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Paper Citation Record · LEDGER

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation

As of 7 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2608.03166.

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

pith.paper-citation-record.v1
2608.03166 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:29:58.290673Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

28 of 28 outbound references displayed

  • verified exact2
  • verified fuzzy3
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch8

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b9fac2ea-4937-4cc2-8d6d-b81eafb9675c · outbound

This paper cites The Oscars of AI Theater: A Survey on Role-Playing with Language Models.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation The Oscars of AI Theater: A Survey on Role-Playing with Language Models

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:29:55.891371Z digest=sha256:2429bf4300e70c6ba97cfa39badcf6cf35f0ba9e9ab9003cd39dab2cddc4d350

Observation 00c93cdc-df59-47ba-bbb0-569dfd3da8a1 · outbound

This paper cites ASSERT: Automated Safety Scenario Red Teaming for Evaluating the Robustness of Large Language Models.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation ASSERT: Automated Safety Scenario Red Teaming for Evaluating the Robustness of Large Language Models

Reference 2

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T00:29:55.943379Z digest=sha256:8ce731e3eebbfdfa6a22ced5550d4e7305591e549bf2d8bcdc10d3359e602715

Observation 103f45a2-66bb-4496-98f7-7f48abc91fd2 · outbound

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

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Reference 3

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no resolver link, observed 2026-08-06T00:29:56.028755Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:29:56.028755Z digest=sha256:fbf8190ed542755f89f286b7a66480392c2eb146dc9c2a1822c24d1e56661a82

Observation 59846c01-4ae4-47c3-9ac5-60a8dff937ac · outbound

This paper cites RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing Language Agents,.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing Language Agents,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T00:30:00.431231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:56.129225Z digest=sha256:e6f8e89fa96c10228b7b293b71906a45e220b6aa8372c1101cfd667e9d1a7d2a

Observation 153fcb74-d969-4170-8d67-9e08ce1803b1 · outbound

This paper cites AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:29:56.208408Z digest=sha256:355e1dcabe1dd65735ff74d3a4707afd129232f1a3b11e82802888c0cce714c9

Observation 8416447f-0537-483c-91d7-93dbd9f4b2fc · outbound

This paper cites Adversarial Testing in LLMs: Insights into Decision-Making Vulnerabilities.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Adversarial Testing in LLMs: Insights into Decision-Making Vulnerabilities

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-06T00:29:59.822893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:56.341529Z digest=sha256:5e99c8b5414a1c6ae9548aced2f4234cd353ec9ea43f1f354b631fcfd10377cb

Observation 4dded492-67ed-4285-83f1-5d72175ab62e · outbound

This paper cites Red Teaming Large Language Models: A Comprehensive Review and Critical Analysis,.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Red Teaming Large Language Models: A Comprehensive Review and Critical Analysis,

Reference 8

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raw_fallback, observed 2026-08-06T00:30:00.272974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:56.408327Z digest=sha256:077a5892d433ed16307a353e343af06dbf4322bd6c389e721576afb9d2d25ee4

Observation aa86cdb8-632d-499e-98c9-a29c2ba83f91 · outbound

This paper cites Security of LLM-based Agents: Attacks, Defenses, and Applications,.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Security of LLM-based Agents: Attacks, Defenses, and Applications,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-06T00:30:00.131587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:56.485119Z digest=sha256:7bfa70e70e43bb19fd0b1d8b01a8aca6aea97d175ec83c19e2c698fa178b5b82

Observation 4dc2bad5-597b-4a54-b856-a8b2916e6f24 · outbound

This paper cites Markov-Enhanced Clustering for Long Document Summarization: Tackling the 'Lost in the Middle' Challenge with Large Language Models.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Markov-Enhanced Clustering for Long Document Summarization: Tackling the 'Lost in the Middle' Challenge with Large Language Models

Reference 10

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local_arxiv, observed 2026-08-06T00:29:59.970446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:56.532477Z digest=sha256:c2a59ff465337de6ad5b4449f48ec48a7820a43f1a84a45527f0603d2866cc37

