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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 11 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 2026-08-10T06:31:04.303077+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:c23b79ec3a55e0b63b6b4bbee7c28fe9eb034f08b843c96f8926e523bb7275cd

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:be65d7fa150333c6784fa0a4a134f7cfda1b50420718c38c5fab28864ca15197

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=sha256:2f08cd718e92b7759cf5e41f1273301669e78a7121dc737a49f8b7d101240e9e

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:f3a2526569496fe6e3446914cdfcb9250052e3fe1e05118741fb369715c9556a

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:d6003885ca6a65ea50cda4e5514d191e2d9ba79ab16c346ecb981ada2faa0729

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:e8bb882b5b419d51d66d6b4150099793cfb02532f55b6c3dbb1cd6b571730162

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:ad061e62f99609e1e51084699951d05f7e0aa16c2ac039d61d80c6ea0f0d5b7a

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=sha256:45a9ffb0d70bb1c282390f5f4ba1c77cdb6413613da28895814170cf395697ac

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:a53e07b10c4d9fd5b56ac83bdc2a4475bf483f4a740ced2b38398adc7d14e1d7

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:ffa525c75dbdcb8de35f11eb2b3c1d29772af7cf02eb5b2ad7c48eb6683901c1

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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local_arxiv, observed 2026-08-10T14:29:28.976575Z

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source=pdf_text observed=2026-08-10T14:29:27.888840Z digest=sha256:1a297ef3f7ac770f98721121b3b30a9bf4558cd1def4b8d0fed768650ec380c6

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=sha256:1b62cb9ee86fd921067fc94d132387a97512cb38fbaee1ab43ecb10e8a8eac69

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:d4f265e545c101e19513d27ac7f5993aa4e07a886899d43632763f9d09278f0f

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:ee68c7558f06cbfc23b8cf5898d84dff0dbdd51efb8c0cfe42bf5bc4dff42725

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:ce5c39f9c0a49ab72200b4d3da7b05163a4e33c8ff8de846f8e8ba068cb998db

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=sha256:68748c0fb5c29f7285b9225733db0063a0709b119325486dacbd7a371b92031d

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:e35eb94468d2703faf14b47925415718eab1e8853d66f4222de3ae614e5573a1

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:b36936d026d1d8d23b79d6c0647b31abf3b1e1bbf3d5ac57c163d53d076a0ce9

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=sha256:7e0a9b263f5a85669b865e766872e28d0f4d258a42d1f19180630a63dc09a8e6

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=sha256:743a2249294fbccd0f4162d36e03c757b6a5ee657f94c2696dc353a403daee8a

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:d3251cf50656fa158c65687316eda4331abf68eaa59f5df3c454a22e2e492c32

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:ed75d0a8a36dde30a843fa8af77165e7a4f469932d87ccee1a0ff009d4d388cf

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:bfacf9819b9e7e0971c3c3ef551c57de8934df9d556c7fe567f78fd974d7f048

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=sha256:4efab3fd719d7ba3bf2f6780c0f21599f6c56387922dc35d5c23c8cce0bae840

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:ff5fdd6c5ce44a98f6f316205c803b4690bb62647821cf6c29e0c6cbd65aff44

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:c393a925c64533fdb247b9e8d925a3e905a9e2ad8303dc6f3b9be2000fd8c79a

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=sha256:094fd286083506a102bb6d03bb9e6dd6102fb4bd5f3e547796ab3873cc6744d9

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:f751d30b8edefb913e28ab80d1960adf9512a644c7d980e2ea604920eecda933

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=sha256:6f409307b6db1857815b0a8e74bf51e3af9ede1b8ada09e257389fd1f9e684f9

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=sha256:68ebadf467e58626b4b3622c61c4ee25e24a40f3949730ca74c5bdfa8301a174

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=sha256:13ba4c38165fda63b4904de6a1aac503dc502ab067dcda0981041217cfb256ba

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:dd9f7502953b01d20c3148a607ba28e23d49fed6c0a1eb34fe60de05df09d42f

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=sha256:5c72b8ef300d02824e09a6b2cc58472d4b4ca20b5acb03bd4d6cf6467ab5ba67

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=sha256:335d00f3df327d2e2254aa93170982523a857c8791c803471ed4998c8c1675a6

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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source=pdf_text observed=2026-08-10T14:29:27.982581Z digest=sha256:823299c93b3c1c2f59c3034147c740987a30eb221b0a291a4f6e9699f40d3cba

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=sha256:4ba56a2b972849bdc711970bea3597a4fba0883dbbb1f0ea7a7b3af569389dff

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:ac0efa6fdc2473fd893e2f32eeb54d13e617f3de755ae3dc20f630c065ea7e78

