Pith. sign in

Paper Citation Record · LEDGER

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators

As of 14 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.19421.

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

pith.paper-citation-record.v1
2607.19421 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T18:01:58.408621Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 840b03aa-13ca-47ad-ab5f-40e1096afd09 · outbound

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

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators An image is worth 16x16 words: Transformers for image recognition at scale

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:55.951520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:55.951520Z digest=sha256:d2cd093cec715062eb22c8e5dc6f06228c8d97c7941bb53a4dc56c9349f49ce9

Observation 4c9d69ca-bdd7-486a-9683-df9a19047864 · outbound

This paper cites CrossLight: A cross-layer optimized silicon photonic neural network accelerator.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators CrossLight: A cross-layer optimized silicon photonic neural network accelerator

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.026577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.026577Z digest=sha256:328516628aace510d812023c82a06473c3dc77b8de4af216e5ed70762bf81008

Observation e650b96c-0af9-4b80-af1a-6a1288624d15 · outbound

This paper cites Lightator: An optical near-sensor accelerator with compressive acquisition enabling versa- tile image processing.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Lightator: An optical near-sensor accelerator with compressive acquisition enabling versa- tile image processing

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.128015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.128015Z digest=sha256:e4a7e3fcc29f22527d026c875c4fa571bbffa6d1b96ae698bd58b871f06975a6

Observation 30071e29-cbad-4205-9bf6-1d7a56494e24 · outbound

This paper cites Opto-ViT: Architecting a near-sensor region of interest-aware vision transformer accelerator with silicon photonics.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Opto-ViT: Architecting a near-sensor region of interest-aware vision transformer accelerator with silicon photonics

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.244114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.244114Z digest=sha256:20ea651a6ed918982caef2652808f8a0644dfeb3ea10fdfc2bd9303d5701c14e

Observation 2e4925ca-ab29-4829-9550-e4ade3ebbf26 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.362203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.362203Z digest=sha256:04ed9e8d18cd3972aca521f69d42faccc25d3b57855afe73840890fddcf4d86f

Observation 7cc8263d-32bf-4d00-8147-b0e49406bd3c · outbound

This paper cites Belongie, Bharath Hariharan, and Ser-Nam Lim.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Belongie, Bharath Hariharan, and Ser-Nam Lim

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.474591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.474591Z digest=sha256:5aee138a10bb8a663485c08256bad0e2a15d89c6dcbe9a03da79affaf5579eb2

Observation 4ba09789-addf-4a46-9bd2-597c9132f4a1 · outbound

This paper cites Parameter- efficient transfer learning for NLP.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Parameter- efficient transfer learning for NLP

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.577069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.577069Z digest=sha256:2d0207d2c0cb96f80d325263b14e1520a5e4837e1043da8dc565ee5fd2d30881

Observation 0d9a0a29-0ed0-4bd0-b1cc-9b649e6cfa7c · outbound

This paper cites FacT: Factor-tuning for lightweight adaptation on vision transformer.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators FacT: Factor-tuning for lightweight adaptation on vision transformer

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.655353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.655353Z digest=sha256:c0304f4139c75294d9ad18602b8d2763ab7af42c882e1bd253cd2eb97b132812

Observation 1b9c765b-c4e9-410d-869c-845ebe52c234 · outbound

This paper cites AdaptFormer: Adapting vision transformers for scalable visual recognition.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators AdaptFormer: Adapting vision transformers for scalable visual recognition

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.765404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.765404Z digest=sha256:9b118b277dcdf65d368a551988522d29c3148e6f2b8519425da0cbb8bb595cb9

Observation bb921478-086f-448f-8151-44ef57769b2a · outbound

This paper cites LightBulb: A photonic-nonvolatile-memory-based accelerator for binarized convolutional neural networks.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators LightBulb: A photonic-nonvolatile-memory-based accelerator for binarized convolutional neural networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:56.971614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:56.971614Z digest=sha256:7608e5c04aea46d9ca7c2e2f73fb9ccefe38affe59c163fc37dfd4f7795730af

Observation ee97e804-4edf-4a56-ac42-d458198664b3 · outbound

This paper cites HolyLight: A nanophotonic accelerator for deep learning in data centers.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators HolyLight: A nanophotonic accelerator for deep learning in data centers

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.061811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.061811Z digest=sha256:cf2dd55cc95224637f4ff3d8793f89ddb38fdcfa277215b98dda22488f20f250

Observation b9069f5f-bcb7-45c8-af98-3d7cbeccc9c2 · outbound

This paper cites Sunny, Asif Mirza, Mahdi Nikdast, and Sudeep Pasricha.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Sunny, Asif Mirza, Mahdi Nikdast, and Sudeep Pasricha

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.146415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.146415Z digest=sha256:2dfbcdd26851e7b48edce2a90ca044d28475c25f9b686d9cef627ae244fca004

Observation 67046053-ba09-47c6-85c9-1d2c8d026484 · outbound

This paper cites TRON: Transformer neural network acceleration with non-coherent silicon photonics.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators TRON: Transformer neural network acceleration with non-coherent silicon photonics

