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Paper Citation Record · LEDGER

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

As of 24 August 2026, this Paper Citation Record lists 100 of 115 outbound references and 6 inbound Pith citation observations for arXiv:2501.15269.

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

pith.paper-citation-record.v1
2501.15269 v1

Coverage vector

measured 100 of 115 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:29:28.341757Z

measured 106 of 106 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:32:34.540866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:34:01.805164Z

Reference resolution

100 of 115 outbound references displayed

  • verified exact3
  • verified fuzzy12
  • unresolved85
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1085029e-f5bc-4e3e-b53f-e9c6969a3217 · outbound

This paper cites GPT-4 Technical Report.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-10T14:29:27.846865Z digest=sha256:de1f1381003369ce2690e3451648390024e1612f1dde04297814b8829cdd9f73

Observation 801c4a88-2033-41f8-81f3-88ed53b86144 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Flamingo: a visual language model for few-shot learning

Reference 2

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source=pdf_text observed=2026-08-10T14:29:27.851227Z digest=sha256:dd9f19358e9a6f86be3e4aa800cf344b5e4a310a5126df78eec6b2d22d96ea2e

Observation 85acb3bb-d89c-4fd5-b14f-e11da302d963 · outbound

This paper cites Vqa: Visual question answering.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Vqa: Visual question answering

Reference 3

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source=pdf_text observed=2026-08-10T14:29:27.854969Z digest=sha256:c5abc9d2d673b0156a2bd70b506bf749895c04e87acc0d5ad95b7e498d103144

Observation d7d1d599-7e2e-416e-9651-168a7cef0606 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 4

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source=pdf_text observed=2026-08-10T14:29:27.858635Z digest=sha256:e66e553dafd28cc743c13b73cc0f0f968239f44e4cd2835a094c8776cb84a892

Observation 8b541e01-9d04-44b2-b5fd-2717b63d2b97 · outbound

This paper cites Hallucination of Multimodal Large Language Models: A Survey.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Hallucination of Multimodal Large Language Models: A Survey

Reference 5

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source=pdf_text observed=2026-08-10T14:29:27.863635Z digest=sha256:4dfa0c9a4a814f6498c1615ee43485e50201353f40e8c96061ab47dd48e85edd

Observation 41ac2492-6092-4054-903f-a45f05b2f410 · outbound

This paper cites The (r) evolution of multimodal large language models: A survey.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink The (r) evolution of multimodal large language models: A survey

Reference 6

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source=pdf_text observed=2026-08-10T14:29:27.867663Z digest=sha256:0d4a12bc61baa81b3dfd8bd3377df9ec7a8fe0bcefc72471d99c5865adb8d79c

Observation 1d59d971-b065-444d-ad33-f710b95db610 · outbound

This paper cites Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization

Reference 7

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source=pdf_text observed=2026-08-10T14:29:27.871553Z digest=sha256:bb341206ee56ee5c20b46d5807a2a5831190da69a8111e62153f9d40ed9428a8

Observation dd212740-b38c-48ab-be8d-5b4d29ca6468 · outbound

This paper cites Lion: Empowering multimodal large language model with dual-level visual knowledge.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Lion: Empowering multimodal large language model with dual-level visual knowledge

Reference 8

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source=pdf_text observed=2026-08-10T14:29:27.876564Z digest=sha256:c2e6181b9f1ebbe8ae93239d893d70968d94be5ae0071a710824901e07377def

Observation a308abfb-da00-43d2-b970-4cca791c8646 · outbound

This paper cites ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Reference 9

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source=pdf_text observed=2026-08-10T14:29:27.880204Z digest=sha256:184e36e8baed06d560f17774cb2da489b6ccbb77509d7721ec890dc67e7b91d1

Observation 847f7306-1e7e-4928-b61e-3f490958965d · outbound

This paper cites MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 10

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source=pdf_text observed=2026-08-10T14:29:27.884637Z digest=sha256:6288e61a2a2fb0b520f1cf9ca057f349e0b58ec088b4c846951800fe8b6af31d

Observation 189f1814-aa29-4386-aced-6b0188ad64aa · outbound

This paper cites IPL: Leveraging Multimodal Large Language Models for Intelligent Product Listing.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink IPL: Leveraging Multimodal Large Language Models for Intelligent Product Listing

Reference 11

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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.

source=pdf_text observed=2026-08-10T14:29:27.888840Z digest=sha256:76fe4e8cc0fc1d61f8f8ebdff0661dccf61146a407999b0bfc5fcd4a0cc43a49

Observation 74dc016f-f815-49f1-bb9b-f7ef715dfa01 · outbound

This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 12

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source=pdf_text observed=2026-08-10T14:29:27.892821Z digest=sha256:53992d50f42a936a3319428f6242beda47ecfeb96891b066b35c0454b9392fc4

Observation db0fafe1-74d4-4dfa-9aba-70883dead080 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 13

