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Paper Citation Record · LEDGER

Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2503.20807.

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

pith.paper-citation-record.v1
2503.20807 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:39:02.165360Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T08:25:33.133716Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 39da5403-40f6-4d78-85f8-53acdaf25241 · inbound

Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning cites this paper.

Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T04:39:02.165360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:39:02.165360Z digest=sha256:82441f23c08e63021a409edc8eaa48e65678c662dc9d99908e6f6eba593d91ee

Observation a94f89f0-6f8a-4e3c-8a54-48347b233e42 · inbound

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation cites this paper.

MGC: A Compiler Framework Exploiting Compositional Blindness in Aligned LLMs for Malware Generation Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T20:45:53.256752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:45:53.256752Z digest=sha256:8f543f84643c891b421c54ba2a3b2f56623eaca6f4071468acd893e2efa088a9

Observation bd4afc7b-fa79-48ba-8e05-a5e2111d8659 · inbound

The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systems cites this paper.

The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systems Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T20:43:17.054377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:43:17.054377Z digest=sha256:3ac96a18b0fb100c0672692750a39a7069c4c067baf4f3229383df9dfaeaf015

Observation 94c9e1d4-5c84-47b2-b681-6432ad745347 · inbound

SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems cites this paper.

SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T18:28:42.095587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:28:42.095587Z digest=sha256:4d2320482737328bcc9eb94520c30165ddbb0a0cade76d1ada8c15922a236f11

Observation 7c230880-3385-43e3-8533-e11278fc4f3f · inbound

SATORI: Static Test Oracle Generation for REST APIs cites this paper.

SATORI: Static Test Oracle Generation for REST APIs Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-05T17:26:48.603348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:26:48.603348Z digest=sha256:ba00e7faf876b48ab575dfe09be1964b254f8c36431730d0980d406ab82de205

Observation 3107c52a-dcc4-49bd-bf8e-ffbe921079db · inbound

Learning to Stay Safe: Adaptive Regularization Against Safety Degradation during Fine-Tuning cites this paper.

Learning to Stay Safe: Adaptive Regularization Against Safety Degradation during Fine-Tuning Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T20:56:37.297488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T20:51:57.399260Z digest=sha256:6b47cd0a52404c495950a6a293bb2fb42cb4b082844948c468fa10f9352f3fb3

Observation 00d9cc25-c853-451b-84e9-ad4052653782 · inbound

From Parameter Dynamics to Risk Scoring : Quantifying Sample-Level Safety Degradation in LLM Fine-tuning cites this paper.

From Parameter Dynamics to Risk Scoring : Quantifying Sample-Level Safety Degradation in LLM Fine-tuning Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:45:44.182263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T18:08:11.122577Z digest=sha256:5dab6c16ffe7461b0318bc1713125f7c0c22f61d0200b5480b38fbcbc51d0b30

Observation 7b53cd25-bba3-46a8-aa58-7d927f3c01ed · inbound

The Deterministic Horizon: Impossibility Results as Design Specifications for Trustworthy AI Systems cites this paper.

The Deterministic Horizon: Impossibility Results as Design Specifications for Trustworthy AI Systems Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:30:22.757248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T05:29:39.640753Z digest=sha256:69a072c92531d4ee299b84011fd329d2bda3e4e10d9396e3a874e1d062ef3127

Observation 8d9c324b-6d11-41f9-9b30-8f284c9a2d0b · inbound

Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training cites this paper.

Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:25:33.136615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-01T08:21:41.008505Z digest=sha256:9827572bde000d87f4bf85fb4445fbc5955a07f81d86cc3d8ab2d3188f76fcec

Observation 0041fc41-573d-4f99-b5e7-10a2dcf71261 · inbound

Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training cites this paper.

Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-14T19:20:54.974570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T19:20:54.974570Z digest=sha256:a904dacbdd193294c9ac0bdc081d6fca13bbc84e01f25094582d7dd7bc546791