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:27.993212Z digest=sha256:45f5dd3fff8de27ab4d4bcf5f8120c370dd92f00254ddf0c8fcd7e11d49ef54b

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-reported events for the cited work

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source=pdf_text observed=2026-08-10T14:29:27.996615Z digest=sha256:86a73fa53f7fbe27679ea1b76533d546dbbc3ac161e843767834a1dee6b9d9b9

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=sha256:73714714c84b0dbe370da450f40437f7448f3a1f08ca6ca14fcff6b3d55fee25

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-reported events for the cited work

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source=pdf_text observed=2026-08-10T14:29:28.004970Z digest=sha256:d7b485a241793361c14388b91bd55aedd87d21b6a18494307e07829721a11ad3

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:c02ab91ed8567d7c43e3d3ec0a2ceef579f3df0775f5de6d1d1bfb47b89f567b

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=sha256:80ddfa9d82e7ecd0bfb99f4e363998c3dd614be633892c6329e32368d9ce6658

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

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.017232Z digest=sha256:bc41dea277fae03132227f930e01768a0a4fe2128ba606f118a0076874712575

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

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source=pdf_text observed=2026-08-10T14:29:28.021367Z digest=sha256:81b9f7afd2567e81e836692b281972237bdfdb9c69eae946ee5e48e708640b62

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:b9b8830b4156e499e6debf11cc0c719b20d24188f3dc540ed62e078cf2a7d313

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:ca60c0717322fe77a517fbda1e7bca4de859c344b80cff51a59652fd13aadd66

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

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.033866Z digest=sha256:176840f282ca5cd7b6e12da95344dd203a3c64a7dc935a6ae48e1ff3cb49083a

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=sha256:7fb67c1f5652884ab7e2af20f165a20a8d5ff2d795639de0abbb61ec4cf6a42c

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=sha256:8f342b0b825adb5aadd00f491103baa0ce0688d010185babbedd367e388024be

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.046459Z digest=sha256:6132ef4312ba1d189af1c8be12b2d6e72d94ebd24034c4cb82d0660c79d74034

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=sha256:2ba148d47fd325fea86aae06517541f966db1dd345e8c69f1ba404d1616ae1f9

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

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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=2026-08-10T14:29:28.053371Z digest=sha256:7917e1db0f16f9d9989c91fb1ea6f8ed3ce2bd69e9b1e5bbd8817f1f0f54a7dd

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.056851Z digest=sha256:8bb6b47a224e1e2faf82598131eb5722d3944fc83d24e49ffb5fb407958119b7

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

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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:d9d93f3bc2fad3778b5d967ee747655c8e02ad3ab942a171ad94afe46dee39f8

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:d3046748f5de98e02cb4b659449235a110742312bd01c073cd16164f147619dc

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.067564Z digest=sha256:f1bc53c459da84d564d4397e1a363e0300a6caca02bf856c0e9c47704a53390f

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:f7f4a9685c76fe279192786bea9ad41c080ba8026cfb4820b36947ab16468ac1

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.074482Z digest=sha256:126dd982344ff91df2de801c29d1121f956f0ac3f4c2dc52a3181c73f7502613

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

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T14:29:28.078245Z digest=sha256:c20030091a5256bb864774df3ea5cbba52e9d7111101102145ddc790751714d4

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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no resolver link, observed 2026-08-10T14:29:28.081919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.081919Z digest=sha256:fcf891318aa88f8daa35133a1f2d949f3dcb1f6525904664bd1523db13a523b6

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.086662Z digest=sha256:b8021c70b87080e07fe5dbb64fc089bf6fe8457ae4f1894e2d02650d27feeebb

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=sha256:482cf3ba8373290dac837dd85937af393d48b36a91f5dfc8c374c1b6aacd290a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.094725Z digest=sha256:8ffcc4e451e0e5e08b7591efcaf0e8784362cdb9c6c2943bf8286a6682af7b8a

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=sha256:00f31e73c918f1e870df6a7c643477ce1095a205f754752d597696422ab92a09

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

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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=sha256:60488632fa1d95c221f24feefd1bed72c468b2ab9370e761c9bc1baf13e2d069

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=sha256:22f38721fec6708500f4d181c2ea6a318b2c9564f3ab1fa528db3f8eb5532b3b

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

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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=sha256:537112061606371f0087caf7f1b7f2ab7e96d2573541476439b9e3d3db0c5472

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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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:b3dc71e710b2f054fadf1c39685c816b31efe36666ba1059701fcb17e8050762

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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no resolver link, observed 2026-08-10T14:29:28.118822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:29:28.118822Z digest=sha256:375b9605b631d0853496cc17936073a7f7e4fdd05136f9cd836ce26234295b8b