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source=pdf_text observed=2026-08-10T14:29:27.896365Z digest=sha256:1391844a5390967e138956bd2520a1e9a4edafed4a983db75cfc30f26cc5dc57

Observation 74352b39-8c25-4ace-887d-21071d6d40a5 · outbound

This paper cites Multi-Object Hallucination in Vision-Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Multi-Object Hallucination in Vision-Language Models

Reference 14

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source=pdf_text observed=2026-08-10T14:29:27.900835Z digest=sha256:9125ef0c2925e3f5d22e39d4a72126b00693fa8b2c8e157c36e9242bdce3ca57

Observation 5052bb9d-86ae-4270-ba46-a70f7f0b920b · outbound

This paper cites Transfer Attack for Bad and Good: Explain and Boost Adversarial Transferability across Multimodal Large Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Transfer Attack for Bad and Good: Explain and Boost Adversarial Transferability across Multimodal Large Language Models

Reference 15

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source=pdf_text observed=2026-08-10T14:29:27.904771Z digest=sha256:bd2a95f5737ec6285f4be1203d7655285b3c15a6a39d95af1ca0dbd02c8b1c3a

Observation 9cd4ca39-9df0-4cff-8292-9f30898ba5d7 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 16

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source=pdf_text observed=2026-08-10T14:29:27.908486Z digest=sha256:c6005ec9fdbb40630dd832e79c246b8a595d35a4f59b376e3156fa8c676f5efd

Observation 2123aedd-9f85-4e36-ad58-fd53aebdc76a · outbound

This paper cites Optimal structure identifi- cation with greedy search.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Optimal structure identifi- cation with greedy search

Reference 17

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source=pdf_text observed=2026-08-10T14:29:27.911856Z digest=sha256:6590b1fb1e8ff799708a7b7eab09bcdc498a20aaadfb1c24e2e4d47601904d82

Observation 552ab65e-a6f6-4d2a-bd3e-0cf30613f362 · outbound

This paper cites On the robustness of large multimodal models against image adversarial attacks.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink On the robustness of large multimodal models against image adversarial attacks

Reference 18

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source=pdf_text observed=2026-08-10T14:29:27.915532Z digest=sha256:7becc01ef7cae7b96be413c1c7ca3cac6cc4a58f26988a235d3e2b6935cba3e7

Observation 0bf73e6b-7975-4970-80d8-ef46c0e2d9c6 · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 19

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source=pdf_text observed=2026-08-10T14:29:27.919151Z digest=sha256:220ea253f0902fa3c27c0e0dad603a674b955b4dd7a4dd1ba253229e9a79cce5

Observation f2de51ba-2160-4adf-8458-b05c90737a74 · outbound

This paper cites Vision transformers need registers.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Vision transformers need registers

Reference 20

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source=pdf_text observed=2026-08-10T14:29:27.923851Z digest=sha256:b65d0df1ac8675bf14c8f36e5158f42301ae8cad4bdb28dd4b6460514c76104d

Observation f2f4adb4-faaf-4e59-8bb2-bbc09de2f695 · outbound

This paper cites HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Driving.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Driving

Reference 21

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source=pdf_text observed=2026-08-10T14:29:27.927310Z digest=sha256:61decc9761075d4baeb6791865b4aab8c624248888fae20384b65fd8ae517487

Observation 58028e65-4650-4515-a6d0-bc4e182c951c · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink An image is worth 16x16 words: Transformers for image recognition at scale

Reference 22

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source=pdf_text observed=2026-08-10T14:29:27.931147Z digest=sha256:56dd2f933b961f767f6d7c17852d638024d9512592ccec172e31a827c1b96334

Observation f1ef4f17-242d-4549-84c6-fc455f335913 · outbound

This paper cites Eva: Exploring the limits of masked visual representation learning at scale.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Eva: Exploring the limits of masked visual representation learning at scale

Reference 23

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source=pdf_text observed=2026-08-10T14:29:27.935698Z digest=sha256:aa000b95b124888fd284f058da6963cee9cc39c2d6daa4c48c54b1a3eec8711b

Observation 5505cf1a-0d08-4870-bca4-566f3218cabc · outbound

This paper cites MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning

Reference 24

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source=pdf_text observed=2026-08-10T14:29:27.939969Z digest=sha256:7be5666e46adb9c7e10a88aa6098ee5d00af52e86ab2753879cbe4bb865e32be

Observation 52052379-10f3-4a09-a9f3-4e07a1fdd88d · outbound

This paper cites Adversarial robustness for visual ground- ing of multimodal large language models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Adversarial robustness for visual ground- ing of multimodal large language models

Reference 25

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source=pdf_text observed=2026-08-10T14:29:27.943665Z digest=sha256:7968d9dce070a6691f63b9a96baa7a8a86195025150dc57c2f1a0c1db22b7fff

Observation 6e8dad2c-b584-4946-840e-5eea5a6ab8c8 · outbound

This paper cites Inducing high energy-latency of large vision-language models with verbose images.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Inducing high energy-latency of large vision-language models with verbose images

