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Paper Citation Record · LEDGER

MoKA: Mixture of Kronecker Adapters

As of 8 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2508.03527.

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

pith.paper-citation-record.v1
2508.03527 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:28:34.590211Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T21:48:48.992712Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T14:26:03.947475Z

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0b93b540-501b-41dc-97c8-609d362db498 · outbound

This paper cites KronA: Parameter Efficient Tuning with Kronecker Adapter.

MoKA: Mixture of Kronecker Adapters KronA: Parameter Efficient Tuning with Kronecker Adapter

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:33.780787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:33.780787Z digest=sha256:8eb40b1a97b2a14193d4bd03c9bb4cd65f0ace20330b0b808783ba5c0c1d2d08

Observation 8109c4af-8725-418c-b469-1345041d3055 · outbound

This paper cites Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor.

MoKA: Mixture of Kronecker Adapters Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:33.897425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:33.897425Z digest=sha256:0b3c10ccf7e3d34213f2adaf22c45b4d0b6a3bb895e68a94e1c1263468923a62

Observation a193b4b6-6741-48b7-9018-e7b89d864739 · outbound

This paper cites LongForm: Effective Instruction Tuning with Reverse Instructions.

MoKA: Mixture of Kronecker Adapters LongForm: Effective Instruction Tuning with Reverse Instructions

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:34.074035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:34.074035Z digest=sha256:9756c9df9a185a8507fc04bd3bd85b8c2a99cb32cdd6c00bffe4849389ab84e4

Observation 398f7ad0-4c69-430d-b57d-5f4caa47d79f · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

MoKA: Mixture of Kronecker Adapters Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:34.214306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:34.214306Z digest=sha256:e9b03cbeb493a6944b211239e86190ce80e279757f683880925dfad3915786cb

Observation a9bce604-f189-40d8-93be-f4b2ddffd55f · outbound

This paper cites Investigating Public Fine-Tuning Datasets: A Complex Review of Current Practices from a Construction Perspective.

MoKA: Mixture of Kronecker Adapters Investigating Public Fine-Tuning Datasets: A Complex Review of Current Practices from a Construction Perspective

Reference 11

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T04:28:34.792815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T04:28:34.368012Z digest=sha256:72156fa1d60188803daf206bf1b35c5368a2e6e216ae5cab3fe89ac29f946230

Observation a15730cf-80bd-49f5-b524-bcfc10e372cc · outbound

This paper cites On the Importance of Local Information in Transformer Based Models.

MoKA: Mixture of Kronecker Adapters On the Importance of Local Information in Transformer Based Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:34.473124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:34.473124Z digest=sha256:38cf3eee9216c4a03d8446162f2484966f62eca9c19f60c3b6f25b1d34b37e4a

Observation dc666cd6-ebc4-4e02-bcae-0adac4783d75 · outbound

This paper cites In Dernoncourt, F.; Preot ¸iuc-Pietro, D.; and Shimorina, A., eds.,Proceedings of the 2024 Conference on Empirical Methods in Natural Lan- guage Processing: Industry Track, 712–718.

MoKA: Mixture of Kronecker Adapters In Dernoncourt, F.; Preot ¸iuc-Pietro, D.; and Shimorina, A., eds.,Proceedings of the 2024 Conference on Empirical Methods in Natural Lan- guage Processing: Industry Track, 712–718

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:28:34.961222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T04:28:34.515854Z digest=sha256:f24f7e12ee50215952d98171d2e9e739b829c4b3f2a5b537f8c96b556e1f6b3a

Observation 153eea27-1dd9-44f9-aba1-491e7b5f0c34 · outbound

This paper cites DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation.

MoKA: Mixture of Kronecker Adapters DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:34.551886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:34.551886Z digest=sha256:1fc49739141fa77ff2be6da9cea02a35cfe14d09bf984de9037f23a4221e693c

Observation 72927286-97e1-4cca-9e47-4892a91ba835 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

MoKA: Mixture of Kronecker Adapters Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:34.590211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:34.590211Z digest=sha256:8177f4bc1d5b82a24d769e0742921fe9f7ced147d701d903ca187c46c510d1fe

Observation 8238bf12-6fe9-4c13-a33e-d723aa155c3a · outbound

This paper cites Decoupled Weight Decay Regularization.

MoKA: Mixture of Kronecker Adapters Decoupled Weight Decay Regularization

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:34.304235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:34.304235Z digest=sha256:25458fe1ca3211f419d91d3de0625ea32d9b74c518ffc6d99598f7411e7efa3d

Observation 62bc8c19-ee17-4ca1-8391-f080e4b94479 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

MoKA: Mixture of Kronecker Adapters Measuring Massive Multitask Language Understanding

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:33.823360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:33.823360Z digest=sha256:93ec2d9a3fb24a2ee08049ed05b22cda3d59afa60fd4b89d84a928cde70b13a5

Observation a8ea1ebd-a0f2-49ab-a5cb-d417771226cc · outbound

This paper cites In Moens, M.-F.; Huang, X.; Specia, L.; and Yih, S.

MoKA: Mixture of Kronecker Adapters In Moens, M.-F.; Huang, X.; Specia, L.; and Yih, S

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:28:35.100627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T04:28:34.163498Z digest=sha256:4cfd500fed18f2fa13ff0146eb5d9960631754176153b364818e1b0e2254d2fe

Observation 1e240c28-b347-42ab-ba56-2c48dac5cd80 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

MoKA: Mixture of Kronecker Adapters Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T04:28:33.553473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:33.553473Z digest=sha256:5a91e6e7b3266a0109ab656f5fa27e4e60be41e00ffe90b403f85489d1725ba1

Observation a14a0119-a895-482d-ad57-32f78b865002 · outbound

This paper cites In Bouamor, H.; Pino, J.; and Bali, K., eds., Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 5254–5276.

MoKA: Mixture of Kronecker Adapters In Bouamor, H.; Pino, J.; and Bali, K., eds., Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 5254–5276

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:28:35.294751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T04:28:33.984932Z digest=sha256:30eb8e3cc6ff59421a5639381d779bc7b0497ddacce162f10f8fb663204164da

Observation fb43819e-9dda-49c2-aa3f-37d0ad9023d0 · outbound

This paper cites In2024 Joint International Conference on Computational Linguistics, Language Resources and Evalu- ation, LREC-COLING 2024-Main Conference Proceedings, 350–357.

MoKA: Mixture of Kronecker Adapters In2024 Joint International Conference on Computational Linguistics, Language Resources and Evalu- ation, LREC-COLING 2024-Main Conference Proceedings, 350–357

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T04:28:35.396870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T04:28:33.676730Z digest=sha256:e45e209b3c2e0b23716811578cb2ab99043829890c737709b6f7127c66b267b6

Pith citing papers

Observation 382ec91b-9051-4b37-bbbc-2e8ac5e2fd96 · inbound

Low-Rank Adaptation Redux for Large Models cites this paper.

Low-Rank Adaptation Redux for Large Models MoKA: Mixture of Kronecker Adapters

Reference 156

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:26:03.949258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T21:48:48.992712Z digest=sha256:63fb2cedfce7d01b3634565c3f44c963366e3befa8166949769ecbfaaab8935b