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Paper Citation Record · LEDGER

InfoFlood: Jailbreaking Large Language Models with Information Overload

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2506.12274.

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

pith.paper-citation-record.v1
2506.12274 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:02:31.476445Z

measured 43 of 43 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T17:49:42.112564Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T17:51:41.877221Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4599e56b-8c40-45b2-b42c-c3dafba462cb · outbound

This paper cites write newline.

InfoFlood: Jailbreaking Large Language Models with Information Overload write newline

Reference 1

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no resolver link, observed 2026-08-07T01:02:27.992361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:27.992361Z digest=sha256:4a49c9c5a3509ff3c2907ba052bafaee1978e45af617c588558e8f71293dd29e

Observation b590bac7-7219-4e38-9bad-ab644bc47292 · outbound

This paper cites Llama 3 model card.

InfoFlood: Jailbreaking Large Language Models with Information Overload Llama 3 model card

Reference 3

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no resolver link, observed 2026-08-07T01:02:28.089322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.089322Z digest=sha256:5cea86b40015e3c26cf230b6302ab45337c5a464bbd6390af8f168d7505a110d

Observation fb56c737-8c7e-4b8b-a525-fc7ba42f9a2f · outbound

This paper cites Does Refusal Training in LLMs Generalize to the Past Tense?.

InfoFlood: Jailbreaking Large Language Models with Information Overload Does Refusal Training in LLMs Generalize to the Past Tense?

Reference 4

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no resolver link, observed 2026-08-07T01:02:28.139129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.139129Z digest=sha256:c73f6ce1aab4dd7dea7e2b9d48d852971e6d8f36fe164f02d1097538970b03c1

Observation 45f4c9b1-61f6-4c56-ac0e-972d3aa5399b · outbound

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

InfoFlood: Jailbreaking Large Language Models with Information Overload Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.219255Z digest=sha256:924a14ce9c6421962eb728f0ad80f53b64d6bace439fe7c760b7ddaf8b3dfead

Observation 9955a0d8-e12a-4bdc-96fc-35040173a9e6 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

InfoFlood: Jailbreaking Large Language Models with Information Overload Constitutional AI: Harmlessness from AI Feedback

Reference 6

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no resolver link, observed 2026-08-07T01:02:28.245895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.245895Z digest=sha256:e3a246fbd2293076a90df0e763cd81161dba4a90ea6ce46a7722835bddb0f894

Observation 73515443-fb14-4a2c-a2b8-88982c43a6ba · outbound

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

InfoFlood: Jailbreaking Large Language Models with Information Overload JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Reference 7

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no resolver link, observed 2026-08-07T01:02:28.336517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.336517Z digest=sha256:f6a77ac48a10becfc11bebea5615bd35e0c20c3ef740606bc8fb36faecab074a

Observation a2e4e2fe-c1aa-4c48-88da-f4468050bfcd · outbound

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

InfoFlood: Jailbreaking Large Language Models with Information Overload Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 8

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no resolver link, observed 2026-08-07T01:02:28.376924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.376924Z digest=sha256:75cfce4a0c1a95f93cfe4f1c30c6b0b0e5c44a757e76ec60b088dcc85cccdf4d

Observation 92da5a23-91f1-46d2-80c5-233ed4293158 · outbound

This paper cites JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs.

InfoFlood: Jailbreaking Large Language Models with Information Overload JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.442955Z digest=sha256:6aae19a6f4a6d6a4ba024962cf8e8bee6122ae45cd6312965bbc7de89d937549

Observation 574d3678-30ed-4795-905f-b9ba33de1454 · outbound

This paper cites Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack.

InfoFlood: Jailbreaking Large Language Models with Information Overload Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.494126Z digest=sha256:15ced9ead27123fcc36c1d310da1afdba5279d685c931885d523c0e0942b15fd

Observation 473d0749-0446-4e7d-975c-e4f8cee67e56 · outbound

This paper cites Google gemini flash, February 2025.

InfoFlood: Jailbreaking Large Language Models with Information Overload Google gemini flash, February 2025

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-07T01:02:32.804000Z

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=arxiv_source observed=2026-08-07T01:02:28.542208Z digest=sha256:cf72be327341bd80cb449901714a38a66f12c3cfa9ceb04b912d2c5c987259de

Observation a952a564-86e3-4215-84b1-0e5002fc8b9b · outbound

This paper cites Deliberative Alignment: Reasoning Enables Safer Language Models.