Observation 51ee87da-f0b5-42b3-9169-f8cfd2021453 · outbound

This paper cites Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment

Reference 11

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T00:29:56.632621Z digest=sha256:681deefbe8dcef6f926d5cc000976da031746d7a96a71544b5b50cb305520a6e

Observation 593966c0-7a4e-4ad2-93af-ea9b594737a8 · outbound

This paper cites RedDebate: Safer Responses Through Multi-Agent Red Teaming Debates.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation RedDebate: Safer Responses Through Multi-Agent Red Teaming Debates

Reference 12

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source=pdf_text observed=2026-08-06T00:29:56.700795Z digest=sha256:a8ab8eb610786a114284ba1c98404848d12d95f16966d70af9210eec0f88b866

Observation edb960e9-8d02-478f-ab19-7cf4cadd7b88 · outbound

This paper cites MART: Improving LLM Safety with Multi-round Automatic Red-Teaming.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation MART: Improving LLM Safety with Multi-round Automatic Red-Teaming

Reference 13

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source=pdf_text observed=2026-08-06T00:29:56.778717Z digest=sha256:79bdf7224da03f9d38d782d90b657737ab9f443181719aa03cb9e1a2316427c2

Observation fcd9b88f-f8d7-48cb-8a23-07b0bcc1fd3d · outbound

This paper cites Evil Geniuses: Delving into the Safety of LLM-based Agents.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Evil Geniuses: Delving into the Safety of LLM-based Agents

Reference 14

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source=pdf_text observed=2026-08-06T00:29:56.858992Z digest=sha256:47eba9adb3859f902953aeb2a7c4e93d27d1ba506fc3313fbfec4d4f9a0b1c3f

Observation 2a562869-30fa-40f6-a310-093383e3a0f5 · outbound

This paper cites RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent

Reference 15

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source=pdf_text observed=2026-08-06T00:29:56.930215Z digest=sha256:3a1cd47d388e8c77751953e42569a8fdea84c64acc166d683ef5c913f66eadbf

Observation d28070b9-00f4-4e73-b1d8-8654f92726e6 · outbound

This paper cites Encounter-based model of a run-and-tumble particle with stochastic resetting.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Encounter-based model of a run-and-tumble particle with stochastic resetting

Reference 16

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metadata mismatch
local_arxiv, observed 2026-08-06T00:29:59.614995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:56.998828Z digest=sha256:c48042d79ba0a94bd4f9ba279b3cc63c8ebc32d1353828d514146b5c419f9c1f

Observation be359958-702e-4cb7-a28d-851c99af979f · outbound

This paper cites Exposing Weak Links in Multi-Agent Systems under Adver- sarial Prompting,.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Exposing Weak Links in Multi-Agent Systems under Adver- sarial Prompting,

Reference 17

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source=pdf_text observed=2026-08-06T00:29:57.065596Z digest=sha256:d3a45ad7d3ad1f26bef2e1f77fbc63e630ae0ae959b65c2a361fa157d17a92f2

Observation 6913ec36-c166-4117-bbd4-745fc6aace07 · outbound

This paper cites Iwasawa module of the cyclotomic $\mathbb{Z}_{2}$-extension of certain real quadratic fields.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Iwasawa module of the cyclotomic $\mathbb{Z}_{2}$-extension of certain real quadratic fields

Reference 19

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local_arxiv, observed 2026-08-06T00:29:59.270567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:57.300906Z digest=sha256:f98b670a6b1cfbc42accd1cacefff8ee0ed5300c0539a7a5d7dc7f136c5c4c76

Observation c6ca3504-9d98-4ad8-8114-0bcf1183b914 · outbound

This paper cites SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code

Reference 20

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source=pdf_text observed=2026-08-06T00:29:57.375647Z digest=sha256:add074e5407aa008b91d6946da3328ef328fb2f5dca49a59d1b82637267ba8b0

Observation a3dc3093-1dfc-4dff-8728-9dbef0276e2e · outbound

This paper cites From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agent Workflows,.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agent Workflows,

