Paper Citation Record · LEDGER

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model

As of 17 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 4 inbound Pith citation observations for arXiv:2501.12206.

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

pith.paper-citation-record.v1
2501.12206 v3

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:28:42.275751Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:44:54.981867Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:34:01.801514Z

Reference resolution

48 of 48 outbound references displayed

verified exact0
verified fuzzy26
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cebe75e3-5d93-4e2c-a9d4-cb9422b86fc3 · outbound

This paper cites Agla: Mitigating object hallucinations in large vision- language models with assembly of global and local attention,.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Agla: Mitigating object hallucinations in large vision- language models with assembly of global and local attention,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:44.013954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b03c8fa3-eaaa-4928-b31e-5721df12e862 · outbound

This paper cites Nikolopou- los, Hans Vandierendonck, Deepu John, and Bo Ji.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Nikolopou- los, Hans Vandierendonck, Deepu John, and Bo Ji

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.994796Z

Source-reported events for the cited work

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Observation 6036a9a4-08fc-439e-9e78-a8ccd741d871 · outbound

This paper cites Qwen Technical Report.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Qwen Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:41.693418Z

Source-reported events for the cited work

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Observation b9e054b2-8ecd-4667-8a6d-94ff044c3fcd · outbound

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

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:41.699528Z

Source-reported events for the cited work

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Observation ecc5df0d-b8da-4357-a1fd-8e86a9138651 · outbound

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

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, march

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.972223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a8b4e75c-16e2-4b74-ae90-6c3fcb0dd92a · outbound

This paper cites Instructblip: Towards general- purpose vision-language models with instruction tuning,.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Instructblip: Towards general- purpose vision-language models with instruction tuning,

Reference 6

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Source-reported events for the cited work

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Observation 9bbefe5c-b46f-4afb-a089-f07b530e149c · outbound

This paper cites Vision transformers need registers, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Vision transformers need registers, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.917685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c6275b5e-986c-42db-8241-63e895ad78c3 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.721770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c826dfec-a4a3-4aef-b2cb-89d898e6a202 · outbound

This paper cites Multi-modal hal- lucination control by visual information grounding, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Multi-modal hal- lucination control by visual information grounding, 2024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.669896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ecf3c9d3-fd65-4e4c-aa05-f955cc1b0e7a · outbound

This paper cites LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:41.984011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87fffa6a-56c4-4da3-a662-aa0ae5ed28f8 · outbound

This paper cites Cogagent: A visual lan- guage model for gui agents.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Cogagent: A visual lan- guage model for gui agents

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.652632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3b17fd8d-0cfa-4ed7-abac-91afe3a32851 · outbound

This paper cites A survey on evaluation of multimodal large language models, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model A survey on evaluation of multimodal large language models, 2024

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:41.995721Z

Source-reported events for the cited work

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Observation c881b9e8-5aee-47a1-bd0e-54d4f3633b19 · outbound

This paper cites Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.001774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8fc29ef-cc3d-4e1f-bcf3-966aa8fdf8c7 · outbound

This paper cites Opera: Alleviating hallucination in multi- modal large language models via over-trust penalty and retrospection-allocation, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Opera: Alleviating hallucination in multi- modal large language models via over-trust penalty and retrospection-allocation, 2024

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.614059Z

Source-reported events for the cited work

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Observation df7ad794-dd1c-45bb-a9a1-05a52ef16438 · outbound

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

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.596824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 17e08fe4-9d2d-49ab-b61e-da5919140776 · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.019215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ded805de-481a-4317-a48b-b0be529cc5be · outbound

This paper cites Code: Contrasting self-generated description to combat hal- lucination in large multi-modal models, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Code: Contrasting self-generated description to combat hal- lucination in large multi-modal models, 2024

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.567529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 16919685-580a-4978-b028-0a81cdea7ffd · outbound

This paper cites Building and better understanding vision- language models: insights and future directions, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Building and better understanding vision- language models: insights and future directions, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.452924Z

Source-reported events for the cited work

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Observation b824524f-581f-43b2-a4ae-95953f9b0cd2 · outbound

This paper cites Reference-free hallucination de- tection for large vision-language models, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Reference-free hallucination de- tection for large vision-language models, 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.320198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81768820-ce7f-4443-94cc-71e13ddb8891 · outbound

This paper cites Vlm-eval: A general evaluation on video large language models, 2023.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Vlm-eval: A general evaluation on video large language models, 2023

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.176831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 269d5e76-cc37-408a-b3e5-0e827378708e · outbound

This paper cites Evaluating object hallucination in large vision-language models, 2023.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Evaluating object hallucination in large vision-language models, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.161168Z

Source-reported events for the cited work

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Observation 6c514fb9-1a90-4ae0-bd2f-629d00a3821a · outbound

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

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Evaluating Object Hallucination in Large Vision-Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.052071Z

Source-reported events for the cited work

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Observation a99d5419-917f-41d6-b745-d4b5133f2125 · outbound

This paper cites Gpt- 4 enhanced multimodal grounding for autonomous driving: Leveraging cross-modal attention with large language mod- els.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Gpt- 4 enhanced multimodal grounding for autonomous driving: Leveraging cross-modal attention with large language mod- els

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.144719Z

Source-reported events for the cited work

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Observation 3a5c302d-b6e8-4d6f-a00c-7a4e0e22ad90 · outbound

This paper cites Microsoft coco: Common objects in context.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Microsoft coco: Common objects in context

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.063233Z

Source-reported events for the cited work

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Observation 62026cff-aadf-4dc3-8cee-a70033b396ff · outbound

This paper cites Visual instruction tuning.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Visual instruction tuning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.117189Z