InfoFlood: Jailbreaking Large Language Models with Information Overload Deliberative Alignment: Reasoning Enables Safer Language Models

Reference 12

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:02:28.553458Z digest=sha256:e008cbc240234e7e801781075f461d5b1f18dc3363017d2aa4159af376d783bd

Observation 883e1bf8-fe66-41cd-a0e0-11ef0faf44fc · outbound

This paper cites Endless Jailbreaks with Bijection Learning.

InfoFlood: Jailbreaking Large Language Models with Information Overload Endless Jailbreaks with Bijection Learning

Reference 13

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source=arxiv_source observed=2026-08-07T01:02:28.608823Z digest=sha256:a6be44bb73c68668e6331fa1be619c3771ed51391faa6631720725bb85cd26e8

Observation 4a6827c6-57e4-4c4f-b82b-4a02dbd4b8be · outbound

This paper cites Perspective api, 2024.

InfoFlood: Jailbreaking Large Language Models with Information Overload Perspective api, 2024

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:02:32.614286Z

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=arxiv_source observed=2026-08-07T01:02:28.647062Z digest=sha256:ef9c075d1799d67b07612c82ac1ab13689caf964bb32d2b969bcb84634c6b42e

Observation 9feef088-88b1-411c-a5e0-edf3e581e8f5 · outbound

This paper cites Guard: Role-playing to generate natural-language jailbreakings to test guideline adherence of large language models.

InfoFlood: Jailbreaking Large Language Models with Information Overload Guard: Role-playing to generate natural-language jailbreakings to test guideline adherence of large language models

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.827911Z digest=sha256:074b6e0f4a502643dbab672f878cde7871daa696cdeb0c9390559ff3ef41acf6

Observation 0aaacc26-e9ae-46e3-b432-fb1b3be88750 · outbound

This paper cites Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters.

InfoFlood: Jailbreaking Large Language Models with Information Overload Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:28.929877Z digest=sha256:b9fc8f5156fdb82b50ef0f968923eb84feb848b9659908d15a90a379229dab43

Observation f29a9c8c-1f44-4a57-a31a-e16b4f2438e7 · outbound

This paper cites Automatically Auditing Large Language Models via Discrete Optimization.

InfoFlood: Jailbreaking Large Language Models with Information Overload Automatically Auditing Large Language Models via Discrete Optimization

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.019773Z digest=sha256:0dd51485c145e288fe3b46d81609054536cfecd1d568892915dfa4adf6f264d2

Observation 65c9f057-029c-4115-b33d-15030852ea12 · outbound

This paper cites DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers.

InfoFlood: Jailbreaking Large Language Models with Information Overload DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 18

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no resolver link, observed 2026-08-07T01:02:29.162442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.162442Z digest=sha256:9e7d6198e69dfd2608666d29bf8c9bd73858e337213eb7556b2a4999eeb9b4c8

Observation 4a430d69-8ffb-4eb8-99a2-165fd2e62582 · outbound

This paper cites AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models.

InfoFlood: Jailbreaking Large Language Models with Information Overload AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.259137Z digest=sha256:f3b090d5be6a1a973a6a11b5768abbbd6fd93c7b447b37bf8e5df25dd3ed08f6

Observation 541aa07d-fcb4-422d-9be6-2c74fe02c0ea · outbound

This paper cites Latent space cartography: Visual analysis of vector space embeddings.

InfoFlood: Jailbreaking Large Language Models with Information Overload Latent space cartography: Visual analysis of vector space embeddings

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-07T01:02:32.406428Z

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=arxiv_source observed=2026-08-07T01:02:29.359293Z digest=sha256:704a5ef7a9d7c37061cb68eb30c6e63b370cfe804ee3dd016fb59920710d2a67

Observation 6efa3274-449a-4025-b20e-ff89ea5efc74 · outbound

This paper cites Black Box Adversarial Prompting for Foundation Models.

InfoFlood: Jailbreaking Large Language Models with Information Overload Black Box Adversarial Prompting for Foundation Models

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.510173Z digest=sha256:b86f91b8a7fbf448a7a0dfb65132e2ec652f142d98b4e87364542a5e49023ccf

Observation a809df2a-ab18-47f9-853a-35b55696cd33 · outbound

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

InfoFlood: Jailbreaking Large Language Models with Information Overload HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.635233Z digest=sha256:71598043ade588c656dcfbf63a6d332f0f13b80b3dc845ebde88379f86e86358

Observation 24cad203-093f-4e9c-bf12-42058fd26783 · outbound

This paper cites Tree of Attacks: Jailbreaking Black-Box LLMs Automatically.

