Pith. sign in

Paper Citation Record · LEDGER

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M

As of 8 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2509.09055.

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

pith.paper-citation-record.v1
2509.09055 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:48:23.200455Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

10 of 10 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e05c4997-8370-41ed-bce8-eefa7f93d9e5 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.384196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.384196Z digest=sha256:cca7af8bfbd6d2b1f13bfd9fc8d9504a08699c2bb0869f8f62515a87d785d1e5

Observation 713eddfd-fe4b-429b-a5e1-ddcdc75da528 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M OPT: Open Pre-trained Transformer Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.457324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.457324Z digest=sha256:04fb45895ceebad6a95580de9b84e8ae4f4595d56d4b4531df5d1988a82dc5de

Observation b1d66f49-ccf2-4d08-be9e-eaccbf368904 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.569427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.569427Z digest=sha256:7d6736342b509e76ad91f63b253b1edbf919c012619bbccd7d37f4ae3436af94

Observation 2a73cc95-c9ce-4d0c-a535-f8894b8213b0 · outbound

This paper cites How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.658957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.658957Z digest=sha256:cd92724e85a44c5275ea86bf2a3557cdf76656dbfec2b8cabbe64a19b345566d

Observation 7740676d-a93a-4607-ba59-16987e2cb33d · outbound

This paper cites Realistic Evaluation of Toxicity in Large Language Models.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Realistic Evaluation of Toxicity in Large Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.761053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.761053Z digest=sha256:1198bad000e2c328e32478f451ec508723465aa20639f1b0ade27d2825ad767d

Observation 40651299-5700-4120-a563-dfeaa452eef7 · outbound

This paper cites Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.847237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.847237Z digest=sha256:6d87d18da220ed650918419936e32e804856c0947d628d7cccc417c239d1663b

Observation 91451675-098c-4626-8d54-ab661566828f · outbound

This paper cites Dynabench: Rethinking Benchmarking in NLP.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Dynabench: Rethinking Benchmarking in NLP

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:22.922729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:22.922729Z digest=sha256:10427547e92f2cd630f6665a9920f80e3f7d23881d84d6cdd97401f688dfb276

Observation ced9a9ae-fd1e-4e8f-b6bd-6c8b837f7175 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Fine-Tuning Language Models from Human Preferences

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:23.005157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:23.005157Z digest=sha256:7546265e535f06c7ce08064eede8ec5b4c65043332dc4151ae31eddaad2ca686

Observation 4adc5a6b-4463-4caf-831a-8f4ac4bf5faa · outbound

This paper cites Red Teaming Language Models with Language Models.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Red Teaming Language Models with Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:23.101317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:23.101317Z digest=sha256:6ab59344ebac16e01c61855b2189874fc03a5cb6a41c22cc1e1941480b0d3616

Observation 98b8aa4c-6825-4719-a95a-f90b96b1c0e0 · outbound

This paper cites Insights into Alignment: Evaluating DPO and its Variants Across Multiple Tasks.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M Insights into Alignment: Evaluating DPO and its Variants Across Multiple Tasks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T19:48:23.200455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:48:23.200455Z digest=sha256:855aad13d92b49f9876530b6baeac9205a9a601bf562c914f19ce89dbcd4c1c0

Pith citing papers

No inbound Pith citation observations are available.