Reference 21

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source=pdf_text observed=2026-08-06T00:29:57.468919Z digest=sha256:d53500e34a7208f04b2a378bf4a4bd59bddedeb47aa3b91e4b085e00e4e9e2d2

Observation 891d8d25-88bf-48f7-bdc6-ff1dad7283dc · outbound

This paper cites Stable Diffusion For Aerial Object Detection.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Stable Diffusion For Aerial Object Detection

Reference 22

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source=pdf_text observed=2026-08-06T00:29:57.573900Z digest=sha256:a379de541d87861293165f6112b733b1f4881234dfaa0aadcf0764d789051065

Observation dc053066-a483-4ae5-860e-62584c6b65a2 · outbound

This paper cites Online Adaptive Traversability Estimation through Interaction for Unstructured, Densely Vegetated Environments.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Online Adaptive Traversability Estimation through Interaction for Unstructured, Densely Vegetated Environments

Reference 23

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local_arxiv, observed 2026-08-06T00:29:59.083036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:57.693775Z digest=sha256:445f84bd0f5fe777e1e65b2b61b56de931c4025d8543f6723cdf6c699f0ebf23

Observation 3974ba24-355a-435e-8cb6-3c8a78a87e94 · outbound

This paper cites Learning to Adapt to Position Bias in Vision Transformer Classifiers.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Learning to Adapt to Position Bias in Vision Transformer Classifiers

Reference 24

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local_arxiv, observed 2026-08-06T00:29:58.912857Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:57.773801Z digest=sha256:b456c4f57aae6fbe86565d1775877df9e2a7759e616af224957022ed265af225

Observation ca0e29d1-e053-4708-b07e-129e648b92ac · outbound

This paper cites Compound Expression Recognition via Large Vision-Language Models.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Compound Expression Recognition via Large Vision-Language Models

Reference 26

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T00:29:58.788800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:58.020373Z digest=sha256:670fcaf83441e2e00f7338fa977710386fd87e1482c68af41b682e25ce18fafb

Observation b455f210-342a-402c-a79c-e6bb5e790e4b · outbound

This paper cites Context-Aware Two-Step Training Scheme for Domain Invariant Speech Separation.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Context-Aware Two-Step Training Scheme for Domain Invariant Speech Separation

Reference 27

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verified exact
local_arxiv, observed 2026-08-06T00:29:58.622840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:58.108401Z digest=sha256:c5211b84e77b696acdd6e860cc01dde47e25ffc513d72b4e650b1aca96af6e6c

Observation 5a58fb64-3080-4b1b-b706-afef034d9e26 · outbound

This paper cites The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:29:58.203660Z digest=sha256:9d5a024403a9a336bad4d8ac01ab7baa1a1dd4d67cc7adc50c7d55a74d5c7386

Observation d7788856-23e0-4090-9d8f-4f6cd1ed82a9 · outbound

This paper cites Lower bounds on the $\ell$-rank of ideal class groups.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Lower bounds on the $\ell$-rank of ideal class groups

Reference 29

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metadata mismatch
local_arxiv, observed 2026-08-06T00:29:58.420619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:58.290673Z digest=sha256:d7a2e41fac39f2dad64f838b925b2d3e308d5c72f463085b14004843ab02dc42

Observation 58b5660d-6260-46e1-908c-065a195af10c · outbound

This paper cites Mitigating Label Noise on Graph via Topological Sample Selection.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Mitigating Label Noise on Graph via Topological Sample Selection

Reference 2024

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:29:57.946969Z digest=sha256:cdce2b8a3fb8e1abebddcf178194d767ee66c6ed415a5391eb83f187c9286d2b

Observation d839405d-1902-4356-b701-0d250ea816f7 · outbound

This paper cites Evaluating the Impact of Verbal Multiword Expressions on Machine Translation.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation Evaluating the Impact of Verbal Multiword Expressions on Machine Translation

Reference 2025

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local_arxiv, observed 2026-08-06T00:29:59.419281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T00:29:57.241797Z digest=sha256:54e42ba756bf7e5acb1c01227d78f55ce9568f614af1fa69fb08f63d1847e674

Pith citing papers

No inbound Pith citation observations are available.