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Paper Citation Record · LEDGER

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders

As of 18 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.18918.

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

pith.paper-citation-record.v1
2507.18918 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:12:07.565182Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

33 of 33 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 338e9752-2541-4f5e-9eff-8556e9c50f03 · outbound

This paper cites an unresolved cited work.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 30dae47e-ea84-4631-bb72-8cac32d9f511 · outbound

This paper cites an unresolved cited work.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unresolved cited work

Reference 2

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T18:12:07.445295Z digest=sha256:d3b6209ad03c36d38417afa6856d441c700c6057eb0ab03338f4ae3b3cbec903

Observation 2f8fcf33-469f-439c-ba78-92fcc59d02c0 · outbound

This paper cites an unresolved cited work.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 95582e47-0852-48c3-89db-470327b74b9d · outbound

This paper cites Systematic Inequalities in Language Technology Performance across the World's Languages.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Systematic Inequalities in Language Technology Performance across the World's Languages

Reference 4

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T18:12:07.452951Z digest=sha256:09ea7863e782a6b7442a995da34b2f61e11f19820f660f5710b4ce747fc1335c

Observation 84951191-8638-47f1-9c88-b9a332d33934 · outbound

This paper cites an unresolved cited work.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-08-15T18:12:07.456879Z digest=sha256:a9510a083bdc9414c03211a27f9a3e5633b07a28abd8477e3b789c43babaa361

Observation d24892a7-df8f-44cf-a001-43ec47384f1c · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 6

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source=arxiv_source observed=2026-08-15T18:12:07.460681Z digest=sha256:423033fef2f75c730733a82f1475f7e5333dfae83ec6fb2e962a9b54e25ca5fe

Observation 0cd44d18-a358-4baa-b2e9-508c23dda289 · outbound

This paper cites Unsupervised Cross-lingual Representation Learning at Scale.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unsupervised Cross-lingual Representation Learning at Scale

Reference 7

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source=arxiv_source observed=2026-08-15T18:12:07.464739Z digest=sha256:d219a8c9c1cafb2b07110e041301935cd6f085cb3fc40ba03323fcfeddb1ea7e

Observation c8a9de56-83c1-4a5d-9f4f-54012f242757 · outbound

This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 8

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source=arxiv_source observed=2026-08-15T18:12:07.468581Z digest=sha256:20bdad42c5d23ac707abeb30bd08a1fc12303aa6b886276d96523e4710509340

Observation f9f247ba-77bc-42a9-a6ec-8edfb29ef416 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Gemma: Open Models Based on Gemini Research and Technology

Reference 9

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T18:12:07.472358Z digest=sha256:0e0438675d127dd511e17e6295ee855cfede93aaa80d8146b0f1cf47536027bd

Observation 2d5cdec2-966e-4907-bb4a-70d84ddbc6a0 · outbound

This paper cites The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.476011Z digest=sha256:7ff8c4dcc9e7fdaaff757d389a224e7023535c89b56393b77968e89a01b2d18d

Observation 43a8ccbc-ed78-492c-9528-4713f8c44c46 · outbound

This paper cites Identifying Necessary Elements for BERT's Multilinguality.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Identifying Necessary Elements for BERT's Multilinguality

Reference 11

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local_arxiv, observed 2026-08-15T18:12:07.763933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T18:12:07.479660Z digest=sha256:227611278b23339f0418afeadd9a4a15be02573a1854d8f6a14848a315a0a292

Observation aa21e598-c817-4c42-80a1-e37880f20baa · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Measuring Massive Multitask Language Understanding

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.483681Z digest=sha256:6c1cf9692ddced09619d7180ee3cd010bc04a3e43f00a1560cded0d99fefe84a

Observation d9b9f68f-ef4b-431f-abc0-b633ce3fd7a8 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders LoRA: Low-Rank Adaptation of Large Language Models

Reference 13

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source=arxiv_source observed=2026-08-15T18:12:07.488131Z digest=sha256:40d740dc2c0ae49c28b39d6793fbc03ba38df751217c29a9f78b29c828e15ed7

Observation 9610adb6-cb65-4d53-ac34-7525a812593b · outbound

This paper cites an unresolved cited work.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T18:12:07.491710Z digest=sha256:b47c2f12d0a6d58291a36e36d208f01f0e4ed7a6a2dd8f99effe9e23b8415b3d

Observation 18b34b9e-5ad8-43c2-b84c-b983a4f96d36 · outbound

This paper cites Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback

Reference 16

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Unavailable: canonical work link unavailable.

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Observation ac351c88-0f6b-467e-b448-a4f9f350efd8 · outbound

This paper cites Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 17

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source=arxiv_source observed=2026-08-15T18:12:07.503183Z digest=sha256:ee24839e9ef8e8065f3648e1c19341ff4fd9ab7dbd608c57cb551eb36e7192f1

Observation 65ced990-2faf-40ae-9479-e8107dfd4336 · outbound

This paper cites Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.506862Z digest=sha256:beb03b99964680c3d56273992a3a3b1db5baab4cc36e3f474787999ff45ebf9e

Observation cd027f01-ae11-43ac-9eea-d2075c23a12a · outbound

This paper cites Interpreting Attention Layer Outputs with Sparse Autoencoders.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Interpreting Attention Layer Outputs with Sparse Autoencoders

Reference 19

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source=arxiv_source observed=2026-08-15T18:12:07.510290Z digest=sha256:6501ccb9aca08214bbea8f1f03834e62b656f3a821fd34c177ff51d5ba357148

Observation 3cf4eab1-5070-485f-beae-68169c7a2eca · outbound

This paper cites GPT-4 Technical Report.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders GPT-4 Technical Report

Reference 20

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source=arxiv_source observed=2026-08-15T18:12:07.514015Z digest=sha256:f6afab491fed3818dc568bbf9a3c27f6f08e9e92d5f31e51592a0adb14921ebf

Observation 595945d9-5b3a-4bbe-a9e5-72bf3a91ff0b · outbound

This paper cites IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators

Reference 21

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source=arxiv_source observed=2026-08-15T18:12:07.517155Z digest=sha256:d2f114d0fc8b069f8e12c57d45c5bb30c0bdd9ceb020f8da801e1db5b0ef7e21

Observation c39cf441-6218-4598-97e6-1175032c620a · outbound

This paper cites How multilingual is Multilingual BERT?.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders How multilingual is Multilingual BERT?

