Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-15T10:31:05.743053Z
Paper Citation Record · LEDGER
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models
As of 5 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2603.14882.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-08T14:44:32.242554Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-08T14:44:59.711636Z
Reference resolution
58 of 58 outbound references displayed
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- verified fuzzy44
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c32950ae-fa91-4131-b677-39c5bb600aff · outbound
This paper cites Data augmentation with noise and blur to enhance the performance of yolo7 ob- ject detection algorithm.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Data augmentation with noise and blur to enhance the performance of yolo7 ob- ject detection algorithm
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.694263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 648f6afc-2a75-4370-afd1-7968eab41f11 · outbound
This paper cites Object detection through search with a foveated visual system.PLoS com- putational biology, 13(10):e1005743.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Object detection through search with a foveated visual system.PLoS com- putational biology, 13(10):e1005743
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.731196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 98835792-3e93-48f2-889e-9ae8bbf9883e · outbound
This paper cites Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.734642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1dc8fe82-bf2c-473a-b38b-23e5989aab5d · outbound
This paper cites M ¨obius trans- formations revealed.Notices of the American Mathematical Society, 55(10):1226–1231.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models M ¨obius trans- formations revealed.Notices of the American Mathematical Society, 55(10):1226–1231
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.737928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f4ae511c-044a-404e-be6e-f055bedf5d7f · outbound
This paper cites Qwen2.5-VL Technical Report.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Qwen2.5-VL Technical Report
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.643584Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0ffaac07-16ee-4144-bc56-e27e8abf039d · outbound
This paper cites A summary-statistic representation in peripheral vision ex- plains visual crowding.Journal of vision, 9(12):13–13.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models A summary-statistic representation in peripheral vision ex- plains visual crowding.Journal of vision, 9(12):13–13
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.744724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1fb6bdf0-2b41-4cb2-a621-8e85202e8e35 · outbound
This paper cites Token Merging: Your ViT But Faster.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Token Merging: Your ViT But Faster
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.626152Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bf716ec9-bd95-46e7-8e6d-d5420f1b131b · outbound
This paper cites A general survey on attention mechanisms in deep learning.IEEE transactions on knowledge and data engineering, 35(4):3279–3298.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models A general survey on attention mechanisms in deep learning.IEEE transactions on knowledge and data engineering, 35(4):3279–3298
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.727690Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 27e13e15-c2fa-4f89-98ca-3ecb3745ca7b · outbound
This paper cites Convolutional neural networks develop ma- jor organizational principles of early visual cortex when en- hanced with retinal sampling.Scientific Reports, 14(1):8980.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Convolutional neural networks develop ma- jor organizational principles of early visual cortex when en- hanced with retinal sampling.Scientific Reports, 14(1):8980
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.741300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f9619b07-9ced-4ece-a261-43bc2bfd7a9f · outbound
This paper cites Instructblip: Towards general-purpose vision- language models with instruction tuning.Advances in neural information processing systems, 36:49250–49267.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Instructblip: Towards general-purpose vision- language models with instruction tuning.Advances in neural information processing systems, 36:49250–49267
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.672840Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e38eead7-ab86-4145-8ce8-c03db7705e70 · outbound
This paper cites The representation of the visual field on the cerebral cortex in monkeys.The Journal of physiology, 159(2):203.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models The representation of the visual field on the cerebral cortex in monkeys.The Journal of physiology, 159(2):203
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.674871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 836cf222-4930-47d3-b85f-1eeb032470f2 · outbound
This paper cites PhD thesis, Indian Institute of Technology Gandhinagar.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models PhD thesis, Indian Institute of Technology Gandhinagar
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.668644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9bd20661-793f-4b0d-989c-b17dfc2dee5d · outbound
This paper cites Modified harris hawk optimization algorithm for mul- tilevel image thresholding.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Modified harris hawk optimization algorithm for mul- tilevel image thresholding
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.747620Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 29105450-b676-4f6f-bd49-ff593144082d · outbound
This paper cites Scribgen: generating scribble art through meta- heuristics.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Scribgen: generating scribble art through meta- heuristics
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.666373Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f520765a-c60f-4bcf-9cfd-94736ae05b6e · outbound
This paper cites Emergent Properties of Foveated Perceptual Systems.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Emergent Properties of Foveated Perceptual Systems
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T10:35:27.617377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4d725512-2d7f-40e7-a844-d7a0cf57d081 · outbound
This paper cites Image quality assessment: Unifying structure and texture similarity.IEEE transactions on pattern analysis and ma- chine intelligence, 44(5):2567–2581.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Image quality assessment: Unifying structure and texture similarity.IEEE transactions on pattern analysis and ma- chine intelligence, 44(5):2567–2581
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.676882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5413c99f-e089-4148-b28e-19f867774949 · outbound
This paper cites Selective attention and the organization of vi- sual information.Journal of experimental psychology: Gen- eral, 113(4):501.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Selective attention and the organization of vi- sual information.Journal of experimental psychology: Gen- eral, 113(4):501
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.681103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5b736cc7-cc00-46f2-8146-f9de1e5efb70 · outbound