Reference 26

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source=pdf_text observed=2026-08-10T14:29:27.947472Z digest=sha256:78518e9c5e7e48350dd4f610bd7e0dd3a7b55426f07166aaeb97e9cba3b7fb2e

Observation a6e18ee9-723c-42ce-ae64-2d9d3a993120 · outbound

This paper cites MultiModal-GPT: A Vision and Language Model for Dialogue with Humans.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink MultiModal-GPT: A Vision and Language Model for Dialogue with Humans

Reference 27

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source=pdf_text observed=2026-08-10T14:29:27.951706Z digest=sha256:850dc212dd9b1f2486dfd90be92cb2bdff8d78f9e137d6322d901fc642c7b514

Observation e8daa2fc-b5c4-433c-9815-f0bc5301c395 · outbound

This paper cites FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts

Reference 28

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source=pdf_text observed=2026-08-10T14:29:27.955780Z digest=sha256:e9739117bac36eaca63e9b9ef140fd9aa016f8feb97d1162831ef807206a045b

Observation bd183a0c-0e20-469a-b8e4-8ae61fac2a91 · outbound

This paper cites Hallusionbench: an advanced diagnostic suite for entangled language hal- lucination and visual illusion in large vision-language models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Hallusionbench: an advanced diagnostic suite for entangled language hal- lucination and visual illusion in large vision-language models

Reference 29

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source=pdf_text observed=2026-08-10T14:29:27.959655Z digest=sha256:ca96f7c18b4390f5b48a2d2f87a95536b9aa2de42a38c1f60907dc8ca8fca18b

Observation c998b18e-4e50-4bca-b5b2-1741d40c3e0a · outbound

This paper cites Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 30

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source=pdf_text observed=2026-08-10T14:29:27.963407Z digest=sha256:101710556c2cbc81ccd56c33d971a065bfe46b802a2fce05e5adf625f4ea6b82

Observation b7430202-b296-46fe-bf57-0c57a47a80db · outbound

This paper cites Clipscore: A reference-free 16 evaluation metric for image captioning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Clipscore: A reference-free 16 evaluation metric for image captioning

Reference 31

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source=pdf_text observed=2026-08-10T14:29:27.968378Z digest=sha256:33d9dc970c6b79ac899afc6c14f524712b8c67d6ed2dd159b5b510b81bb18ee7

Observation cc13ba67-40da-402c-a6d0-57f9316487a2 · outbound

This paper cites The Curious Case of Neural Text Degeneration.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink The Curious Case of Neural Text Degeneration

Reference 32

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source=pdf_text observed=2026-08-10T14:29:27.972140Z digest=sha256:8656d9e2f8256c6129152d5b3d8f443296a99d5bf580df550a54efcd0b48dcc3

Observation 3cda6207-2bab-46be-b681-479e0fc498f9 · outbound

This paper cites Naturalistic physical adversarial patch for object detectors.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Naturalistic physical adversarial patch for object detectors

Reference 33

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source=pdf_text observed=2026-08-10T14:29:27.975776Z digest=sha256:2cb86e8819cc42d64cb9bd7c3a1c3e0a1bdc93ec9008aab0206268b363d12fa1

Observation 20466ca6-7dd4-417d-8887-b9d8e8b146ee · outbound

This paper cites Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation

Reference 34

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source=pdf_text observed=2026-08-10T14:29:27.979180Z digest=sha256:cfa92e986a14e12cf8615b5cb42d4f8c3e0b12ae8673caae30f298a2df540d82

Observation 3acce825-9769-4724-8fa4-3b7a1478bb33 · outbound

This paper cites Hallucination augmented contrastive learning for multimodal large language model.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Hallucination augmented contrastive learning for multimodal large language model

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:27.982581Z digest=sha256:2b9954b3eabeb07ab3414ca7762bb3c974a3bdf06ab7ad528e821c150fcb1aea

Observation 76070ec9-ee0f-4401-a658-c7b443852965 · outbound

This paper cites Diffattack: Evasion attacks against diffusion-based adversarial pu- rification.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Diffattack: Evasion attacks against diffusion-based adversarial pu- rification

Reference 36

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source=pdf_text observed=2026-08-10T14:29:27.985981Z digest=sha256:b2c1dba31e52ffe3b682e0728ced14e6578009961374aacfeb9351beb8dfb3b0

Observation 4a662d7d-fbcd-4f5a-b8eb-fe050e5cb1d0 · outbound

This paper cites Vi- sual genome: Connecting language and vision using crowdsourced dense image annotations.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Vi- sual genome: Connecting language and vision using crowdsourced dense image annotations

Reference 37

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source=pdf_text observed=2026-08-10T14:29:27.989642Z digest=sha256:3327b467f0dc726d4aa6b26950ba052098dee02fabb4b58186c63551bd808983