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

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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:ea946796405bece54cb177eb853be38738fb0b9a6fe666e63d3454616dbbb2d2

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.227605Z digest=sha256:99f7426480373a3e55d2352b00bac60a478ced8dd10a47c633dbdad9d5dc1b68

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.231619Z digest=sha256:c0cab63551abfc829fdda060e5b1c0852dbcb9e469caa8422f5b9f2b0ae448bb

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.235436Z digest=sha256:3df2116815f18ee95e6c67dd1ce991de65259d718ffb41e00b708e49c5943099

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=sha256:4fe7fbea8ec50bcde1189a512846c3a711fb638756cbee0384095da02373da76

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.244180Z digest=sha256:2da78388e67ca1e86ae5dcee0d0113e2bbc753f2cf53d8dcfd5849c33dd2e2bc

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:d908a4cf238b885c65e1c729baad0783df58e9904fc1e0dc9c57980369bc80e3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.252792Z digest=sha256:a97601b7425fbebe4695a1fe3ba188961b026f1da709422866e767a073225df1

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:b65c117cf75abcecceb400ee55ee39c832c863f02377e2397c71974cb21d3aaf

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:da5cba1f0cf45c825714855ffc55a7fc11e80b9e7f8e4bff1fe8eadd274bf79f

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=sha256:7ef6e1ef3b7f70fef207da27df1cab80fa34643823cdd7990d1ac30095d05c8a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.270174Z digest=sha256:c28b11c4128201acc49038af983c62d54b0832898a1c1f5c20dbb80b2afc030e

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=sha256:407502fc811fb227db820e2a48ff1be3d3dfd016d71c111e8fa97e4ed694f60a

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=sha256:575988cdcb433b65089f5cf7eb1b6d051facad8db2ac614b47dde0c95db22ad7

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.282505Z digest=sha256:2cad163bb7e3dcfc4b94589504715faf5d9bd145045d1bcbc004f88ec140501c

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=sha256:673349708227813461ee2d50af95945005b7f2419117a2d375153c88bf51064c

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.289301Z digest=sha256:ce22128502681e8cacd9ec75dbf90147a37df6321cc77ec83119a7994cb05388

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.292954Z digest=sha256:bd1958aca8cc4b6803771b88fd5f75704342e692b9f2d96d6dea8651c4c80697

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=sha256:950e4948c4ba472ba722b0607b3187abb841309510bc206ec3c672f0ad24524d

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:e17211ca8f01eeda3fc83c7e3cf150a060f2e7ae4be4db75740c0899efadafbe

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=sha256:3396be00a317e7a8ef35c62a989bafc058e959471e8da99cbbda0a5e0f22d8e3

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:e991cc140d2bdebac39279b3da5fc30c1175db1f548584dd8318a2ced9d71bf3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.310774Z digest=sha256:0ecce4b88d3821f9ddda47fca97098dd424ce25be2ca44869ae1fa2c5441878c

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.314920Z digest=sha256:0ba40ff3a08d72065de7f72792190ca2f29d872c7eca4a9c45177a7c53d665a8

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=sha256:518b4294e30b8cf46fef91a27e5ff7caaea7e64180dfd69a01c6953d360d87bc

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=sha256:6f90e6012050ceb5cd87b23747e9eda91bb766fcc695ed2e6d2d55d6a5c437e6

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=sha256:5d998647d1f0b8dfa0b6f176fc0e6a5fcea5487ef9fdfb8ae475d769c8c69b83

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.333110Z digest=sha256:b6efdb269282da73f4af20e8f4efea06bcb93eb41e73d5584de7620f67da6f90

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:ee683a0ed800b1a9dd6bb000003e064264c3b939e427f3ab83b7cd52c31da18a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:29:28.341757Z digest=sha256:adf1da2b5a3177179afc0fcd0696de259002cd51795abf4f4cf149ddb1c91884

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:a1619bb459b2d5c9a06167b53d4e81e0f7dc64078294590edd66f53a39945c6e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T01:02:07.088724Z digest=sha256:69e2de91a2ee4a4a2714b78cf1b4e4800f0b0d4d3635f595c60c3dd8e224c6e4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T16:59:10.015928Z digest=sha256:6cc9d0b7f9ea234aa1f8b854c28e8f8b3dad37e72828182199f833a6fd526187

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T03:43:44.821785Z digest=sha256:e115b23926907a7363190816f44def8ef4b06f9b970612a50407bf0934f28e75

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T10:08:07.648295Z digest=sha256:1c3b66093cd30925f5d9864e8e750cc4d51772086e293ce260569da130369a53

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T22:28:35.155099Z digest=sha256:bfb1ed2f764d97d9c23dfdd3a6301383982f848cfb5f52eb05d100eba011b1a9