This paper cites Metamers of the ventral stream.Nature neuroscience, 14(9):1195–1201.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Metamers of the ventral stream.Nature neuroscience, 14(9):1195–1201
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.661486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c080502c-a7b0-4022-8eb0-79be1878c4b9 · outbound
This paper cites The free-energy principle: a unified brain the- ory?Nature reviews neuroscience, 11(2):127–138.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models The free-energy principle: a unified brain the- ory?Nature reviews neuroscience, 11(2):127–138
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.659117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ed7dd5ed-17e5-4800-a57c-90329ed1a442 · outbound
This paper cites FeatUp: A Model-Agnostic Framework for Features at Any Resolution.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models FeatUp: A Model-Agnostic Framework for Features at Any Resolution
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T10:35:27.608930Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 749041e1-ea54-4138-ba47-b955f65917e9 · outbound
This paper cites Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% perfor- mance.Visual Intelligence, 2(1):32.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% perfor- mance.Visual Intelligence, 2(1):32
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.762710Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 52dbf0eb-e94f-4dd0-bd72-c73bb32557bf · outbound
This paper cites Vari- able resolution improves visual question answering under a limited pixel budget.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Vari- able resolution improves visual question answering under a limited pixel budget
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.650273Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 990b23ff-9a13-40d3-bd34-b84cd34ab078 · outbound
This paper cites See- ing more with less: Human-like representations in vision models.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models See- ing more with less: Human-like representations in vision models
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.654698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 07a056aa-f506-4a0a-9fdc-862517fda58c · outbound
This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.713950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0466e7cf-1a37-4ca0-a7a6-6f679a77bec9 · outbound
This paper cites Lvis: A dataset for large vocabulary instance segmentation.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Lvis: A dataset for large vocabulary instance segmentation
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.646080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a5c62fa2-5f0a-4ae3-b774-f519f8053f40 · outbound
This paper cites A survey on vision transformer.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models A survey on vision transformer
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.643977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 82eb9942-4941-40b6-9882-1069f6e1fec9 · outbound
This paper cites Coco-periph: bridging the gap between human and machine perception in the periphery.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Coco-periph: bridging the gap between human and machine perception in the periphery
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.648058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 14c681cd-a103-4d04-a332-dac975a1aea9 · outbound
This paper cites Eye movements in natural behavior.Trends in cognitive sciences, 9(4):188–194.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Eye movements in natural behavior.Trends in cognitive sciences, 9(4):188–194
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.652701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 79981c56-12b0-4e38-9522-7e19687406cb · outbound
This paper cites Vi- sual prompt tuning.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Vi- sual prompt tuning
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.642204Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 929a1275-463c-42d0-9969-634425b509b0 · outbound
This paper cites Transformers in vision: A survey.ACM computing surveys (CSUR), 54(10s):1–41.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Transformers in vision: A survey.ACM computing surveys (CSUR), 54(10s):1–41
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.640412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d99382e1-c4b5-440e-8e40-64155488d60f · outbound
This paper cites Foveation in the Era of Deep Learning.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Foveation in the Era of Deep Learning
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T10:35:27.662926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d122a807-d21f-4a6a-bf84-9729c95af1f8 · outbound
This paper cites Oxford Uni- versity Press.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Oxford Uni- versity Press
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.670665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7ca8e6f7-f59b-4d3c-915e-01d66a709c4b · outbound
This paper cites SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.613119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 99321951-9ab3-4bcd-938e-2702b5060799 · outbound
This paper cites LLaVA-OneVision: Easy Visual Task Transfer.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models LLaVA-OneVision: Easy Visual Task Transfer
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.647915Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4cc72545-f925-4f5b-9606-645e278c9179 · outbound
This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.638366Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5063c342-afa5-446b-9dd7-63d8c0d2ed08 · outbound
This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models DeepSeek-VL: Towards Real-World Vision-Language Understanding
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.621585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 30e190e7-0b4c-42d4-871d-2a753af1ae27 · outbound
This paper cites Bio- logically inspired deep learning model for efficient foveal- peripheral vision.Frontiers in Computational Neuroscience, 15:746204.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Bio- logically inspired deep learning model for efficient foveal- peripheral vision.Frontiers in Computational Neuroscience, 15:746204
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.656836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7b332d7e-6c2c-4cf3-ab75-c75b15888d8c · outbound
This paper cites Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T10:35:27.635083Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a03270dc-468f-497d-95dc-4e01ce2af4d9 · outbound
This paper cites SmolVLM: Redefining small and efficient multimodal models.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models SmolVLM: Redefining small and efficient multimodal models
Reference 39
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.604164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3e1398e7-de42-4952-a76d-a94d53d1d51e · outbound
This paper cites Peripheral vision transformer.Advances in Neural Informa- tion Processing Systems, 35:32097–32111.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Peripheral vision transformer.Advances in Neural Informa- tion Processing Systems, 35:32097–32111
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.664296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff5e0932-77bb-4a0e-8bf0-8a36035ca3a8 · outbound
This paper cites The geometry of m ¨obius transformations.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models The geometry of m ¨obius transformations