Observation 3fb5a997-1bb6-4129-8c84-3828e00c09ac · outbound

This paper cites Gemini Pro Defeated by GPT-4V: Evidence from Education.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Gemini Pro Defeated by GPT-4V: Evidence from Education

Reference 38

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verified exact
local_arxiv, observed 2026-08-10T14:29:28.844132Z

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.

source=pdf_text observed=2026-08-10T14:29:27.993212Z digest=sha256:7f1b07fb48999d6778f226d3b7a30319a1a06bc948da025541357ff708ee5cc9

Observation 8971a31e-e55d-48d4-ae24-075e0739975a · outbound

This paper cites Robust evaluation of diffusion-based adversarial purification.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Robust evaluation of diffusion-based adversarial purification

Reference 39

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source=pdf_text observed=2026-08-10T14:29:27.996615Z digest=sha256:a37b8f59e0aeff1c0778bd91bab04fc2973f2a144113e6dcd8187e1a31ea34cc

Observation 0b5459d7-e655-4f96-b2ef-3fe2e08bca7e · outbound

This paper cites Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision

Reference 40

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source=pdf_text observed=2026-08-10T14:29:28.000337Z digest=sha256:d356c2c1a0635181d8ebe3b3cbdff01be9f3e04acc610e0c0e05f25a37435b4a

Observation 8f18a498-90f4-4086-a615-a9f29c64188a · outbound

This paper cites Miti- gating object hallucinations in large vision-language models through visual contrastive decoding.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Miti- gating object hallucinations in large vision-language models through visual contrastive decoding

Reference 41

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source=pdf_text observed=2026-08-10T14:29:28.004970Z digest=sha256:fb2415e388af19d470e03e77400bc892ad4c13e03a4cafa6e37d7b217123d689

Observation 3c96ac91-d802-4803-88e7-5b8a7db3f860 · outbound

This paper cites Llava-med: Training a large language-and-vision assistant for biomedicine in one day.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Llava-med: Training a large language-and-vision assistant for biomedicine in one day

Reference 42

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.008354Z digest=sha256:7a04b4a2fc332c6958f99e0253d8c76dccec88c51710aa92a63fc26128d514f1

Observation 31850786-e223-45f7-b996-6f84eb60e2d2 · outbound

This paper cites Manipllm: Embodied multimodal large language model for object-centric robotic manipula- tion.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Manipllm: Embodied multimodal large language model for object-centric robotic manipula- tion

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.012256Z digest=sha256:86781999b025b72f928dd9b8eba4896f1342300dc1ba2d1c75be830e19c91b69

Observation 48082089-62de-4957-87dd-63aa377741fb · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Evaluating Object Hallucination in Large Vision-Language Models

Reference 44

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no resolver link, observed 2026-08-10T14:29:28.017232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.017232Z digest=sha256:456d9eebea1c9406265df53c02f4ddd1aa625775fcd5cc3ef5ddad9491bfc33e

Observation 3dd82601-0890-4716-a2cc-6dbf097ef0be · outbound

This paper cites Monkey: Image resolution and text label are important things for large multi-modal models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Monkey: Image resolution and text label are important things for large multi-modal models

Reference 45

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.021367Z digest=sha256:e4b4a104677ab55dd39e3219d25cbd9b47a1febb024474fe707236822b57ba55

Observation ae855e47-b807-4cac-9d5d-c50bb6ff6c3a · outbound

This paper cites Harnessing GPT-4V(ision) for Insurance: A Preliminary Exploration.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Harnessing GPT-4V(ision) for Insurance: A Preliminary Exploration

Reference 46

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.025287Z digest=sha256:17a13f120854eac28811a14a4e3469ab73466cd7441c2e1d1ceff3c3d170099d

Observation e30fc5b9-0107-450e-979a-552c7b088466 · outbound

This paper cites Microsoft coco: Common objects in context.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Microsoft coco: Common objects in context

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.029799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.029799Z digest=sha256:50ed58f980e0deca3a9dfc8b581317da765f8b32846a9ba590a8ddbde60b2f80

Observation 790a7b4f-77f9-48d3-9e00-37211a188720 · outbound

This paper cites Interpreting and Mitigating Hallucination in MLLMs through Multi-agent Debate.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Interpreting and Mitigating Hallucination in MLLMs through Multi-agent Debate

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.033866Z digest=sha256:bc8cdab135e0fb2679d5d5db57b52500f4c4c53f5d4987fd88589d8a35c94f48

Observation 9e3a6a25-5c4f-4a5b-bd2e-d60400782eb9 · outbound

This paper cites GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis

Reference 49

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unresolved
no resolver link, observed 2026-08-10T14:29:28.038592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.038592Z digest=sha256:9b39bced939906fc0b118e9a5e3de00358de5d9095179a69722ce04f6dd83a6b

Observation 2c1a49b8-b6af-4e6d-a559-f4ce8a8a6cab · outbound

This paper cites Mitigating hallucination in large multi-modal models via robust instruction tuning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Mitigating hallucination in large multi-modal models via robust instruction tuning

