Pith. sign in

Paper Citation Record · LEDGER

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models

As of 18 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2505.07846.

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

pith.paper-citation-record.v1
2505.07846 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:38:47.719414Z

measured 20 of 20 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

20 of 20 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 74a4ee3d-e3cd-4bc8-b2ff-f5fdf2502064 · outbound

This paper cites Concrete Problems in AI Safety.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Concrete Problems in AI Safety

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.644757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.644757Z digest=sha256:ea93d5c0bd4b9c8b8f53b79eb9282400a191a1982f6be3821a1d8898e2c8b6a5

Observation ce40c890-fc86-49da-a3e3-75833add6ba5 · outbound

This paper cites arXiv preprint (2024).

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models arXiv preprint (2024)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:38:47.962400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.649786Z digest=sha256:3ac54927bc2e0ce1ad1e357c83dd91cbd4fd46f9427c17bf9f13f26469237cae

Observation df69f904-beb4-4106-97af-4672cf51928f · outbound

This paper cites an unresolved cited work.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-15T23:38:47.951904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.653032Z digest=sha256:a3806fd3535d15f573a275306625b32873caa8697af60f9f5ca9769c879efc2c

Observation 3d02fa8d-4493-4bea-b744-61adf35b4421 · outbound

This paper cites OpenAI Blog (2016).

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models OpenAI Blog (2016)

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:38:47.940191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.656257Z digest=sha256:28a2fdf47ce3a9b4a6c0ce47309ba0f74061ba99fa76de6d539f24e07415026f

Observation 84f7275d-358f-470e-b425-3c3c03af6f93 · outbound

This paper cites Machine Learning 110(9), 2419–2468 (2021).

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Machine Learning 110(9), 2419–2468 (2021)

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:38:47.928278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.659857Z digest=sha256:d21a60c3426b82b298612bf070dffa19e435e336f360228511d79e5745eafcfc

Observation ce182035-b579-4b32-b604-81def3c69671 · outbound

This paper cites AGI Safety Literature Review.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models AGI Safety Literature Review

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.663206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.663206Z digest=sha256:7b8d7e0b3a7cf2db75b719d6baa3350b4fcc9da9cbbf6d961c7f645bb8a727e8

Observation 0d2ba8f9-034e-40a1-9963-32fff295183b · outbound

This paper cites Alignment faking in large language models.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Alignment faking in large language models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.667557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.667557Z digest=sha256:2144b9b0b954d048f2c71942cf803294095da652319c7959d158bb25352b6592

Observation 827234f4-52fb-4446-962d-4aaedcef1b92 · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.671533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.671533Z digest=sha256:d4a32f3743864a36311341c9c9ef4ccdec770154b82a89e35efdc20feb9b1ae4

Observation 91daad12-abe3-4410-90ed-77a445b796b5 · outbound

This paper cites an unresolved cited work.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-15T23:38:47.916232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.675276Z digest=sha256:860bd58cd019416cfd5620c8bd8abe9b2a9ed262e3732118c550d02f537d216b

Observation 2bee653f-9818-4781-883d-24c5d9fcc308 · outbound

This paper cites Artificial Life 26(2), 274–306 (2020).

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Artificial Life 26(2), 274–306 (2020)

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:38:47.905056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.678762Z digest=sha256:53ed2fa996e42ac163d5252f964d8cab7316f4196fdf42a92e3bfc3b318a57c8

Observation 1b926d21-bbe1-47ce-8be4-18f9098e2038 · outbound

This paper cites Sycophancy in Large Language Models: Causes and Mitigations.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Sycophancy in Large Language Models: Causes and Mitigations

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.682170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.682170Z digest=sha256:3d07d122d328829e5c54e89d48f24015034ff91754e7b594c8f781c7fd3fc555

Observation 1d1d8f6f-8bec-4ccf-a4f1-f92a939a456c · outbound

This paper cites Frontier Models are Capable of In-context Scheming.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Frontier Models are Capable of In-context Scheming

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.687048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.687048Z digest=sha256:ec18a37d7f6589c2b56c2095140b158070b52b190bb3bdf721785a39525d6b87

Observation fb33a99a-56e9-436b-864c-7b878b2e3aab · outbound

This paper cites METR Technical Report (2024).

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models METR Technical Report (2024)

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:38:47.893800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.691376Z digest=sha256:de097a4a7868339f3e7c1138e8a2341f1879e4c21d276ec7c4e2ef9b1049d83e

Observation 6f2c69fd-02e4-4b75-bfc2-96c83cc33b55 · outbound

This paper cites LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.695578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.695578Z digest=sha256:5c475c7f618a1b09bd13cbbdb843fd57094d4b0cc208aa2db3a8120a030cecba

Observation 7f1b8a99-c9c3-4718-9bd0-cbb3d6ee5358 · outbound

This paper cites Large Language Models can Strategically Deceive their Users when Put Under Pressure.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Large Language Models can Strategically Deceive their Users when Put Under Pressure

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.699617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.699617Z digest=sha256:53cc65d64cff712ea3cd8b747decd3c339493b69e98a32436c6b9f7cca2a1a1c

Observation 8fd15b43-0ff9-4c81-b923-a15576c728a8 · outbound

This paper cites Hacking CTFs with Plain Agents.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Hacking CTFs with Plain Agents

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.703644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.703644Z digest=sha256:ceed4fb7c1a9d40de58f2f7f7a311d8eb14bc67e15c3bebbe7fb7594af14ae5b

Observation 51597e0b-b3a0-4354-954e-69625c70ee25 · outbound

This paper cites Badllama 3: removing safety finetuning from Llama 3 in minutes.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Badllama 3: removing safety finetuning from Llama 3 in minutes

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.707598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.707598Z digest=sha256:1ea235cfcdd41ef93eb0dded25c98290081a4b3d79e15c253ef28614197680de

Observation fcee41c5-caa6-4df1-a157-056f52985aed · outbound

This paper cites AI Sandbagging: Language Models can Strategically Underperform on Evaluations.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models AI Sandbagging: Language Models can Strategically Underperform on Evaluations

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.711493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.711493Z digest=sha256:e3248ce917229f44803d5730405e74a2b415ef86f7d10bbae0f022a270f28fd4

Observation 5ac26c4b-aba5-44e5-8528-2581966b95c1 · outbound

This paper cites Nature 412(6844), 331–333 (2001).

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models Nature 412(6844), 331–333 (2001)

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:38:47.882647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T23:38:47.715643Z digest=sha256:84a37c32ae5040a75258538ecdbba4f580462ee9e5d7e96b16a998e8b224cb2b

Observation 9f181e63-96d6-488c-a14a-d9f7f38c2eed · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Winning at All Cost: A Small Environment for Eliciting Specification Gaming Behaviors in Large Language Models ReAct: Synergizing Reasoning and Acting in Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T23:38:47.719414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:38:47.719414Z digest=sha256:526b312818f59cab6d631009dbbeb1f4a9eea3730149756fc30db884be5ba59d

Pith citing papers

No inbound Pith citation observations are available.