Paper Citation Record · LEDGER

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models

As of 7 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2506.07645.

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

pith.paper-citation-record.v1
2506.07645 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:31:53.253028Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:49:52.821536Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:49:56.116681Z

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy22
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4d008695-f593-4208-ba51-31e4e4e421da · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:57.455663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9f71cab-131f-46ad-a00d-14d9a0fa2149 · outbound

This paper cites Abhishek Kadian.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Abhishek Kadian

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:57.279635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d0873e1-42d8-4ccc-bf06-f60b293f89ab · outbound

This paper cites Is bert really robust? a strong baseline for natural language attack on text classification and entailment.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Is bert really robust? a strong baseline for natural language attack on text classification and entailment

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:57.065191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 494ce934-11f8-465d-98af-2063a34bfb3f · outbound

This paper cites BERT-ATTACK: Adversarial Attack Against BERT Using BERT.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models BERT-ATTACK: Adversarial Attack Against BERT Using BERT

Reference 4

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Observation 7a4fd339-e467-415a-aeaa-a5c304c995cf · outbound

This paper cites T3: Tree-autoencoder constrained adversarial text generation for targeted attack.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models T3: Tree-autoencoder constrained adversarial text generation for targeted attack

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:56.934032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0e6dce39-9b11-4ff2-bc6b-b8e9cee93ee7 · outbound

This paper cites Word-level textual adversarial attacking as combinatorial optimization.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Word-level textual adversarial attacking as combinatorial optimization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:56.769717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 708ca4f9-ed20-4287-b385-20c6778e8517 · outbound

This paper cites Jailbroken: How does llm safety training fail? In A.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Jailbroken: How does llm safety training fail? In A

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:56.608085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2c7cd213-aa61-43a0-83fc-aa177eb2dcf9 · outbound

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

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 8

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Source-reported events for the cited work

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Observation 520d65f0-4b99-4d75-a8cb-f9ded3c3d50d · outbound

This paper cites Unsupervised cross-lingual representation learning at scale.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Unsupervised cross-lingual representation learning at scale

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:56.440564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9efb2c49-8718-4600-89ac-d171f7d68c43 · outbound

This paper cites Command r +, 2024.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Command r +, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:56.270851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ab00409d-a765-44c0-ab85-7562cdddffc7 · outbound

This paper cites Qwen2 technical report, 2024.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Qwen2 technical report, 2024

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d911da25-be68-4681-ac4f-cec3cee70907 · outbound

This paper cites Textbugger: Generating adversarial text against real-world applications.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Textbugger: Generating adversarial text against real-world applications

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:56.115353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 061bbeb1-a010-4f80-9e34-d7af884bcb74 · outbound

This paper cites Zico Kolter, and Matt Fredrikson.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Zico Kolter, and Matt Fredrikson

Reference 13

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Source-reported events for the cited work

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Observation 8790b90f-0382-4bdd-8466-9fe2a9fb89bf · outbound

This paper cites Adversarial glue: A multi-task benchmark for robustness evaluation of language models.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Adversarial glue: A multi-task benchmark for robustness evaluation of language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.960751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d782fc8d-f70e-4391-867e-14dff1aa4d3a · outbound

This paper cites Decodingtrust: A comprehensive assessment of trustworthiness in gpt models.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Decodingtrust: A comprehensive assessment of trustworthiness in gpt models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.836210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4d710b39-8dc0-4301-92fc-11298720ee4c · outbound

This paper cites Deep inside convolutional networks: visualising image classification models and saliency maps.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Deep inside convolutional networks: visualising image classification models and saliency maps

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.707012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 82d185ad-bddb-4010-9096-5e5b31a96d63 · outbound

This paper cites A unified approach to interpreting model predictions.Advances in neural information processing systems, 30:4765–4774, 2017.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models A unified approach to interpreting model predictions.Advances in neural information processing systems, 30:4765–4774, 2017

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.497368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5bd1de35-5a22-4fd3-bef5-7754d2d6dc14 · outbound

This paper cites why should i trust you?.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models why should i trust you?