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.042623Z digest=sha256:0834d7532132773e8776899102694c47d3c5f5230ccbdb805c2674ca605c8fb6

Observation 33fab8f4-cdec-4733-bad3-f3c3bf1ab5ba · outbound

This paper cites Improved baselines with visual instruction tun- ing.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Improved baselines with visual instruction tun- ing

Reference 51

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T14:29:28.046459Z digest=sha256:203456bc8cb581d76cd6d6fb1cacc1fd339e2391da4ffee5a3845d0d897ace20

Observation 6f6c710a-1f2b-413b-97d7-ec4aebaa2cb2 · outbound

This paper cites Visual instruction tuning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Visual instruction tuning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.049942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.049942Z digest=sha256:3d12296d2e67abfa5391a873c41702802c2fa5aec61a85c535f78be8db4f12a7

Observation 347c487f-2aa3-4030-b7f3-d5412e5620d4 · outbound

This paper cites Models See Hallucinations: Evaluating the Factuality in Video Captioning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Models See Hallucinations: Evaluating the Factuality in Video Captioning

Reference 53

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.053371Z digest=sha256:412ad94a21035f839cdc2db965c335f98fd7e8161f821a078efc1f6267f100e7

Observation 4a53f1a0-06e6-4818-8908-e0e4d35b268c · outbound

This paper cites PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.056851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.056851Z digest=sha256:bf785b53d4636d4e4526a64735fbbff6aed74d5a4263bafb3cbc865dc422a3c0

Observation 32dc33f8-9e26-4b78-869c-fc45190565cc · outbound

This paper cites MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models

Reference 55

Resolution
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no resolver link, observed 2026-08-10T14:29:28.060424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.060424Z digest=sha256:d6a5c9ddc44028c30386d95c4588e6d2c103e6b8646469c908fbe55535750283

Observation 20260262-0ed8-4ab3-8e44-f8ddfd4f377c · outbound

This paper cites MMInstruct: A High-Quality Multi-Modal Instruction Tuning Dataset with Extensive Diversity.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink MMInstruct: A High-Quality Multi-Modal Instruction Tuning Dataset with Extensive Diversity

Reference 56

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.064100Z digest=sha256:d4d8debc061c42ab4d5d9ee1c5eb257cf86f8e1594da8330a03428f6f19a2075

Observation 83840c11-7195-427f-a43d-73e3cacd31fe · outbound

This paper cites Robollm: Robotic vision tasks grounded on multimodal large language models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Robollm: Robotic vision tasks grounded on multimodal large language models

Reference 57

Resolution
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no resolver link, observed 2026-08-10T14:29:28.067564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.067564Z digest=sha256:cc672a4189ed769da690b433c3e775a71a211235315f75f2f3039b9d418ea4b8

Observation 8dd12174-451e-401a-8b1d-90ec30f71686 · outbound

This paper cites JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks

Reference 58

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.071084Z digest=sha256:32b7b6673bb9217c1bb15cc8071636773bc938f37156936870c452115be70c10

Observation d06010ab-dcd7-464f-9472-a6daabaff6c6 · outbound

This paper cites Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Character.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Character

Reference 59

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no resolver link, observed 2026-08-10T14:29:28.074482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.074482Z digest=sha256:39d54b2eb2455d20a94bad442efda745bc6706f3827d50ea5af7fcf376ce509a

Observation fb2887a6-1cb3-47c2-b0b9-b24129c5184f · outbound

This paper cites Ok-vqa: A visual question answering benchmark requiring external knowledge.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Ok-vqa: A visual question answering benchmark requiring external knowledge

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.078245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.078245Z digest=sha256:dea7c7edfd021a2b3826d9a9e6e24a8b4f0e040a93031cc67aea92a4e803fc77

Observation 1c4a6f49-ac79-4291-a5ef-452841b5138d · outbound

This paper cites Large Language Models: A Survey.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Large Language Models: A Survey

Reference 61

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.081919Z digest=sha256:5a4d4ea33d5d89162627095e187f965cd076fb621d2a9b92f4893e84ed6941fb

Observation 6a8bd129-2a24-45c1-b7bc-743a381b7d52 · outbound

This paper cites Yo'LLaVA: Your Personalized Language and Vision Assistant.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Yo'LLaVA: Your Personalized Language and Vision Assistant

Reference 62

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.086662Z digest=sha256:c2f155a8ba53b457f4a7fd483b758dfdf88f1d0dbbc2feace64553d107b259d8

Observation d1e7d157-24e3-45a2-af25-c004c017afe1 · outbound

This paper cites Jailbreaking Attack against Multimodal Large Language Model.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Jailbreaking Attack against Multimodal Large Language Model

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.090315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.090315Z digest=sha256:4f66520a8b9de2adba9e09d07aff6df3c4160477c1b97bf458df5cc49102c632

