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Paper Citation Record · LEDGER

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs

As of 14 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2608.08542.

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

pith.paper-citation-record.v1
2608.08542 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:46:16.031718Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

39 of 39 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

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Outbound references

Observation ea4a5626-c8c3-4e70-8829-b18cfd35a061 · outbound

This paper cites SafeMERGE head-to-head (main paper§7).We compare against the selective-layer baseline Safe- MERGE (Djuhera et al.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs SafeMERGE head-to-head (main paper§7).We compare against the selective-layer baseline Safe- MERGE (Djuhera et al

Reference 1

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-14T04:46:16.031718Z digest=sha256:112bcd8012ee6bdd078e523e1308e501dc72626282483df92640ba31a6005c1c

Observation 5b9e2e57-c5aa-42e1-ac6f-76b9d5c56953 · outbound

This paper cites Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic

Reference 3

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source=pdf_text observed=2026-08-14T04:46:15.901261Z digest=sha256:7cb254249ab6fcfe11501a6b27d28c070ad05806e3a9217aebe3a70aa3d0661b

Observation 15b2f3a2-c95f-4eb2-b658-4266ccfd58fb · outbound

This paper cites JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Reference 4

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source=pdf_text observed=2026-08-14T04:46:15.906278Z digest=sha256:18920e7b78a0c4c4fde1d56dac19a6346731729179df34c017fbd45e30b3be65

Observation 48c50b2d-4fdf-4c95-b322-8adc64ac5459 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Training Verifiers to Solve Math Word Problems

Reference 7

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source=pdf_text observed=2026-08-14T04:46:15.918373Z digest=sha256:6820ad962a05c6745f29a9915aa9cb5ef0ca1d842dbcb1c7dc31c9717d78ad32

Observation f9a16946-6a01-4984-8eba-7ea33532729f · outbound

This paper cites SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging

Reference 9

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source=pdf_text observed=2026-08-14T04:46:15.925093Z digest=sha256:462d75d94f0de7e0f1127a1b975a7530183117de05d3b0a646bd6f3242064486

Observation 263505ab-b217-4b2e-b25a-28d22d546b0b · outbound

This paper cites Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging

Reference 10

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source=pdf_text observed=2026-08-14T04:46:15.928433Z digest=sha256:9d93451aa1734a8a172178d46abc51920150c3b5b18b8d4b7aa39f3f59b89b51

Observation 160a6b59-3d94-4591-99d9-e8d9d0612bba · outbound

This paper cites Merging Improves Self-Critique Against Jailbreak Attacks.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Merging Improves Self-Critique Against Jailbreak Attacks

Reference 11

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source=pdf_text observed=2026-08-14T04:46:15.931694Z digest=sha256:259e316f54d79629cab2e90527d7a01f1e3d9e8ba83566d247e77a9a1e07bb5d

Observation 43554abd-4fb4-4256-9cc0-980f1fe26210 · outbound

This paper cites Model Merging and Safety Alignment: One Bad Model Spoils the Bunch.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Model Merging and Safety Alignment: One Bad Model Spoils the Bunch

Reference 12

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source=pdf_text observed=2026-08-14T04:46:15.935356Z digest=sha256:2ecc287208baee73b27422b2dd780114737b6980adec1d97005776ac8037236c

Observation 5fb6fffd-c50d-49bc-81ba-9498562ad1d6 · outbound

This paper cites InAdvances in Neural Information Processing Systems (NeurIPS).

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs InAdvances in Neural Information Processing Systems (NeurIPS)

Reference 13

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source=pdf_text observed=2026-08-14T04:46:15.938898Z digest=sha256:d0f93a04909bd6d1309aae401e12c850786d9996fec7ddddfeb103bf75108206

Observation 10883db3-9c84-4ec1-bad8-edea276f3489 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Measuring Massive Multitask Language Understanding

Reference 14

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source=pdf_text observed=2026-08-14T04:46:15.941922Z digest=sha256:14c677a8f3a5b0ec5a957fb68725fd7461b40b6fc079dd6039f0191a0ada1982

Observation 8de3ed6b-2a59-4fd7-9736-82895f6c5e3e · outbound

This paper cites Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models

Reference 15

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source=pdf_text observed=2026-08-14T04:46:15.945333Z digest=sha256:e118620ddacd5252ace867133dca493df354f5d13dac64a52038ecc77e7b4067

Observation 97bca837-2cde-42f6-8e2d-0e43a7d6a0a2 · outbound

This paper cites Editing Models with Task Arithmetic.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Editing Models with Task Arithmetic

Reference 16

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source=pdf_text observed=2026-08-14T04:46:15.948851Z digest=sha256:50c804a2bddb493f6e32535c832f8bfe3f077fa5cc2a904d3fbed527dee9d3ab

Observation 4d59b9b3-4460-4231-8a1c-bdae26f7acce · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 17

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source=pdf_text observed=2026-08-14T04:46:15.952662Z digest=sha256:b7775a0417747f41a69ef3a8a4ffb3397a9cb8e5fd3debd74839167c434f01c2