InfoFlood: Jailbreaking Large Language Models with Information Overload Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Reference 23

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unresolved
no resolver link, observed 2026-08-07T01:02:29.718383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.718383Z digest=sha256:26574f0f963f2a703895f2c3e7f7f81a859667913fc986a99d516de8a9ffc108

Observation 10e19b5b-e007-47c4-bf0a-f615dafda644 · outbound

This paper cites SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning.

InfoFlood: Jailbreaking Large Language Models with Information Overload SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Reference 24

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no resolver link, observed 2026-08-07T01:02:29.757780Z

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source=arxiv_source observed=2026-08-07T01:02:29.757780Z digest=sha256:134bfd492176ed1dd24054c07cd6da86b65c3dd801bd4bbf7f1e3d02737e24a4

Observation 6200ca5a-b30b-4867-b0b9-f8011ce157a4 · outbound

This paper cites Openai moderation api, 2024.

InfoFlood: Jailbreaking Large Language Models with Information Overload Openai moderation api, 2024

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T01:02:32.219003Z

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=arxiv_source observed=2026-08-07T01:02:29.845731Z digest=sha256:01be2483c67f1912c42519268bea8cc86997ae4726f80c2beba76e7e1c16aded

Observation b38239c3-6085-4789-8206-326b6f1e0291 · outbound

This paper cites GPT-4 Technical Report.

InfoFlood: Jailbreaking Large Language Models with Information Overload GPT-4 Technical Report

Reference 26

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source=arxiv_source observed=2026-08-07T01:02:29.913107Z digest=sha256:c861b8620a69fdbe446e018cd423f034b1961fc5f5da50eb5079370fb082670c

Observation 6b8825c2-d16d-4378-bea6-e14046117ef8 · outbound

This paper cites Training language models to follow instructions with human feedback.

InfoFlood: Jailbreaking Large Language Models with Information Overload Training language models to follow instructions with human feedback

Reference 27

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source=arxiv_source observed=2026-08-07T01:02:30.027097Z digest=sha256:771e0fe0960f455d3085baa06fa3371e556954ccc868fe6fdfba62499c7f622d

Observation 80fcbd30-de18-44ae-81ce-192f881e457b · outbound

This paper cites AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs.

InfoFlood: Jailbreaking Large Language Models with Information Overload AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs

Reference 28

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:30.091792Z digest=sha256:4b2bb13d218ebcba3a3297885e102b5c6db5aaf6134bc2c336a916bf12c744a1

Observation b793d7b8-c6d6-4b08-b920-345c2a849c87 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

InfoFlood: Jailbreaking Large Language Models with Information Overload Direct preference optimization: Your language model is secretly a reward model

Reference 29

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no resolver link, observed 2026-08-07T01:02:30.174966Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:02:30.174966Z digest=sha256:36a5c1e43e6c067f53b7c3830c86584bab8a6fb50119df5ded9ac44040b1cb31

Observation c0c2182a-f26f-4c40-bf7f-b3bcf6a1a0da · outbound

This paper cites CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion.

InfoFlood: Jailbreaking Large Language Models with Information Overload CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion

Reference 31

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:02:30.366652Z digest=sha256:956154cad0a8fff70ec3aeda9c4e6ebe7aa669fc7dc4448477954b0c02e201d3

Observation 314bd4fa-9e4f-4c90-8d5a-5b5c89129320 · outbound

This paper cites SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks.

InfoFlood: Jailbreaking Large Language Models with Information Overload SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks

Reference 32

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:30.422551Z digest=sha256:5c5d24b34b63daa07e3175b3a9e81e73ad1facfeb234dc52cef4ffe6928a11dc

Observation 5ab4b317-26e8-41fe-b82d-e552fd642400 · outbound

This paper cites do anything now.

InfoFlood: Jailbreaking Large Language Models with Information Overload do anything now

Reference 33

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no resolver link, observed 2026-08-07T01:02:30.513966Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T01:02:30.513966Z digest=sha256:ed0b4462247f40673a69652a7a2f03b8271f5744a1da1d56fcc8c59b44bcb7ec

Observation 7c95f0d9-0902-46fa-9095-085198e0c53e · outbound

This paper cites Recursive deep models for semantic compositionality over a sentiment treebank.