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.348533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 64325dac-4991-4c87-9b3f-ed2d3dea7f14 · outbound

This paper cites Not Just a Black Box: Learning Important Features Through Propagating Activation Differences.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Not Just a Black Box: Learning Important Features Through Propagating Activation Differences

Reference 19

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Source-reported events for the cited work

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Observation d71100d1-4b94-408f-b8f1-e95597503279 · outbound

This paper cites Axiomatic attribution for deep networks.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Axiomatic attribution for deep networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.187002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0a8f3b63-2968-47ff-98b6-a2dec677041b · outbound

This paper cites SmoothGrad: removing noise by adding noise.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models SmoothGrad: removing noise by adding noise

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:51.789088Z

Source-reported events for the cited work

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Observation 03d2b5f1-1aaa-4c82-8cb4-5f497f00d6f7 · outbound

This paper cites Quantifying attention flow in transformers.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Quantifying attention flow in transformers

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:55.043952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6ac6f594-cb48-4528-8d52-7c735742f2fe · outbound

This paper cites an unresolved cited work.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:31:54.916931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 05941d96-703e-4298-9545-7f134d8218a6 · outbound

This paper cites Transformer interpretability beyond attention visualization.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Transformer interpretability beyond attention visualization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:52.081039Z

Source-reported events for the cited work

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Observation 676f16b6-9d68-4595-82c5-30213ecc561a · outbound

This paper cites an unresolved cited work.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aa0759a2-3815-4780-a733-9d29ec8e95a4 · outbound

This paper cites HerBERT: Efficiently pretrained transformer-based language model for Polish.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models HerBERT: Efficiently pretrained transformer-based language model for Polish

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:54.577546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 134639a1-038d-493a-acf8-5c0540e5a903 · outbound

This paper cites Polbert: Attacking polish nlp tasks with transformers.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Polbert: Attacking polish nlp tasks with transformers

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:54.436921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 084fd28a-2ccb-4c01-a893-002d81e697cd · outbound

This paper cites Assessing generalization capability of text ranking models in polish,.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Assessing generalization capability of text ranking models in polish,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:54.295432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d9afd97-688d-428c-bb26-f0933bb5f6f5 · outbound

This paper cites Bielik 7b v0.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Bielik 7b v0

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:52.563257Z

Source-reported events for the cited work

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Observation c949ec37-2fa7-4bd4-84cd-846400d902ad · outbound

This paper cites OpenChat: Advancing Open-source Language Models with Mixed-Quality Data.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models OpenChat: Advancing Open-source Language Models with Mixed-Quality Data

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:52.627591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a07116a8-6252-46a8-9d49-de7c94e931c5 · outbound

This paper cites PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:52.719510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 031ca908-b744-490f-b050-7b0ccbfccc79 · outbound

This paper cites On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:52.805313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e2795de-e445-400b-868b-4dcd724c71fa · outbound

This paper cites Maziarz, Maciej Piasecki, and Ewa K.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Maziarz, Maciej Piasecki, and Ewa K

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:54.178357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b526d6b0-99d6-4bc3-aaf6-2db5d5d1ecf5 · outbound

This paper cites KLEJ: Comprehensive Benchmark for Polish Language Understanding.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models KLEJ: Comprehensive Benchmark for Polish Language Understanding

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:52.962319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b77522c8-dffb-4987-8e05-59dedae8ba07 · outbound

This paper cites This is the way: designing and compiling lepiszcze, a comprehensive nlp benchmark for polish.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models This is the way: designing and compiling lepiszcze, a comprehensive nlp benchmark for polish

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:54.021129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b1548104-7518-4f9b-a2ee-2d03d8fbad11 · outbound

This paper cites an unresolved cited work.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:31:53.878229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0dfcd451-078c-4945-8501-ab3a93d71f72 · outbound

This paper cites Multi-level sentiment analysis of PolEmo 2.0: Extended corpus of multi-domain consumer reviews.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Multi-level sentiment analysis of PolEmo 2.0: Extended corpus of multi-domain consumer reviews

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:31:53.757806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6bbc474a-cffd-4379-9cb7-697953d4241e · outbound

This paper cites Mistral 7B.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Mistral 7B

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:53.253028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58f40129-988c-4afd-a6af-d427c95ca895 · outbound

This paper cites an unresolved cited work.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Unresolved cited work

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T05:31:50.358904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33062dbf-f4cb-4e11-82e0-e56bc0ac1b54 · outbound

This paper cites Assessing generalization capability of text ranking models in Polish.

Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models Assessing generalization capability of text ranking models in Polish

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:31:53.576927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 7daf2794-dfba-4877-a328-33cb345afc63 · inbound

PL-Guard: Benchmarking Language Model Safety for Polish cites this paper.

PL-Guard: Benchmarking Language Model Safety for Polish Evaluating LLMs Robustness in Less Resourced Languages with Proxy Models

Reference 2025

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T23:49:56.218135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.