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Paper Citation Record · LEDGER

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification

As of 20 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2504.13562.

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

pith.paper-citation-record.v1
2504.13562 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:10:31.131754Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 62ae4d59-dd8c-457d-8afb-1fa5b705cfbc · outbound

This paper cites Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models

Reference 1

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no resolver link, observed 2026-08-16T12:10:30.898210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.898210Z digest=sha256:f53c70457901acf37fc23e4d752a880ceeabf2ecc68b9096a2170766a84fb492

Observation d58959d5-2197-41e6-8d01-c45298f405c0 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Reference 2

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no resolver link, observed 2026-08-16T12:10:30.904167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.904167Z digest=sha256:f33db2e5cd7b8bf96aca961217b32627ac9f8925bb6c1b93b4ad916e9f956005

Observation 2ede2e4a-7d9d-4021-8cc7-cc0ba662f677 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 3

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no resolver link, observed 2026-08-16T12:10:30.910396Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.910396Z digest=sha256:25d8a238695091781d9aa645c99c642821a5576c56375e75eebe369fb5a266a7

Observation 245933f6-3bad-4a58-866a-850cf9a12834 · outbound

This paper cites Bender, Timnit Gebru, Angelina McMillan - Major, and Shmargaret Shmitchell.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Bender, Timnit Gebru, Angelina McMillan - Major, and Shmargaret Shmitchell

Reference 4

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no resolver link, observed 2026-08-16T12:10:30.915634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.915634Z digest=sha256:a5086b17f07fe8e5059b7738142c01b70637ff4547017f9b4397aed41afd7ac8

Observation 18e1e37a-e73a-4df6-92d2-fade10287c68 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:10:31.959640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:30.920517Z digest=sha256:9f480fb02ad1b3bdf5eda5668de05cbd1e2aa86779d3b40c98b98f62cf8c5c65

Observation b600ed47-243c-4441-adb5-d84d93d8382d · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 6

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no resolver link, observed 2026-08-16T12:10:30.925082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.925082Z digest=sha256:a85a5ebdea0e07635d8b3cebd8da3ff7a3e82b32a6dea9090e0dca4a8e48dda6

Observation fffb375a-25d3-45e4-a074-0cfa3666257f · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Reference 7

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no resolver link, observed 2026-08-16T12:10:30.930303Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-16T12:10:30.930303Z digest=sha256:d560d87e0dcc2c07c032eceb8a9b47e98b7138ce17c34b27f4dafe7145c6b011

Observation 7fd13752-c144-4f96-9926-123a15e39aa2 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 8

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no resolver link, observed 2026-08-16T12:10:30.935163Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.935163Z digest=sha256:403ab6f14b89fc2d037fb82973ebafc74d740275344fe447cce896aa7d9a2ee5

Observation 5f908982-cb68-417b-9abc-8fb5f5cf95d9 · outbound

This paper cites Injecting Universal Jailbreak Backdoors into LLMs in Minutes.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Injecting Universal Jailbreak Backdoors into LLMs in Minutes

Reference 9

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source=arxiv_source observed=2026-08-16T12:10:30.939879Z digest=sha256:eb18e4aa1774e9de0e0155af0fe287c67b8ba8ee958119d45432bdfe2561c734

Observation 3ca86a27-66a4-4eb5-b4bb-a387c53d98ba · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 10

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no resolver link, observed 2026-08-16T12:10:30.944718Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:30.944718Z digest=sha256:b87f56532dd6d8567cb47fee483173886469188558716ccbc94caf2f320c6549

Observation a90b09ef-8ac4-4e71-876e-b7d460e28410 · outbound

This paper cites OR-Bench: An Over-Refusal Benchmark for Large Language Models.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification OR-Bench: An Over-Refusal Benchmark for Large Language Models

Reference 11

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source=arxiv_source observed=2026-08-16T12:10:30.948693Z digest=sha256:afe3a813dc2e04f0dfd12acbbcbdfe5a082a640656f0d01fb3f12b96c6267e4c

Observation b00dda28-cf7a-4a73-a981-9336b9192a41 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 12