Observation adf28c34-7f99-4986-9011-ebd7b34f0dcb · outbound

This paper cites Gpt-4v(ision) technical work and authors.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Gpt-4v(ision) technical work and authors

Reference 64

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unresolved
no resolver link, observed 2026-08-10T14:29:28.094725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.094725Z digest=sha256:2cda59d27460fd07d65718a467a05a0218d3d58ff804a60c690d2f852467fab2

Observation fb5e4e67-91c0-4dbf-b3e5-1215c72c1928 · outbound

This paper cites Gemini flash.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Gemini flash

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.098994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.098994Z digest=sha256:9f62c4c32639b8a2b4d87f2fa8d5c793223ac6caa450bf9b80d74468d714cf04

Observation 4c4e6060-9076-4d9d-821b-387505eb533b · outbound

This paper cites Gpt-4o mini: advancing cost-efficient intelli- gence.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Gpt-4o mini: advancing cost-efficient intelli- gence

Reference 66

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.102622Z digest=sha256:d8cd842c570a7f8c57d69576fbfc83eb1333b1a4eb9012f624bbaed996f69f2e

Observation 0fc84af7-7740-4afa-b1b7-2c771c7b9d6b · outbound

This paper cites Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & Hallucinations.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & Hallucinations

Reference 67

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.106071Z digest=sha256:a025d1f89d917e22436830b09420573a6d6520445f1ab87aa3a43fd539b51666

Observation 34d20abf-4daa-4e04-ac0e-de1bd311da0c · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.110780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.110780Z digest=sha256:4dfabfa2a5e965f5a9bd8f3c628047b887f819e11601d504081266e62a8d339a

Observation 4cceb0a5-18c8-41fa-8f02-c3161de806cb · outbound

This paper cites Grounding multimodal large language models to the world.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Grounding multimodal large language models to the world

Reference 69

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unresolved
no resolver link, observed 2026-08-10T14:29:28.114766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.114766Z digest=sha256:cd5df96dbfc43e931bb5bbb492f45036bf9bcc3bbeabddd51cb2966270c7fb9a

Observation fdd19afd-82a8-4ef0-a335-634424fb29d3 · outbound

This paper cites Visual adversarial examples jailbreak aligned large language models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Visual adversarial examples jailbreak aligned large language models

Reference 70

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.118822Z digest=sha256:ac5cc35f97f9ee2192ce1ff45ac0aa0785e035d6373ab3b829b8449e05bafbc7

Observation ca80f517-2ac1-4712-bd7f-3c234b98d298 · outbound

This paper cites Learning transferable visual models from natural lan- guage supervision.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Learning transferable visual models from natural lan- guage supervision

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.122547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.122547Z digest=sha256:460827b4f123de6b1e0b060a0e91252fa56b0df7f2e9fac1c892a00b238e4161

Observation 7b31e1eb-3310-4da8-82b9-6debc1f1dbeb · outbound

This paper cites Object hallucination in image captioning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Object hallucination in image captioning

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.387161Z

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.

source=pdf_text observed=2026-08-10T14:29:28.227605Z digest=sha256:bb1be48da44f16301e6a232a2c0b5c8b524475fe4fc36e292b2615adb09db98c

Observation 7be458b5-51b1-4e2d-8ad1-e8c301c9cee0 · outbound

This paper cites Laion coco: 600m synthetic cap- tions from laion2b-en.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Laion coco: 600m synthetic cap- tions from laion2b-en

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.375809Z

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.

source=pdf_text observed=2026-08-10T14:29:28.231619Z digest=sha256:577fb2d765706304df718c6cf387682912653e772566c66ec5b40ddb9842910d

Observation 240c93c4-f465-4f6f-a528-098b219eaf5a · outbound

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

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.364508Z

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.

source=pdf_text observed=2026-08-10T14:29:28.235436Z digest=sha256:a6e2fedb34011e25ebd18e41975816cb19d9be027d8d58a9001e91a26df64e6b

Observation d9d1ea95-bad3-484c-8f22-4482098919c9 · outbound

This paper cites Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.240127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.240127Z digest=sha256:a51419902e5c52d15fc4323f12cd9c061a6294c3a2b558636003f154c066f95b

Observation 0d0849ed-ecd4-4787-9f36-e4c290ebaccc · outbound

This paper cites Self-training large language and vision assistant for medical question answering.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Self-training large language and vision assistant for medical question answering

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.354145Z

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.

source=pdf_text observed=2026-08-10T14:29:28.244180Z digest=sha256:1ad477af92ff9577a08e65f4c50c3dfed5639e25e16a9906263ceb85e3ca0b0e

Observation c4fc7447-6fa3-4e0c-aac4-f959644e3131 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.248761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.248761Z digest=sha256:dfe7342faa6e0c5791b06bee7abf105548d4aab67a0081c115b18a57c533e437

Observation e4e75d29-822e-4c62-bd20-0cba3bcc7332 · outbound

This paper cites An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual Representation.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual Representation