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.756118Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5b08aeba-4620-41e4-a457-0e53e67a8a2f · outbound
This paper cites Learning to search for and detect objects in foveal images using deep learning.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Learning to search for and detect objects in foveal images using deep learning
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.753523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 52f67fdc-44b3-4d3c-bb24-706a049ab5cb · outbound
This paper cites Human peripheral blur is optimal for object recognition.Vision research, 200: 108083.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Human peripheral blur is optimal for object recognition.Vision research, 200: 108083
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.710594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a94cd915-bce3-4f97-b45c-40659c023607 · outbound
This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.Advances in neural information processing systems, 34:13937–13949.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Dynamicvit: Efficient vision transformers with dynamic token sparsification.Advances in neural information processing systems, 34:13937–13949
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.750484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c74410da-f002-4040-a94e-d837bdc379a8 · outbound
This paper cites Biologically inspired image sampling for electronic eye.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Biologically inspired image sampling for electronic eye
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.723571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation eaa78c98-22e2-47ad-9a4c-19cd4889d51e · outbound
This paper cites Robotic materials with bioinspired microstructures for high sensitivity and fast ac- tuation.Advanced Science, 13(15):e09739.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Robotic materials with bioinspired microstructures for high sensitivity and fast ac- tuation.Advanced Science, 13(15):e09739
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.717368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0218b050-ffb4-4e88-b015-d151fb2e6cf9 · outbound
This paper cites A-okvqa: A benchmark for visual question answering using world knowl- edge.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models A-okvqa: A benchmark for visual question answering using world knowl- edge
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.706937Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d7534fa2-d532-452e-90a6-86752c1da381 · outbound
This paper cites Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T10:35:27.658311Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f3921aa6-5a35-43f5-ab29-7575a8922137 · outbound
This paper cites Multivariate stochastic approximation using a simultaneous perturbation gradient approximation.IEEE transactions on automatic control, 37(3):332–341.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Multivariate stochastic approximation using a simultaneous perturbation gradient approximation.IEEE transactions on automatic control, 37(3):332–341
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:35:28.678951Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation af1f6430-0ad6-415a-82e8-961a673bfa71 · outbound
This paper cites Pe- ripheral vision and pattern recognition: A review.Journal of vision, 11(5):13–13.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Pe- ripheral vision and pattern recognition: A review.Journal of vision, 11(5):13–13
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.759239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 41923778-ee58-4d55-a2a5-73b6a9255a3f · outbound
This paper cites Central and peripheral vision for scene recognition: A neurocomputational model- ing exploration.Journal of vision, 17(4):9–9.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Central and peripheral vision for scene recognition: A neurocomputational model- ing exploration.Journal of vision, 17(4):9–9
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.697699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d9ea73e5-70da-456b-bb51-9e6a76e7037c · outbound
This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.630268Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 88e62a00-72a6-4ce4-89da-d692cf9e9866 · outbound
This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Ad- vances in neural information processing systems, 33:5776– 5788.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Ad- vances in neural information processing systems, 33:5776– 5788
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.720624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 573345b3-4ac8-47be-95dd-b4a9928691c7 · outbound
This paper cites Emulating human-like adaptive vision for efficient and flexible machine visual perception.Nature Machine In- telligence, pages 1–19.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Emulating human-like adaptive vision for efficient and flexible machine visual perception.Nature Machine In- telligence, pages 1–19
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.703051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 01a0c6a9-d91f-4ce8-960d-4fdeeda6d0d8 · outbound
This paper cites Controlmllm: Training-free visual prompt learning for multimodal large language models.Advances in Neural Information Processing Systems, 37:45206–45234.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Controlmllm: Training-free visual prompt learning for multimodal large language models.Advances in Neural Information Processing Systems, 37:45206–45234
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.702339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7cba3786-890d-45cd-ae9c-bc4f6b09d91e · outbound
This paper cites Qwen3 Technical Report.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Qwen3 Technical Report
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T10:35:27.639521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ba856bf3-d05e-4a5b-8f09-33256ac6d2d3 · outbound
This paper cites Ferret: Refer and Ground Anything Anywhere at Any Granularity.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Ferret: Refer and Ground Anything Anywhere at Any Granularity
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T11:29:05.422888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7e47f42b-2de2-4bdb-9986-2f98378a40c9 · outbound
This paper cites Vsi: A visual saliency-induced index for perceptual image quality assess- ment.IEEE Transactions on Image processing, 23(10): 4270–4281.
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models Vsi: A visual saliency-induced index for perceptual image quality assess- ment.IEEE Transactions on Image processing, 23(10): 4270–4281
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T10:39:57.685691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation bc148bdd-efd0-49e6-9c82-564e8ed3f352 · inbound
Toward Native Multimodal Modeling: A Roadmap cites this paper.
Toward Native Multimodal Modeling: A Roadmap LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models
Reference 261
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T23:04:01.864944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2ca7f7bd-a232-4a5d-b24c-c506c11375b3 · inbound
EAGOR: Embodied Reasoning in Omni-direction cites this paper.
EAGOR: Embodied Reasoning in Omni-direction LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-07-08T14:44:59.712899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.