Adversarial Attack on Large Language Models using Exponentiated Gradient Descent | Paper Citation Record

Observation ecfac2b9-d001-430c-80aa-1f47eb2c5117 · outbound

This paper cites Unified Pre-training for Program Understanding and Generation.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Unified Pre-training for Program Understanding and Generation

Reference 1

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Observation 224d9eff-28a6-4853-9cdb-f37c0d937cca · outbound

This paper cites Language mod- els are few-shot learners,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Language mod- els are few-shot learners,

Reference 2

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Observation 6b344d69-fb6c-4b64-ac68-856baac636e4 · outbound

This paper cites Who is GPT-3? An Exploration of Personality, Values and Demographics.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Who is GPT-3? An Exploration of Personality, Values and Demographics

Reference 3

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Observation ea3f0ac9-3db0-4b8c-8e99-4af6bf8154d7 · outbound

This paper cites Large language models surpass human experts in predicting neuroscience results.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Large language models surpass human experts in predicting neuroscience results

Reference 4

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Observation 395a3caf-83ec-451f-b458-6c6446f698e2 · outbound

This paper cites Chatgpt and large language models in academia: opportunities and challenges,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Chatgpt and large language models in academia: opportunities and challenges,

Reference 5

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Observation 06155572-288c-4d6b-b618-4ef88c394a2f · outbound

This paper cites Ethical and social risks of harm from Language Models.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Ethical and social risks of harm from Language Models

Reference 6

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Observation 3fdffb2c-61e4-4d2f-88a4-4530c5d0ef5f · outbound

This paper cites Extracting training data from large language models,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Extracting training data from large language models,

Reference 7

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Observation ade23326-426d-47ea-96a8-08fb19169b21 · outbound

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

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Training language models to follow instructions with human feedback,

Reference 8

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Observation 4bab69ff-0aea-46ea-a11d-5f4c1cc8f16f · outbound

This paper cites Pretraining language models with human preferences,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Pretraining language models with human preferences,

Reference 9

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Observation bb493853-c1ab-4c47-b369-2084b2ed5838 · outbound

This paper cites RAIN: Your Language Models Can Align Themselves without Finetuning.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent RAIN: Your Language Models Can Align Themselves without Finetuning

Reference 10

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Observation dd737c25-6545-473a-a787-3c97b810300d · outbound

This paper cites MasterKey: Automated Jailbreak Across Multiple Large Language Model Chatbots.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent MasterKey: Automated Jailbreak Across Multiple Large Language Model Chatbots

Reference 11

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Observation da1edfa5-ebac-49a4-8dac-588f4095140f · outbound

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

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 12

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Observation 92200545-6874-49d2-9dc1-2d296e23ed14 · outbound

This paper cites Intriguing properties of neural networks.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Intriguing properties of neural networks

Reference 13

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Observation d7a49216-f850-413b-9f8d-660bb3b0ae02 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Explaining and Harnessing Adversarial Examples

Reference 14

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Observation 61eb4008-ecbc-4d42-8f19-1de8b84833a0 · outbound

This paper cites Jailbroken: How does llm safety training fail?.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Jailbroken: How does llm safety training fail?

Reference 15

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Observation a3780aa4-ae9c-4d04-abca-1657f0f21b7c · outbound

This paper cites Prompt engineering in large language models,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Prompt engineering in large language models,

Reference 16

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Observation 14ce5075-4c6a-4b89-9a50-1b37925fadcc · outbound

This paper cites AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.388004Z

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Observation 654f7344-1368-4768-aae3-8abf3f74544f · outbound

This paper cites Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.392502Z

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Observation 06702131-5177-4386-bec7-c3ef6dc06e96 · outbound

This paper cites Are aligned neural networks adversarially aligned?.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Are aligned neural networks adversarially aligned?

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.396800Z

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Observation 01f0e7e2-5dc8-4218-ab0d-752c9ffe1e46 · outbound

This paper cites Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation

Reference 20

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Observation bff6df8c-b177-4d6e-9e59-ec97cd3131be · outbound

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

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 21

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Observation d4da211b-6020-46bf-817d-97544570e12e · outbound

This paper cites Fast Adversarial Attacks on Language Models In One GPU Minute.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Fast Adversarial Attacks on Language Models In One GPU Minute

Reference 22

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Observation 84ad1fc4-de68-4e33-9fb0-16b1bd0f29a7 · outbound

This paper cites Attacking large language models with projected gradient descent,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Attacking large language models with projected gradient descent,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.307932Z

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Observation 28be6349-f425-497c-ad24-49d4f9380f25 · outbound

This paper cites Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.418332Z

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Observation 8674ed51-c1f0-4cee-837e-addf1442e3b4 · outbound

This paper cites Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.423122Z

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Observation 45d0c3f6-4a6f-4b91-98f9-a86b9c764ba6 · outbound

This paper cites Assessing Adversarial Robustness of Large Language Models: An Empirical Study.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Assessing Adversarial Robustness of Large Language Models: An Empirical Study

Reference 26

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Observation cfe9e1c3-21d3-43a2-a2aa-694cabcdd200 · outbound

This paper cites Geometric analysis and metric learning of instruction embeddings,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Geometric analysis and metric learning of instruction embeddings,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.283105Z