Reference 78

Resolution
verified exact
local_arxiv, observed 2026-08-10T14:29:28.629907Z

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.

source=pdf_text observed=2026-08-10T14:29:28.252792Z digest=sha256:3ac47977c6667b69060092f936d52bd2ee99aa5b1e5b3bb95d3b01564f2d0562

Observation d874f987-be29-40bd-a1f7-94cac49a0673 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink LLaMA: Open and Efficient Foundation Language Models

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.257332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.257332Z digest=sha256:ca528ec229fd6d3ef086c3a0d1df6ac2a488c7731ed4fd7bfea6b6071f5e9a34

Observation 92c8cdad-cf58-48c9-b88d-4d0257b2aa59 · outbound

This paper cites Attention Is All You Need.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Attention Is All You Need

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.261514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.261514Z digest=sha256:e0aa8a1b10fb12103b3ab42f988d00e2c4730589b6fa68b92cb63ef1101b230d

Observation 419f1e5e-7dda-4b92-89f3-0dbd140b6289 · outbound

This paper cites AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.265994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.265994Z digest=sha256:8a67fbeb17fabaa44dc72b847d6d1ff80d9b4611a5100a5bc3df71d2cd61c622

Observation efb8a9ea-9688-4b1d-894b-bf58ac43da7b · outbound

This paper cites Label words are anchors: An information flow perspective for under- standing in-context learning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Label words are anchors: An information flow perspective for under- standing in-context learning

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.343500Z

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.

source=pdf_text observed=2026-08-10T14:29:28.270174Z digest=sha256:f423b4386b6cfe2e85d9c0cb0f3011dfee0554fdcab6184818f65b04ec28914b

Observation d42c0744-2cd9-43fc-bd22-079b58f5946e · outbound

This paper cites AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.274493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.274493Z digest=sha256:65616bddf86814b1c9adf15d2e396f072ad4fa26faaf396e47164c2774b08dc5

Observation 12669dc7-45b5-4a1c-88bf-31dc496043a2 · outbound

This paper cites Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.278563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.278563Z digest=sha256:bdcad21cf2c820792a3f61f036a1d84cbc288cf01803dbca5e6d38d46a611b07

Observation 1c2e545c-89de-487b-815d-27e839f68b4e · outbound

This paper cites Efficient streaming language models with attention sinks.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Efficient streaming language models with attention sinks

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.332619Z

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.

source=pdf_text observed=2026-08-10T14:29:28.282505Z digest=sha256:f14b5f21b0788fbf98536706deda9ec20f07539eed82edc6ff336a65e505ac6c

Observation 06624e22-3b03-4c6f-8cbd-6adc3c90ae81 · outbound

This paper cites Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.285836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.285836Z digest=sha256:6d339d8cb1c5d22f9d77bdfcb885b29c0819afa01e98126c999a58c864480b35

Observation 5347bd0a-9cd8-4195-824c-e6edb3403e8c · outbound

This paper cites Self-evaluation guided beam search for reasoning.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Self-evaluation guided beam search for reasoning

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.322101Z

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.

source=pdf_text observed=2026-08-10T14:29:28.289301Z digest=sha256:ec6927417ec3365aba8ad3342b8ac32b42499f84c1ac6d7c5c6cb660a0f005e8

Observation c8f13d1e-e2bb-49cb-8db6-647abbe28d04 · outbound

This paper cites Drivegpt4: Interpretable end-to-end au- tonomous driving via large language model.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Drivegpt4: Interpretable end-to-end au- tonomous driving via large language model

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.310497Z

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.

source=pdf_text observed=2026-08-10T14:29:28.292954Z digest=sha256:d8f7073efd8a99a622f9a787cf2bcaff954e251fa4198e01e257143d9c3c0adb

Observation be00772f-ab01-4e96-9645-29dd506a6267 · outbound

This paper cites UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.296141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.296141Z digest=sha256:a27bd6e431a5a7cbb0b1544b14c2ae214b1c7d2462cd171bfa8399127884df52

Observation 68a55dc5-5502-4a89-ab29-33ee49b962d3 · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.299813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.299813Z digest=sha256:ac19e6bd6dce23e7888cf4dbee59409bb8ae514c9fc5d5e08717e232e5aa015a

Observation c03b8bc0-1090-43d1-aa14-905524ae4ca9 · outbound

This paper cites Woodpecker: Hallucination Correction for Multimodal Large Language Models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Woodpecker: Hallucination Correction for Multimodal Large Language Models

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.303331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.303331Z digest=sha256:2613ba8f31ad596e84f878b02d5c96e46165384ca64798bf6ad3ccbfeec92357

Observation 1133fe17-9355-436b-956f-2df28ff037be · outbound

This paper cites Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.307138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.307138Z digest=sha256:71700b527cb9c2735ab3f8cccde7b9ce82d0043bfdc6ab129b88983ddbfa2952

Observation 532e901e-98eb-49ec-bcb3-da71f6749e5f · outbound

This paper cites Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.299253Z

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.