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raw_fallback, observed 2026-08-16T12:10:31.935707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:30.952547Z digest=sha256:3805285e58ec9ccb154fddf2021141afc8e66c6a07db931e70917727e6797941

Observation f625397d-fc9d-4e2d-9788-082c094a3b0e · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 13

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source=arxiv_source observed=2026-08-16T12:10:30.956078Z digest=sha256:fa13fdf55c706c5a29ba9fc0440c6d0c35d15652c825711e32be0bcf66a908a6

Observation 77d3d7ce-ea34-46aa-b1fb-04b9522bfce0 · outbound

This paper cites Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing

Reference 14

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source=arxiv_source observed=2026-08-16T12:10:30.960158Z digest=sha256:6384f9b1ce12bcacd5fec45674a77b1ca7e59a3f0824c8d46bd0304785e8fb0d

Observation a1389b44-281d-4d50-b791-e7350b403733 · outbound

This paper cites Mixtral of Experts.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Mixtral of Experts

Reference 15

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no resolver link, observed 2026-08-16T12:10:30.964242Z

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source=arxiv_source observed=2026-08-16T12:10:30.964242Z digest=sha256:0f76843dc42632cca485a4f92bb96dde47321c630996c0853524c6823be7f624

Observation aac9a438-846e-4cff-9e05-9a54cf1bcfb3 · outbound

This paper cites WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models

Reference 16

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source=arxiv_source observed=2026-08-16T12:10:30.968917Z digest=sha256:5cc19800c76d0c6d5e8cb0339392174e4d6543bc3106b1510499b80ed478d70f

Observation 0fb49374-8d37-42f5-a66b-36c1df2b2d4d · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 17

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raw_fallback, observed 2026-08-16T12:10:31.922004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:30.974149Z digest=sha256:310d02c33a7545391615c9ac9b36eb20c7ae447aa72a38004aa4343a12482005

Observation 6b46e0dc-c6ca-4f1e-9976-5d8a59afcfcd · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-16T12:10:30.978703Z

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source=arxiv_source observed=2026-08-16T12:10:30.978703Z digest=sha256:69e5204538dc047e3f912d154722ba1435f9b39bda55951badb7e7b8f300ba1f

Observation 3493a01b-a5f8-40d1-8da2-7247ba2ac36c · outbound

This paper cites DeepInception: Hypnotize Large Language Model to Be Jailbreaker.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification DeepInception: Hypnotize Large Language Model to Be Jailbreaker

Reference 19

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source=arxiv_source observed=2026-08-16T12:10:30.983352Z digest=sha256:2bc827b5585627dce2e046fb7b3e4b0b97c280e10efcc8bd3faa0a273c3511fd

Observation 25ba5215-cad9-43cf-9589-6974ce7b167b · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 20

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raw_fallback, observed 2026-08-16T12:10:31.907722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:30.988165Z digest=sha256:0eb9bacf2600e8159922189a5e3dc73ce0a935e72a2e3a19d8684d2929e1e1bf

Observation a3965006-66f1-4af7-b424-54cc5c34482a · outbound

This paper cites Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs

Reference 21

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source=arxiv_source observed=2026-08-16T12:10:30.992805Z digest=sha256:9a41274499cd10d6c5dcdb8cc752bbc06113ae34c76094c7657f0f4a676cc486

Observation 9402466e-5bd3-43c8-ad65-98a5b4b713f9 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

Reference 22

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no resolver link, observed 2026-08-16T12:10:30.997511Z

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source=arxiv_source observed=2026-08-16T12:10:30.997511Z digest=sha256:405b6c107a232ae6f0df30f9199ec5a83b98e7dc0d60ce391db55e3817ce5294

Observation 0dba8af0-03c4-4526-a6d5-e5399af47a86 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 23

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raw_fallback, observed 2026-08-16T12:10:31.892305Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.003090Z digest=sha256:bdfc8b0397ef28ab77cb4b4f96c57c695e519a45e4d43077aed918942313334e

Observation cca35e4b-f552-4d59-99dc-e326b1bf4058 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 24