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Observation 03fff507-e944-4e25-a0ce-5f076953e413 · outbound

This paper cites Large Language Models as Superpositions of Cultural Perspectives.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Large Language Models as Superpositions of Cultural Perspectives

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.437346Z

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Observation 6ee496b2-3fb9-4b6c-b248-dafb5a595ebb · outbound

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

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.442750Z

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Observation c26ca2eb-4355-42de-acb8-0add32eb973b · outbound

This paper cites Universal Adversarial Triggers for Attacking and Analyzing NLP.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Universal Adversarial Triggers for Attacking and Analyzing NLP

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.448110Z

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Observation 5ecb55fd-450c-412a-8e07-68c412623829 · outbound

This paper cites HotFlip: White-Box Adversarial Examples for Text Classification.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent HotFlip: White-Box Adversarial Examples for Text Classification

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.453009Z

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Observation 031b59af-b7c5-40eb-ad2b-de002ad07537 · outbound

This paper cites AmpleGCG: Learning a Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent AmpleGCG: Learning a Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.457905Z

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Observation d3308ecb-c694-4f5d-8543-3f71de6150ec · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 33

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Observation fdb3f88b-be62-4313-9720-d8d3ec6d2e2b · outbound

This paper cites Efficient projections onto the l 1-ball for learning in high dimensions,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Efficient projections onto the l 1-ball for learning in high dimensions,

Reference 34

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Observation 220e539b-b4b8-4f9a-9de6-08aaac1c4c78 · outbound

This paper cites Crafting ad- versarial input sequences for recurrent neural networks,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Crafting ad- versarial input sequences for recurrent neural networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.259076Z

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Observation 51c67002-a060-4470-90a3-029f7b96093b · outbound

This paper cites Exponentiated gradient versus gradient descent for linear predictors,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Exponentiated gradient versus gradient descent for linear predictors,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.245280Z

Source-reported events for the cited work

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Observation 1f0ac72d-5457-4369-a5b9-348e98340a84 · outbound

This paper cites Exponential gradient with momentum for online portfolio selection,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Exponential gradient with momentum for online portfolio selection,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.230310Z

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Observation eec37898-d42e-4b23-9078-219ed691a07c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Adam: A Method for Stochastic Optimization

Reference 38

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Observation 610f98c6-7859-47c2-b45b-f20c3ab68553 · outbound

This paper cites The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.491670Z

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Observation 8e0d4897-07a3-4234-aedf-fdab31654c2a · outbound

This paper cites Iterative bregman projections for regularized transportation problems,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Iterative bregman projections for regularized transportation problems,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.215871Z

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Observation 6565e7be-3bc6-4dab-8688-02cda61b87ee · outbound

This paper cites An inertial forward-backward algorithm for the minimization of the sum of two nonconvex functions,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent An inertial forward-backward algorithm for the minimization of the sum of two nonconvex functions,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.200720Z

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Observation 6bc92a63-76ee-409f-b546-87659bc84cd3 · outbound

This paper cites Computational Optimal Transport.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Computational Optimal Transport

Reference 42

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Observation 6d20c213-c18d-423d-b8b9-3aa3f4a10790 · outbound

This paper cites An inertial forward-backward algorithm for the minimization of the sum of two nonconvex functions.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent An inertial forward-backward algorithm for the minimization of the sum of two nonconvex functions

Reference 43

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Observation de503318-da62-4e26-a0e7-2beb59d07e89 · outbound

This paper cites Introducing mpt-7b: A new standard for open-source, commercially usable llms, 2023,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Introducing mpt-7b: A new standard for open-source, commercially usable llms, 2023,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.186032Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d2537125-b55c-4f03-bf93-4b0d1331be5b · outbound

This paper cites The Falcon Series of Open Language Models.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent The Falcon Series of Open Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.522098Z

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Observation 8dd98fed-e5d9-49b9-b7cc-b97fc133e0e5 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:29:17.171571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7013ffd1-1a30-4f9b-b00a-6f29aeaddb9b · outbound

This paper cites Mistral 7B.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Mistral 7B

Reference 47

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Observation 43df6081-4a84-4b9f-ac0b-2cd2f4fabcf6 · outbound

This paper cites Safe RLHF: Safe Reinforcement Learning from Human Feedback.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Safe RLHF: Safe Reinforcement Learning from Human Feedback

Reference 48

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Observation 86bb26c6-1c16-446a-b6d2-76881b89c8b9 · outbound

This paper cites The Llama 3 Herd of Models.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent The Llama 3 Herd of Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.544087Z

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Observation af923638-4bb1-4dd4-8a51-57cccc6e8d7f · outbound

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

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.560280Z

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Observation 514f4c1d-22c2-4815-8c9f-08c0818c727f · outbound

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

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.555115Z

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Observation 2717cc57-55ef-4152-8970-3dcd38bde6d9 · outbound

This paper cites Adversarial Attacks on Large Language Models Using Regularized Relaxation.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Adversarial Attacks on Large Language Models Using Regularized Relaxation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T21:29:16.565174Z

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Observation e64fdc34-cb90-4957-ab86-426938272978 · outbound

This paper cites Iterative Bregman Projections for Regularized Transportation Problems.

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent Iterative Bregman Projections for Regularized Transportation Problems

Reference 2014

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T21:29:16.747727Z

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