Observation ed595a6f-298f-4b54-97b1-b072efecf5e5 · outbound

This paper cites LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B

Reference 18

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source=pdf_text observed=2026-08-14T04:46:15.956173Z digest=sha256:d686f57ed727e74d086ab8657f02422cf75acc0f11d3e7dadfea6107bcc374a4

Observation f062de73-6dba-4e4b-b2f7-661c6350bfc7 · outbound

This paper cites Ma, Q.; Liu, D.; Chen, Q.; Zhang, L.; and Shao, J.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Ma, Q.; Liu, D.; Chen, Q.; Zhang, L.; and Shao, J

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-14T04:46:15.959717Z digest=sha256:cd92e6a0a9e249e0e7ef4c3cb616559b8198bbcf05262f62f5f17c4f50abea23

Observation 34fe08dc-c22f-40d1-b7a6-97b24bf6ac3d · outbound

This paper cites LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint

Reference 20

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source=pdf_text observed=2026-08-14T04:46:15.963181Z digest=sha256:d954b19b86c789c779a7cf88d29166381bbc97af3cfe8cf8da93a3e9f51749ef

Observation 86e8fea2-8046-4f65-b74d-eb2de5219de0 · outbound

This paper cites HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Reference 21

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source=pdf_text observed=2026-08-14T04:46:15.966829Z digest=sha256:7153b909a26defe2f0ab8dfc13e2071bdfc6d9d8dbd28fe1de2c02b69a379e9d

Observation b5a8c56f-75eb-4375-ae08-1c6007877dbb · outbound

This paper cites Safety Alignment Should Be Made More Than Just a Few Tokens Deep.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Safety Alignment Should Be Made More Than Just a Few Tokens Deep

Reference 22

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source=pdf_text observed=2026-08-14T04:46:15.970418Z digest=sha256:712b96adee9040042a0cbebbe7e711a605d9eec3d428f2219c3b15a7cfcec4d5

Observation 6326a994-2fc5-488f-ba26-9a40adc8c0bb · outbound

This paper cites Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Reference 23

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source=pdf_text observed=2026-08-14T04:46:15.973885Z digest=sha256:cba4a2c3a7839b2d45495d34f744c2b752e1ced30415a9ea0be08c1921b7ff58

Observation 661d7a26-7acf-4570-b022-dc295f2eff51 · outbound

This paper cites Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack

Reference 24

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source=pdf_text observed=2026-08-14T04:46:15.978011Z digest=sha256:7e17929278f45ab943d3242c4bb71e668df3d322b922536902274cb761200de6

Observation e620d36b-1e62-46d8-af9a-40cd00a1cf4b · outbound

This paper cites Thakkar, M.; Fournier, Q.; Riemer, M.; Chen, P.-Y.; Zouaq, A.; Das, P.; and Chandar, S.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Thakkar, M.; Fournier, Q.; Riemer, M.; Chen, P.-Y.; Zouaq, A.; Das, P.; and Chandar, S

Reference 25

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source=pdf_text observed=2026-08-14T04:46:15.981197Z digest=sha256:f314ee816fbcac736bd32d0270de2a91af67caaed726b372bd86866ecef4e249

Observation 0aed9cd0-699d-49f4-a2b1-3cbe23fd347a · outbound

This paper cites Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs

Reference 26

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source=pdf_text observed=2026-08-14T04:46:15.984176Z digest=sha256:ac936e851b6377dbde36451c976d88209ab9af2746304a5c40c377425fe25204

Observation df4dee33-b099-436b-821c-ee82e644ba1c · outbound

This paper cites Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications

Reference 28

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source=pdf_text observed=2026-08-14T04:46:15.991367Z digest=sha256:911b80988f38ef234fa3b8c3ed107defcaa971cd12044c90b9a173c791b77696

Observation a0068464-d3d9-4cf4-9eef-4d141eb2f968 · outbound

This paper cites InIEEE Symposium on Security and Privacy (S&P).

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs InIEEE Symposium on Security and Privacy (S&P)

Reference 30

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-14T04:46:15.998855Z digest=sha256:252d16c02df046c314eb04ce3895f67a65c4821f74987c4e5b2838a41550d659

Observation e8a0e393-1d01-47bf-9d95-30e914561159 · outbound

This paper cites Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

Reference 31

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source=pdf_text observed=2026-08-14T04:46:16.001976Z digest=sha256:8dea92883c943f722aaccf808bd3ea6cc384ed55f66cb66ec6214948fe96a6b4

Observation 48faf8a9-8c10-4345-8027-8a2ed3018bd4 · outbound

This paper cites TIES-Merging: Resolving Interference When Merging Models.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs TIES-Merging: Resolving Interference When Merging Models

Reference 32

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source=pdf_text observed=2026-08-14T04:46:16.005471Z digest=sha256:2daec7e072b1decb8e44ae6771d7e10ae23477853c2225ab96548ee33b38d607