source=pdf_text observed=2026-08-10T14:29:28.310774Z digest=sha256:a53bd95add137e3770264c8bc91aacc1cf2159da2e6a97978796ff600771e0da

Observation ba79c143-3998-4f6a-8444-4a59f9366f26 · outbound

This paper cites Rlhf-v: Towards trustworthy mllms via behavior alignment from fine- grained correctional human feedback.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Rlhf-v: Towards trustworthy mllms via behavior alignment from fine- grained correctional human feedback

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.287588Z

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.

source=pdf_text observed=2026-08-10T14:29:28.314920Z digest=sha256:601e0ea0116bba3447399bd2682ab98fd8816fc4ebc054260cbb2ca1fa4ceda6

Observation f379fb86-6723-4b09-8d16-9290b406a22e · outbound

This paper cites Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.318562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.318562Z digest=sha256:a60a4ac867a42fbbe45ff5ef6c6b197b7147f3a67db807691d617129fe854c25

Observation db51e8cf-b656-4296-9df9-53d5ca57e3d8 · outbound

This paper cites Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.323931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.323931Z digest=sha256:ed76c23c79d1cfa10f6b7e9c157a594b4e4d452623edb6f6aa354f5f162231b9

Observation f1dfbae8-9876-4e0c-a730-6dd11911cf5b · outbound

This paper cites LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.328190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.328190Z digest=sha256:672441b99ae7fa5e61de4a6e7b5b4b600e13f75c2f40bbd344b40633f2e1f75a

Observation c05361fe-9d17-4206-a37d-5467f0ed5f7d · outbound

This paper cites On evaluating adversarial robustness of large vision- language models.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink On evaluating adversarial robustness of large vision- language models

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.274888Z

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.

source=pdf_text observed=2026-08-10T14:29:28.333110Z digest=sha256:099e6acf055bdd2a325634780c81351371f2499461dd2c8b5bc3f679b7bbf86e

Observation d65fa5c5-8b38-4691-997b-7d159e6ba07d · outbound

This paper cites Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-10T14:29:28.337407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.337407Z digest=sha256:62ac10a71e89f6591bff60c7d5c9ccd4c60d5193f6c55b00e0784e278455104d

Observation 04c7a2c8-8f67-49cd-a605-bbb6ce9a015c · outbound

This paper cites Pre-trained multi- modal large language model enhances dermatological diagnosis using skingpt-4.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Pre-trained multi- modal large language model enhances dermatological diagnosis using skingpt-4

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:29:29.261895Z

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.

source=pdf_text observed=2026-08-10T14:29:28.341757Z digest=sha256:fc2454e637a9906fab7bd358050b6a940b288a9b5a79ffb5f6819d2ff6c137f5

Pith citing papers

Observation d6d1e12e-8049-433f-a92f-0c05434cee76 · inbound

Extracting Visual Facts from Intermediate Layers for Mitigating Hallucinations in Multimodal Large Language Models cites this paper.

Extracting Visual Facts from Intermediate Layers for Mitigating Hallucinations in Multimodal Large Language Models Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T15:32:34.540866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:32:34.540866Z digest=sha256:dbefaa44998d63f440679475dabcd68bec59e32d279e7591065e7005d9b79f43

Observation d790f951-692b-4272-a4bc-f4da2ba9d10c · inbound

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments cites this paper.

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-19T01:02:54.889649Z

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.

source=pdf_text observed=2026-05-19T01:02:07.088724Z digest=sha256:e85a73d6d70e819e55ec9ebcbb10cd0553c0428f206b50bea566f7f3787a1962

Observation 2ae76e75-cffa-4cab-9f63-b636d15419fb · inbound

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement cites this paper.

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:51:10.002380Z

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.

source=pdf_text observed=2026-05-08T16:59:10.015928Z digest=sha256:a53fb5b7bcb55d922147c08da203aedde7018f628a3d1284cfe89a34b78fd09d

Observation 6c4e377e-89a3-49e7-8b11-0c6de3a6bc17 · inbound

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement cites this paper.

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:06:35.968383Z

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.

source=pdf_text observed=2026-05-12T03:43:44.821785Z digest=sha256:b7034dc5d5fe90423f99285b2bfb570fb7aa4e99758f2558e2693cacc9dea960

Observation 165690ed-78af-4d1a-add3-62a85499a74b · inbound

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling cites this paper.

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:08:11.978912Z

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.

source=pdf_text observed=2026-05-20T10:08:07.648295Z digest=sha256:994a35a27b938fbb76edcb1d3e271976bc9c2d06af7bdc1060e0c56403e0d8ac

Observation a1e2cfed-d8cc-4f77-8f07-435cc7556f5a · inbound

Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning cites this paper.

Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:34:01.808738Z

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.

source=pdf_text observed=2026-06-29T22:28:35.155099Z digest=sha256:937256bf91913dc41d19f9802bccab2b59f3f8f19e944625afa85b5262cf99c1