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Paper Citation Record · LEDGER

MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.20771.

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

pith.paper-citation-record.v1
2410.20771 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:21:52.578039Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T04:39:34.638237Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2932c929-5f41-4754-bfab-a7c1bb4c1407 · inbound

Thinking beyond the anthropomorphic paradigm benefits LLM research cites this paper.

Thinking beyond the anthropomorphic paradigm benefits LLM research MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T22:21:52.578039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:21:52.578039Z digest=sha256:87f4b7acc5723025c5d8e8665eece2c36774adb2d45af4973433dbba37e14287

Observation ad746d5b-2b45-4b54-82da-e7c4ccfb0193 · inbound

Synergy: End-to-end Concept Model cites this paper.

Synergy: End-to-end Concept Model MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T16:45:34.114874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:45:34.114874Z digest=sha256:873f59783e0846e53f4a098095ae7238ca3ba3ab9c4e7dc6b96bef082c5acd5f

Observation 9411b321-d2b4-4d65-9136-3b363ca98be3 · inbound

Accelerating Vision Transformers with Adaptive Patch Sizes cites this paper.

Accelerating Vision Transformers with Adaptive Patch Sizes MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T05:42:24.447668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T05:41:48.429067Z digest=sha256:63061b3ddd0a30637869ee3a9577fe99c7eada7ac1210ef7d32f0f8ec072beff

Observation b180b5a6-dc70-4904-b5e7-e5b1062322d6 · inbound

Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models cites this paper.

Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:36:28.928013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T04:05:28.713898Z digest=sha256:7190806ff8b7bda4c8207a6ca0adc6ad7c449602d730ce92847b0f7d24341755

Observation 56843ffe-c741-42ce-87a2-a0da519ea809 · inbound

Phonemes to the Rescue: Multilingual Tokenization Based on International Phonetic Alphabet cites this paper.

Phonemes to the Rescue: Multilingual Tokenization Based on International Phonetic Alphabet MrT5: Dynamic Token Merging for Efficient Byte-level Language Models

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-04T04:39:34.639605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-26T16:53:25.556222Z digest=sha256:1076a9d647574e5b5652b98be9fcacf9c236812865728a60e1cdb305406ad204