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.270116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.270116Z digest=sha256:aa2da77df6a89a6cc430dd4746be9ecc791acc0bbdac44c02dad830d615544f6

Observation 75070bac-03ae-48b2-b039-28569a2f86cb · outbound

This paper cites AdapterFusion: Non-destructive task composition for transfer learning.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators AdapterFusion: Non-destructive task composition for transfer learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.365983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.365983Z digest=sha256:c02fe0f51ec5d61d0a32d5ead0e69c59607cdd23160bbea816ad10d22daca4c3

Observation cd00f1dd-9aa0-483f-97c3-4038caf641d8 · outbound

This paper cites Fast and robust analog in-memory deep neural network training.Nature Communi- cations, 15(1):7133, 2024.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Fast and robust analog in-memory deep neural network training.Nature Communi- cations, 15(1):7133, 2024

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.457930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.457930Z digest=sha256:6cae314d9bf75d1cc520b3d00cab3417c4f2f4d1d1528a2cc0cb76a0ff1fb401

Observation 4c5c1055-dc8b-4711-a567-ab22493b1f73 · outbound

This paper cites ReTransformer: ReRAM- based processing-in-memory architecture for transformer acceleration.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators ReTransformer: ReRAM- based processing-in-memory architecture for transformer acceleration

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.574863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.574863Z digest=sha256:cc3d1e9466d19c38d0d60e7c54a68e889be4cf604b90a2e747ae6593ab11d3a7

Observation 99dd0c71-a713-46fa-bed4-78c1dce8efbd · outbound

This paper cites Light-Bound Transformers: Hardware-Anchored Robustness for Silicon-Photonic Computer Vision Systems.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Light-Bound Transformers: Hardware-Anchored Robustness for Silicon-Photonic Computer Vision Systems

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.675873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.675873Z digest=sha256:e7ff0ca233830baf6b6ae56d7a9f25a779e5f3abeeffbc6a0b6be3fbbfcdfa7d

Observation c0c19a0e-6107-412a-8f6e-fb23f488d637 · outbound

This paper cites Neural Prompt Search.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Neural Prompt Search

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.730943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.730943Z digest=sha256:161cc8d52a796ab19783f597300924362f594ec54260d2e41a3f37d3e59e8f66

Observation 0712ba36-c289-4b44-93ff-a549e21f5632 · outbound

This paper cites Freepdk45: An open-source predictive process design kit.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Freepdk45: An open-source predictive process design kit

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.851019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.851019Z digest=sha256:799f05c42e58f76fe4a9abc0ef194a95477251426898641956c74165da537fb6

Observation 353bd5d0-c30a-4dba-bc42-b38945e07ab8 · outbound

This paper cites Synopsys design compiler, product version 14.9.2014, 2014.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Synopsys design compiler, product version 14.9.2014, 2014

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:57.914701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:57.914701Z digest=sha256:3799663c4b5f283bd29ea8597f3761eeb0d43b56fc98b54960b41a68c157dbea

Observation fffc8b17-678d-41ca-a6aa-7e54bb1bf7fe · outbound

This paper cites A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:58.032541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:58.032541Z digest=sha256:634e278a1ac2a8dae1e4c34925cd7e11c14faa32433e2864c06c820fc24043d6

Observation f3526b13-01ca-4439-ab49-d1360b466300 · outbound

This paper cites Food-101 – mining discriminative components with random forests.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Food-101 – mining discriminative components with random forests

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:58.110826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:58.110826Z digest=sha256:ec634d52fcd30302c538f50fe0e329760b19d24562f6f7263ebd9d79ceca9480

Observation 65bdff12-f27e-4731-bfde-88cc2541450d · outbound

This paper cites 3D object representa- tions for fine-grained categorization.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators 3D object representa- tions for fine-grained categorization

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:58.207941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:58.207941Z digest=sha256:89902972f2bf9d662e1541224ba03145d3eeca39953542a88a1d2376440e472a

Observation 4241f0b7-6159-48c8-b9b5-337b90dc525c · outbound

This paper cites Automated flower classification over a large number of classes.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Automated flower classification over a large number of classes

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:58.267579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:58.267579Z digest=sha256:4039a53a3fb1be8ab511f949c18e5e1dad2f23cd5d5f3efb3b4a25b80770f5b6

Observation 0c65579c-752a-4b6a-b799-df1a4ac15826 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Fine-Grained Visual Classification of Aircraft

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:58.349988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:58.349988Z digest=sha256:2c60267c99fa915b029f45c84bcd3def32c9cad5fc651731d35c2917d5e6bd07

Observation 6c4df452-efc5-45b7-8bad-acc9712e9414 · outbound

This paper cites Parkhi, Andrea Vedaldi, Andrew Zisserman, and C.

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators Parkhi, Andrea Vedaldi, Andrew Zisserman, and C

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-01T18:01:58.408621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:01:58.408621Z digest=sha256:9ca393181853f890e5bbf89788c14bd77bc44d0c672351ab5ab3b9cddd688d7d

Pith citing papers

No inbound Pith citation observations are available.