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raw_fallback, observed 2026-08-16T12:10:31.875915Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.008312Z digest=sha256:0d700ffd96ca5608650819673361943316949a60a00bd109b5af641678066397

Observation 09df1fb0-8d16-476d-bdac-33c129394e40 · outbound

This paper cites GPT-4 Technical Report.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification GPT-4 Technical Report

Reference 25

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source=arxiv_source observed=2026-08-16T12:10:31.013275Z digest=sha256:30e77f33046dcce3d9719b8d9b00c4337939ecfbeb51c7d2e14254634aaa1a90

Observation 77fca6da-6759-4b32-a6e5-4e44c4cc73df · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 26

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raw_fallback, observed 2026-08-16T12:10:31.860430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.017732Z digest=sha256:5185ecde115088eee190415e02f67632c6045bcf2aabc390f970100f66dd5647

Observation 91c07911-987f-4f36-af22-692348e74303 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 27

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no resolver link, observed 2026-08-16T12:10:31.022326Z

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source=arxiv_source observed=2026-08-16T12:10:31.022326Z digest=sha256:2aebf770cff4a2b0dd95af7396c815531bd86898d96894be5c1293dd44d44ae2

Observation 28163107-d7c6-4216-b8a1-b3b2d3f08e8b · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks

Reference 28

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source=arxiv_source observed=2026-08-16T12:10:31.026735Z digest=sha256:0b740db8ca0844dbaf962ed879d96482ef5539fc775a9cb5f0a4d1d9ef5386bd

Observation 22002250-cb8b-45a8-88bf-b3ecec84cc53 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 29

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no resolver link, observed 2026-08-16T12:10:31.031366Z

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source=arxiv_source observed=2026-08-16T12:10:31.031366Z digest=sha256:254d3dca0e0da06bd1db11e4e09633b78828afe001f96fc0074cc9328d6737f4

Observation 0ce3cdde-fb4f-4623-922d-eba00cc09e96 · outbound

This paper cites do anything now.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification do anything now

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:10:31.845971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.036107Z digest=sha256:45df63b51f307663115d39f488ddc62c794f6b6997aa08a4dbec49f3bdea929c

Observation c84cdb34-fce2-45c7-afff-22cb6dacb3af · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-16T12:10:31.040694Z digest=sha256:042cc7e54fbf0a28c4b51a8fc150237fc8e61a9afdf8e73eb181c9b8a13bb518

Observation fbfe326f-9e8d-4b9f-8e54-c1bbbfbd1e94 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 32

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no resolver link, observed 2026-08-16T12:10:31.046231Z

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source=arxiv_source observed=2026-08-16T12:10:31.046231Z digest=sha256:51aa6f57a654394ec8f88820cb864dffd9075d3ca1e396d6ec82201d978d715c

Observation 0c50aca7-63f7-4a47-b6ce-969c24fcdf55 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 33

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no resolver link, observed 2026-08-16T12:10:31.050526Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.050526Z digest=sha256:03fb0d29901d5f0c599fb2cddb2146ce4ba22963affa672c1d10164143586bf8

Observation a3a3f5d5-f0c5-4208-a783-e54ec33b01d8 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 34

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raw_fallback, observed 2026-08-16T12:10:31.830997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.055141Z digest=sha256:d2b44a8170b9e803210ff23f344600acfca140307dca4d7a063a3ba200c86ff2

Observation ad9db7de-fa27-496f-bae5-2d5b87b42f9c · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 35

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unresolved
raw_fallback, observed 2026-08-16T12:10:31.815248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.059987Z digest=sha256:064b869556d42d36ea8c0a7adfe2f8825ef46c4441d98b62e41ad05e6cfa0448

Observation c3d0bbf9-03d8-49cd-8153-bb7f999c5e68 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Reference 36

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no resolver link, observed 2026-08-16T12:10:31.064804Z

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source=arxiv_source observed=2026-08-16T12:10:31.064804Z digest=sha256:443cff337a616cf65648ed911e3edfc94a641518131819883e010f70c5108913

Observation b454e88e-88f5-494e-bbc2-cc822f24a2ef · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 37