Observation cc05a525-f187-4a51-91da-fc87494fd375 · outbound

This paper cites Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace

Reference 33

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source=pdf_text observed=2026-08-14T04:46:16.009315Z digest=sha256:e055eb6c1b5105d1dfc280d0f281df8ab0533f5f18af2af212d3a4aa24e0d362

Observation 295ba9dd-4fd7-4a7e-b69e-5d522a441f8d · outbound

This paper cites Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch

Reference 34

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source=pdf_text observed=2026-08-14T04:46:16.012609Z digest=sha256:952e01652681f1d3e9625b8fa40ac172629fded8f332b0a247b802022728e1c5

Observation 1ac8c5ef-3832-406b-b9f0-0167555c2ab6 · outbound

This paper cites 13 Zhang, J.; He, Y.; Cai, K.; Zhao, H.; Suya, F.; and Tian, Y.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs 13 Zhang, J.; He, Y.; Cai, K.; Zhao, H.; Suya, F.; and Tian, Y

Reference 35

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source=pdf_text observed=2026-08-14T04:46:16.015991Z digest=sha256:7b2f751127f2a6d36ff2e72bc21a7bd54f2227095041896ca242c7db45c806a6

Observation 816b8940-0521-4aa9-8f69-e4b1d337326e · outbound

This paper cites RogueMerge: Robust and Unified Attacks against LLM Model Merging.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs RogueMerge: Robust and Unified Attacks against LLM Model Merging

Reference 36

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local_arxiv, observed 2026-08-14T04:46:16.084279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-14T04:46:16.019854Z digest=sha256:559f5300ad364fb10338de7960c6c06fc69b6e49454f471a802b8504c04783d0

Observation 98f5e297-da19-442b-ad61-891ff6f9b58f · outbound

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

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Instruction-Following Evaluation for Large Language Models

Reference 37

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source=pdf_text observed=2026-08-14T04:46:16.024015Z digest=sha256:6b2b8145a082b441ba5fb4b2663aba5bf50db7953d4a58fad4c518bb61d01a3d

Observation 6c633179-6ea7-4e8f-95ce-bdbd5f951d6a · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 38

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source=pdf_text observed=2026-08-14T04:46:16.027663Z digest=sha256:db75878976ff7db0c165cee3aa743cef4cfd177551a935a0ea897c238ae75569

Observation b5977ead-c045-42d7-8b35-919c91173192 · outbound

This paper cites On Adaptive Attacks to Adversarial Example Defenses.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs On Adaptive Attacks to Adversarial Example Defenses

Reference 2020

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source=pdf_text observed=2026-08-14T04:46:15.987575Z digest=sha256:ccf580ae6ae4c34777acd871db2d623e2ac6ef192fce1500c8d991ff938473d1

Observation c5912dd9-fde1-4e9a-ae1b-df767c20100c · outbound

This paper cites Evaluating Large Language Models Trained on Code.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Evaluating Large Language Models Trained on Code

Reference 2021

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source=pdf_text observed=2026-08-14T04:46:15.914300Z digest=sha256:b2f23754e8312964380f634c1f0890417dca8b8a4ffa64b441fb61f1ce073622

Observation 18a463a7-77b2-4c50-ba3f-5b93303b948c · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 2022

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source=pdf_text observed=2026-08-14T04:46:15.995296Z digest=sha256:a376be0d18977bc457bfe5a5e358b7fe99058b34680ab49940fbe4d2840b9d66

Observation 47639529-db75-489e-bd56-2232d42798dc · outbound

This paper cites Jailbreaking Black Box Large Language Models in Twenty Queries.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 2023

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no resolver link, observed 2026-08-14T04:46:15.910426Z

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source=pdf_text observed=2026-08-14T04:46:15.910426Z digest=sha256:f8f6702300041d7b27b1059cff102f947ec2eecf8da07dd61bde8889cf95182f

Observation d44097e4-6445-4aeb-bbc8-f3be439fbf4f · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Refusal in Language Models Is Mediated by a Single Direction

Reference 2024

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source=pdf_text observed=2026-08-14T04:46:15.897691Z digest=sha256:cdfaedc7a9d5978ca0469ceb300cd88381074b1a294c8cfd9d6c25aa28801d6e

Observation 51554e35-6a93-4cf9-9a88-4642ef2b828a · outbound

This paper cites Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Reference 2025

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source=pdf_text observed=2026-08-14T04:46:15.893135Z digest=sha256:66a68ee04b14387481d9d25e92094c94faeb9dde35efec7449f3b6cd4af7b08e

Observation 22524470-4f0d-4b99-b3eb-a6973346ebee · outbound

This paper cites Djuhera, A.; Kadhe, S.

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs Djuhera, A.; Kadhe, S

Reference 2026

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no resolver link, observed 2026-08-14T04:46:15.922065Z

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source=pdf_text observed=2026-08-14T04:46:15.922065Z digest=sha256:5ba273e5b35b2343fd84f4afe27e8db2dcdbd457fc766c22628c9c44109b7356

Pith citing papers

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