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Paper Citation Record · LEDGER

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach

As of 17 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2508.21206.

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

pith.paper-citation-record.v1
2508.21206 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:34:18.912344Z

measured 26 of 26 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 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 exact3
  • verified fuzzy1
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd0489b4-c21c-467e-b357-4094d062cef5 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 1

Resolution
verified exact
doi, observed 2026-08-05T14:34:19.512417Z

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.

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Observation f18b90d3-f2cc-43ea-9e70-43ffee26f921 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 2

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unresolved
no resolver link, observed 2026-08-05T14:34:17.193581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.193581Z digest=sha256:2775c7522d0e71d0b5285a1fd2ecf8342543d02c1ac8a62fda026dc661cc2bf8

Observation c21c6555-96ec-437a-a77c-2284cef50ca4 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.231984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.231984Z digest=sha256:e874bc40b448997e62237649ec92b3412b038a7e93539b6eeda465a79f51bdcf

Observation 0ecb1c54-1984-4efe-9a9a-6410e4e17a43 · outbound

This paper cites WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.303431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.303431Z digest=sha256:f2927b3f31501f8f04e93aee963c26d617b761f3cfc7d162fe43bd9e0a520bbb

Observation f4be825a-1db2-4c08-97dd-0c0258270203 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.370790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.370790Z digest=sha256:f043ea3cef06c14df71a71b278792243d587091396a9a069aeb89e5ba7cb61c9

Observation 36fad96b-33e5-4119-a01c-61db347b0dcb · outbound

This paper cites o zde G \.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach o zde G \

Reference 6

Resolution
verified exact
doi, observed 2026-08-05T14:34:19.347553Z

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.

source=arxiv_source observed=2026-08-05T14:34:17.420656Z digest=sha256:01445d25e3f0856d02d7df715326387209caf956133b14fa543ddde3ba26493a

Observation 4bb36a9f-624d-498f-9c40-a02617a47362 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.527463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.527463Z digest=sha256:224408ff6273e63b7b54f85abd1f5d0054e1762d53fe3f121eeebfed7ad3f3e8

Observation f9073330-54fb-41c9-b838-e9fa5d460af3 · outbound

This paper cites Challenges and Applications of Large Language Models.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Challenges and Applications of Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.588895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.588895Z digest=sha256:cd49f473965e6357fd469dffaf345c3aecedb0ee2ea0f2d11ddb6f7194402ed0

Observation 9f265c88-9c28-4be4-be59-a2462d3ccc64 · outbound

This paper cites Girshick.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Girshick

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.666515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.666515Z digest=sha256:cfdcfa4c660761f5d0a79669edf2c2e3a686d3fa6b844892fd698dffb0bcc3f8

Observation 2ae960b8-40c5-4a4b-a00e-84928b4b160c · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.727931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.727931Z digest=sha256:3a6676f037df189dcb2dcd560f7bfb05b3f215edd42fc40b3e1b849581d7d9e1

Observation ad260618-c94e-43fa-a112-ce6f551e81b3 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-05T14:34:20.256668Z

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.

source=arxiv_source observed=2026-08-05T14:34:17.817676Z digest=sha256:b25f69fda88c63279e5b73f8353f380e87864d927ee8452d0c32d7d230cdfb49

Observation b6748289-39c1-4ef3-9d44-2ea6c855e65d · outbound

This paper cites Overcoming Vocabulary Constraints with Pixel-level Fallback.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Overcoming Vocabulary Constraints with Pixel-level Fallback

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:17.902741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:17.902741Z digest=sha256:32ea79d913757877f2bcc72b7a611169d66ec6fdf0eebe2a7bbaf65a2105dd5b

Observation 848f0ba0-a54e-46d5-a8fd-6d301580bcf2 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-05T14:34:20.126639Z

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.

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Observation 76419c1a-c1c6-402d-8428-d4caa0499a02 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.041165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.041165Z digest=sha256:311dfe5479f3e8004dea1db5f29121caaac39aace36652002cf80bb20691056b

Observation 3d08f3d8-2f59-43c9-8630-4f560e9633c5 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.092070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.092070Z digest=sha256:dcfa107abe53fe937761d3dd6034767927d024b6ddee598ab97b6bc162c16320

Observation fcddb53e-6a81-4930-853b-0503501af33b · outbound

This paper cites Lotz, Emanuele Bugliarello, Elizabeth Salesky, Miryam de Lhoneux, and Desmond Elliott.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Lotz, Emanuele Bugliarello, Elizabeth Salesky, Miryam de Lhoneux, and Desmond Elliott

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:34:19.980853Z

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.

source=arxiv_source observed=2026-08-05T14:34:18.136761Z digest=sha256:9bdb79cdb8d49378e06aa2e67dd11de0df1f4b25e4ec60a2130aed76687f6588

Observation 4c8670de-304d-4334-b0f0-dcb0bfa685be · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.246604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.246604Z digest=sha256:5d09d1147d047b88dcb6162421bdb21d4f81d8b2d4bb1261743218386e434779

Observation fe403c07-1347-41c2-9ace-16ffb516a464 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.316573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.316573Z digest=sha256:ec13e2012f0aedf4d77e992b77cf501442978c1ddb40ba25b17e858cf7792bac

Observation c758b651-d7de-4e11-b2cd-3899ee792297 · outbound

This paper cites Manning, Andrew Ng, and Christopher Potts.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Manning, Andrew Ng, and Christopher Potts

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.431615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.431615Z digest=sha256:b3279adc1672cff8a050989d5b711af1fed44d5c43ca5f1bb09794997ca3ada7

Observation 36e3404e-bc7b-43b7-bd43-7421df25789f · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.479295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.479295Z digest=sha256:a37dc014bfceef8bace874a332d0f14fb4e8877a55e7a8fba2a0ba48c173bb55

Observation fbdf34a4-a5c3-40bb-a0c2-0a90d8a68820 · outbound

This paper cites an unresolved cited work.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Unresolved cited work

Reference 21

Resolution
verified exact
doi, observed 2026-08-05T14:34:19.142895Z

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.

source=arxiv_source observed=2026-08-05T14:34:18.578099Z digest=sha256:88aa21df8c41d86415bb92b29f5604ba31bbd507f6853c0c308b722a886979ae

Observation f6b9d174-4cbd-43bc-8bf1-0005c3f98dd0 · outbound

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

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach LLaMA: Open and Efficient Foundation Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.646589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.646589Z digest=sha256:067d5e11e69edc63cb496afc44a564b9de4b11d00df8901581d612ddf66d5170

Observation 0a170fde-e0cc-458b-8e07-360164ad479f · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.697951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.697951Z digest=sha256:16d338159c338fd8cb34cebe930af0d8e7eb3e36db6f5530990dc613cdfe91e5

Observation bba2c418-2bd6-4eef-be00-47333a709afe · outbound

This paper cites Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.777526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.777526Z digest=sha256:d4954d850287bbf0e2a909643529d018515200eb1466f22f0f5bc9b6422ca8f3

Observation bb45166e-93d2-426e-bed4-f3b1b0cf859c · outbound

This paper cites online" 'onlinestring :=.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach online" 'onlinestring :=

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.831980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6706ecb2-916e-49cb-98f1-3913f727fa53 · outbound

This paper cites write newline.

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach write newline

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T14:34:18.912344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:34:18.912344Z digest=sha256:ff4fd8ba2161d0224584b06f42e2fe4154bc2aeaba71fc2b323b64f9b84836c1

Pith citing papers

No inbound Pith citation observations are available.