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no resolver link, observed 2026-08-16T12:10:31.069229Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.069229Z digest=sha256:7762a87886d22cf54e8cd253f752a6ad3579c593478876ba353d0c9afaf31499

Observation f809632a-e5c1-4ace-94e5-516b24aafc35 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:10:31.791377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.073293Z digest=sha256:adc8507692e38a08ffb0a9018333e1062d3e6ee74eedaa67a2ca1f0afec620af

Observation 5a701a33-ae22-4dda-9ab4-a90d4ad77df7 · outbound

This paper cites A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.077809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.077809Z digest=sha256:74b311b81fd31c579d1f7cd3b8c821dfa9d43965632421cdd24413dab20d3b0b

Observation 4fbc9df5-e981-4a39-b09a-557393605066 · outbound

This paper cites GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.083034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.083034Z digest=sha256:11e368696092c37e24a66f98d3ccc015ba26b649bbc14b0852f9b1b3e7c76821

Observation 5fa10b5e-15c8-4546-b981-9aa37f58c252 · outbound

This paper cites Mind the Inconspicuous: Revealing the Hidden Weakness in Aligned LLMs' Refusal Boundaries.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Mind the Inconspicuous: Revealing the Hidden Weakness in Aligned LLMs' Refusal Boundaries

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.088250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.088250Z digest=sha256:d4a59fa8cb41e0ea0bb0cb6dc687c060714c2e69c97ee23f76797392fc7b6680

Observation e0e1ef83-954b-4e3d-baf3-6fe8801ae300 · outbound

This paper cites AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.093405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.093405Z digest=sha256:ef198b716654d35c5a0484f77fe03b59cc142ed253a94acf49b29f18c801fa3b

Observation 7df04aee-21bb-46bd-9156-c2910edfe740 · outbound

This paper cites From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.098839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.098839Z digest=sha256:6a9f1b9468f481a42d9bea744b7358b230f9e1bf51665503b9c7a967aa005e3f

Observation a167b720-56ec-45c0-b909-80cdf83c8234 · outbound

This paper cites an unresolved cited work.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:10:31.776451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T12:10:31.103761Z digest=sha256:70ee105ba233301c50e28f0a84d3c73c5c8539b2945fc7a9adf4aa8d82aa9446

Observation f68c0b31-1ae0-4ea4-a11b-c12c54df7d38 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Instruction-Following Evaluation for Large Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.108393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.108393Z digest=sha256:74057676d7e023dddc44a6114b961c3ca8c5a1be35f3622edade3bdacf854b6a

Observation 6c8fdd32-ceb5-46cb-98db-96a416576729 · outbound

This paper cites EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.112869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.112869Z digest=sha256:4162384cf33627c8a0aba83912eb54c6f1e6f350689173ead99370e2fc6ba797

Observation 0a81a26c-05cf-4e47-ab71-dfbc0f7b0720 · outbound

This paper cites Don't Say No: Jailbreaking LLM by Suppressing Refusal.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Don't Say No: Jailbreaking LLM by Suppressing Refusal

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.116961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.116961Z digest=sha256:01b3e0229d66e94d8b1f2f46a31c6becfa3c785e0d3c5296728b116d37ddeafc

Observation 5e069761-60d8-472b-acb5-1e6bbb1abf55 · outbound

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

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.122045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.122045Z digest=sha256:f4451b7f54f95e29a49f4f185e1dbf7f0c2ccdbb445bc505b7d12d3fffdb522d

Observation e724aed9-0c47-4b6e-bdbe-b1b18cf33114 · outbound

This paper cites online" 'onlinestring :=.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification online" 'onlinestring :=

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.126712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.126712Z digest=sha256:f0d02bbc731f745352110f623a01055e86e40b97b36a361e52d6017413072c2d

Observation cc4eada2-5e12-4294-ab6c-4d89b87174ba · outbound

This paper cites write newline.

DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification write newline

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-16T12:10:31.131754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:10:31.131754Z digest=sha256:a18e96cfbd1ea219081059d097765c9621df1a49f1119e5990d6597391adc673

Pith citing papers

No inbound Pith citation observations are available.