Source-reported events for the cited work

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Observation 057b4ae5-1c0b-4f76-b895-e19a0cc7fbb5 · outbound

This paper cites Visual instruction tuning.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Visual instruction tuning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.072757Z

Source-reported events for the cited work

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Observation 45101b8e-64f7-4863-8dc9-6ff86868437d · outbound

This paper cites A survey on hallucination in large vision-language models,.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model A survey on hallucination in large vision-language models,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.078333Z

Source-reported events for the cited work

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Observation 3c1a433d-e008-4f0b-b33a-998f8934cb7d · outbound

This paper cites Paying more atten- tion to image: A training-free method for alleviating halluci- nation in lvlms, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Paying more atten- tion to image: A training-free method for alleviating halluci- nation in lvlms, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.078577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3df155bd-5f2a-4dda-9762-67548722f339 · outbound

This paper cites Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models

Reference 29

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Source-reported events for the cited work

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Observation 7fe2a868-7d6f-4edc-8553-eaf011d25820 · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.094407Z

Source-reported events for the cited work

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Observation 784ff819-22cd-4800-ae7c-13a03565c709 · outbound

This paper cites Vista-llama: Reducing hallucination in video language models via equal distance to visual tokens.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Vista-llama: Reducing hallucination in video language models via equal distance to visual tokens

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.062004Z

Source-reported events for the cited work

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Observation 0fb71868-bf1b-48c6-afbe-7e6992b059ed · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Learning transferable visual models from natural language supervi- sion

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.133517Z

Source-reported events for the cited work

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Observation 2204cb83-7859-4382-bb79-c3226c277391 · outbound

This paper cites Object Hallucination in Image Captioning.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Object Hallucination in Image Captioning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.155224Z

Source-reported events for the cited work

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Observation 181d5f5f-f57e-47c4-a8ee-4ce6e1ce459d · outbound

This paper cites Arık, and Tomas Pfister.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Arık, and Tomas Pfister

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.029973Z

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Observation 1bf4b930-e462-4796-bb99-0cc3d3b5724b · outbound

This paper cites Visual text meets low-level vision: A comprehen- sive survey on visual text processing, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Visual text meets low-level vision: A comprehen- sive survey on visual text processing, 2024

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.010949Z

Source-reported events for the cited work

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Observation 5b3667b1-1698-4f56-aabb-15a579959005 · outbound

This paper cites Mitigating entity-level hallu- cination in large language models, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Mitigating entity-level hallu- cination in large language models, 2024

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:42.992611Z

Source-reported events for the cited work

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Observation b7b701dd-9b22-4faa-a669-2733cd166fbc · outbound

This paper cites Evaluation and Analysis of Hallucination in Large Vision-Language Models.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Evaluation and Analysis of Hallucination in Large Vision-Language Models

Reference 37

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Observation 13b72026-dccb-4dec-ab73-2229e4ff33ff · outbound

This paper cites Visionllm: Large language model is also an open-ended decoder for vision-centric tasks, 2023.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Visionllm: Large language model is also an open-ended decoder for vision-centric tasks, 2023

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:42.972940Z

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Observation bfbb2228-5f6f-48df-968f-3b24e1cefcf1 · outbound

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PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 39

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Observation c8cf76d3-9626-476c-805f-9332bd5a1df1 · outbound

This paper cites LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models

Reference 40

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PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model A Survey on Multimodal Large Language Models

Reference 41

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PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data, 2024

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:42.765073Z

Source-reported events for the cited work

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Observation ba2d2d30-3afc-40e3-9c57-92dae7f0463d · outbound

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PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Sigmoid loss for language image pre-training

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:42.677767Z

Source-reported events for the cited work

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Observation 6d6e63ca-ed06-4655-a3c2-e71fcbd7a45a · outbound

This paper cites Vision-language models for vision tasks: A survey.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Vision-language models for vision tasks: A survey

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.260931Z

Source-reported events for the cited work

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Observation 868ac95e-4c65-42cb-8a23-46aacd7d3f1e · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model OPT: Open Pre-trained Transformer Language Models

Reference 45

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Source-reported events for the cited work

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Observation 7a7b035a-aa99-4f35-86c9-ec5c70dc255d · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T17:28:42.270697Z

Source-reported events for the cited work

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Observation cbf2c9d0-5529-413c-8428-3b77b3aca602 · outbound

This paper cites Ibd: Alleviating hallucinations in large vision- language models via image-biased decoding, 2024.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model Ibd: Alleviating hallucinations in large vision- language models via image-biased decoding, 2024

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:42.572620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a24d36d2-2478-4698-b7c6-c8fbed12cf15 · outbound

This paper cites org/blog/2023-03-30-vicuna, 3(5),.

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model org/blog/2023-03-30-vicuna, 3(5),

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:28:43.951583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation eff686ce-38f4-432d-871b-66cc90968a7d · inbound

CAI: Caption-Sensitive Attention Intervention for Mitigating Object Hallucination in Large Vision-Language Models cites this paper.

CAI: Caption-Sensitive Attention Intervention for Mitigating Object Hallucination in Large Vision-Language Models PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T21:44:54.981867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55ad7066-1187-4b0e-98f2-ea60b2651ddd · inbound

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings cites this paper.

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T23:35:18.882276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 992b2855-7ec2-4c27-94d7-51fccf0ab630 · inbound

CAST: Mitigating Object Hallucination in Large Vision-Language Models via Caption-Guided Visual Attention Steering cites this paper.

CAST: Mitigating Object Hallucination in Large Vision-Language Models via Caption-Guided Visual Attention Steering PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:50:40.327897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5a8682e6-8c52-484c-a40a-7d4c8aa504b5 · 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 PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:34:01.803714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.