound

This paper cites Learning to solve routing problems via distributionally robust optimization.Proceedings of the AAAI Conference on Artificial Intelligence, 36(9):9786–9794, Jun.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Learning to solve routing problems via distributionally robust optimization.Proceedings of the AAAI Conference on Artificial Intelligence, 36(9):9786–9794, Jun

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:15:37.617568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3140bc79-3da6-4062-a460-0eed0ea391bd · outbound

This paper cites Investigating Group Distributionally Robust Optimization for Deep Imbalanced Learning: A Case Study of Binary Tabular Data Classification.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Investigating Group Distributionally Robust Optimization for Deep Imbalanced Learning: A Case Study of Binary Tabular Data Classification

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:15:37.082762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 070e8d7b-3340-42d0-bbe5-28824f83265f · outbound

This paper cites an unresolved cited work.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Unresolved cited work

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.564754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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