Reference 22

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Source-reported events for the cited work

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Observation 693ea4bc-6062-434b-bbc4-edb4fb6fb2c9 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Gemma 2: Improving Open Language Models at a Practical Size

Reference 23

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source=arxiv_source observed=2026-08-15T18:12:07.525198Z digest=sha256:35eda336bb37c40101098b6a94f92a18798322ffa4cf0866c46bf90bba5d9db6

Observation a4f78c07-9115-4035-9b3e-258232668620 · outbound

This paper cites ChatGPT MT: Competitive for High- (but not Low-) Resource Languages.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders ChatGPT MT: Competitive for High- (but not Low-) Resource Languages

Reference 24

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source=arxiv_source observed=2026-08-15T18:12:07.528680Z digest=sha256:27759ccace15ac161b0b1361f7d7f7bb03bb9ea98b303a2eddb00ac8a7b0dcd9

Observation 56e94ebc-a771-43bf-ab5b-7e8125e9545e · outbound

This paper cites Fine-tuning Whisper on Low-Resource Languages for Real-World Applications.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Fine-tuning Whisper on Low-Resource Languages for Real-World Applications

Reference 25

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no resolver link, observed 2026-08-15T18:12:07.532281Z

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source=arxiv_source observed=2026-08-15T18:12:07.532281Z digest=sha256:f9aa85eb4f5947dab005333239eac0e501746443eeab98f52193dd97d25a4a47

Observation f6a1ed88-a265-4b69-9b33-88e91f636db2 · outbound

This paper cites Turner, Callum McDougall, Monte MacDiarmid, Alex Tamkin, Esin Durmus, Tristan Hume, Francesco Mosconi, C.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Turner, Callum McDougall, Monte MacDiarmid, Alex Tamkin, Esin Durmus, Tristan Hume, Francesco Mosconi, C

Reference 26

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T18:12:07.535894Z digest=sha256:76fbaaed93f0fc473a582da97bb87a768da6187b552ac352c372a05be6dda611

Observation 43c6d25f-51a1-47db-a601-b8a65e6d4c87 · outbound

This paper cites o rg Tiedemann, Mikko Aulamo, Daria Bakshandaeva, Michele Boggia, Stig-Arne Gr \.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders o rg Tiedemann, Mikko Aulamo, Daria Bakshandaeva, Michele Boggia, Stig-Arne Gr \

Reference 27

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no resolver link, observed 2026-08-15T18:12:07.539077Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.539077Z digest=sha256:b53e17b9019b461e9965f4864bd9d942e28734e70fbfcdf0cd67c69a56715757

Observation c079181b-6477-4c7c-a75a-ad2a598e78a8 · outbound

This paper cites an unresolved cited work.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Unresolved cited work

Reference 28

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raw_fallback, observed 2026-08-15T18:12:07.874412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T18:12:07.544343Z digest=sha256:7926124be32f1ae91d1a1657efc03ec62ada8124be1b1f3c978f68ecfaf45c3c

Observation fc43fd43-4f86-4daf-b10a-cd8b862e6b69 · outbound

This paper cites true features.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders true features

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T18:12:07.862506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T18:12:07.547717Z digest=sha256:3d291477af1b17aa1b7af121d2737da92449cf9e65e8d3c978a921c5b4964a94

Observation 18aae1e9-5d63-4c40-b02a-283974f426ae · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.550986Z digest=sha256:4caa1a11c14cc5259029f794e02753045acf354d7e0f4e9382bf845a246ce43d

Observation dd8fad50-0d86-4d6e-b3ee-260b2164c0b2 · outbound

This paper cites Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models

Reference 31

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no resolver link, observed 2026-08-15T18:12:07.554627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.554627Z digest=sha256:b0d88096b8f891d25f007f3e44a1028e1c33bb84adb44453b573ef131f237a29

Observation e6ffd819-0129-4a67-b9f3-6e1a4a93c22e · outbound

This paper cites Investigating Layer Importance in Large Language Models.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders Investigating Layer Importance in Large Language Models

Reference 32

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source=arxiv_source observed=2026-08-15T18:12:07.558217Z digest=sha256:2f11bf5d66e0be898d80744da8d580e994565241f5faaf926a10fd6cf02f828d

Observation b16c7baa-af1b-46f6-bae1-019d67671d3d · outbound

This paper cites online" 'onlinestring :=.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders online" 'onlinestring :=

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.561681Z digest=sha256:24c57ada0bf345133155b1eda2b6379e080650a8b359b311bab43d0718fe1830

Observation cd4e9386-d0e7-46b2-b79f-1e9d61eea54c · outbound

This paper cites write newline.

Uncovering Cross-Linguistic Disparities in LLMs using Sparse Autoencoders write newline

Reference 34

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no resolver link, observed 2026-08-15T18:12:07.565182Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:12:07.565182Z digest=sha256:59db2cc8ec06d5d904f58b50167ba418adbfd360b4be24137d38ab238d39ccf8

Pith citing papers

No inbound Pith citation observations are available.