InfoFlood: Jailbreaking Large Language Models with Information Overload Recursive deep models for semantic compositionality over a sentiment treebank

Reference 34

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source=arxiv_source observed=2026-08-07T01:02:30.587700Z digest=sha256:05ad55722ca3d5291bcad804b01b9955c1017ec104dc8be07298a19c4546dcc4

Observation dbd642cc-ed8a-4ba2-8d62-f8a6c359e9da · outbound

This paper cites Large language models in medicine.

InfoFlood: Jailbreaking Large Language Models with Information Overload Large language models in medicine

Reference 35

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no resolver link, observed 2026-08-07T01:02:30.712250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:30.712250Z digest=sha256:b93872a341957dc98e78c4b38d0525b389e363477ac6b7dae03f0357ab9aa419

Observation fcdfa2ab-2f5c-43c9-ab85-01f48fa5160e · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

InfoFlood: Jailbreaking Large Language Models with Information Overload Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:30.756720Z digest=sha256:58a4c2915f5b5f2297d7807925fe9e3e6fcbd48addfe6d19fb35e0d3f9dfe2dc

Observation 8ab6afcf-d67c-4ad8-a10a-563b24ebe579 · outbound

This paper cites Visualizing data using t-sne.

InfoFlood: Jailbreaking Large Language Models with Information Overload Visualizing data using t-sne

Reference 37

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:30.856232Z digest=sha256:d31ab1052f4062366c2a1474bb4fcdd0e6f4c5266efcf7a38c5a516429692bbb

Observation c709599e-1314-44af-9e8d-3c787a4fce59 · outbound

This paper cites Jailbroken: How does llm safety training fail? Advances in Neural Information Processing Systems, 36, 2024.

InfoFlood: Jailbreaking Large Language Models with Information Overload Jailbroken: How does llm safety training fail? Advances in Neural Information Processing Systems, 36, 2024

Reference 38

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source=arxiv_source observed=2026-08-07T01:02:30.934742Z digest=sha256:8658769020640c75d0ca65a0373b071a2ef90012919afff76bdbc812da29544d

Observation 55f36b96-93fa-4d92-8919-e1cc47c74088 · outbound

This paper cites Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations.

InfoFlood: Jailbreaking Large Language Models with Information Overload Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Reference 39

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no resolver link, observed 2026-08-07T01:02:31.037588Z

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source=arxiv_source observed=2026-08-07T01:02:31.037588Z digest=sha256:74cb39a0b1aa36a34270e7052fa237139e08bba0009bd54888f886717d76a7f4

Observation 73cea915-73c7-46c1-b2e3-ef246887c76b · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

InfoFlood: Jailbreaking Large Language Models with Information Overload BloombergGPT: A Large Language Model for Finance

Reference 40

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no resolver link, observed 2026-08-07T01:02:31.124015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:31.124015Z digest=sha256:343f3e8875d22140c159f062dca1d9766cc227cfc1af60bc003a64bfee026b05

Observation dce94c35-f6d7-4b5d-a23d-c2fc8e2b52e1 · outbound

This paper cites Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking.

InfoFlood: Jailbreaking Large Language Models with Information Overload Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:31.192664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:31.192664Z digest=sha256:55d72ef88563e0315b2c61f99634c9141047ea1fa16d325818d459d4299824b9

Observation 94e37423-7f20-4f0d-a15e-2c7c1724b829 · outbound

This paper cites GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher.

InfoFlood: Jailbreaking Large Language Models with Information Overload GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:31.303381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:31.303381Z digest=sha256:c8c276fbb16d0f9878ed233ca26c6e17d53225ae44fd0f3e095b59a17b7534ee

Observation 9b10db3e-a698-4987-a2eb-a75b8bdc3bc4 · outbound

This paper cites How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs.

InfoFlood: Jailbreaking Large Language Models with Information Overload How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:31.370445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:31.370445Z digest=sha256:233c329c80c5d55157fd40c2da10a8f060deccd882723109b93a0adc4e95dd15

Observation 73804334-59f5-4743-8987-c8ad397573d2 · outbound

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

InfoFlood: Jailbreaking Large Language Models with Information Overload Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:31.476445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:31.476445Z digest=sha256:54265d4a5a9d62df0d0db71fa1991287c7b634b759e6141800afd24912c6d12b

Pith citing papers

Observation 37cb36f4-60e7-476b-856c-01c913c0bbe7 · inbound

Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain cites this paper.

Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain InfoFlood: Jailbreaking Large Language Models with Information Overload

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-18T17:51:41.879269Z

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=arxiv_source observed=2026-05-18T17:49:42.112564Z digest=sha256:9851926a871c45a10d1092c4b3731fc228a97ca693f29be18478514e8bdb20f3