Paper Citation Record · LEDGER

Natural Language-based Assessment of L2 Oral Proficiency using LLMs

As of 15 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 2 inbound Pith citation observations for arXiv:2507.10200.

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

pith.paper-citation-record.v1
2507.10200 v1

Coverage vector

measured 42 of 42 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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

Source: pith, observed 2026-08-06T17:43:17.637365Z

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation eefaa68c-ccb6-4c1d-9f4e-db326a493b34 · outbound

This paper cites Natural Language-based Assessment of L2 Oral Proficiency using LLMs.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Natural Language-based Assessment of L2 Oral Proficiency using LLMs

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:43:17.726088Z

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Observation 30ddd0f2-15a1-40fb-9c0a-fa01d62a79ab · outbound

This paper cites It aims to assess whether LLMs can interpret and apply these descriptors in a manner comparable to human raters.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs It aims to assess whether LLMs can interpret and apply these descriptors in a manner comparable to human raters

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:25.702669Z

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Observation 44071626-1210-4fe2-b021-754d5dd9fdba · outbound

This paper cites Both the LNG and S&I language tests comprise five sections, each designed to assess a different as- pect of a candidate’s language proficiency.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Both the LNG and S&I language tests comprise five sections, each designed to assess a different as- pect of a candidate’s language proficiency

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:25.419607Z

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Observation 9783b6a6-a71f-493a-846d-e6e8054a5fc0 · outbound

This paper cites tised) [23], in a zero-shot setting.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs tised) [23], in a zero-shot setting

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:25.186787Z

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Observation 14e9dfec-cd5f-4a35-bcb2-7f2321a8e62b · outbound

This paper cites Train Type PCC SRC Dev Eval Dev Eval BERT S&I Spont.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Train Type PCC SRC Dev Eval Dev Eval BERT S&I Spont

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:24.990827Z

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Observation 3e42944a-40c0-4146-b374-ac48f367e922 · outbound

This paper cites Our results demon- strate that this approach, relying exclusively on textual informa- tion in a zero-shot setting, achieves competitive performance.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Our results demon- strate that this approach, relying exclusively on textual informa- tion in a zero-shot setting, achieves competitive performance

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:24.717632Z

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Observation 1794ded0-ee0c-4dbe-b4bb-6905b4b7ec92 · outbound

This paper cites Howson, The English effect.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Howson, The English effect

Reference 7

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Observation 48536f72-cbfc-4eb2-98bd-48926cd2f441 · outbound

This paper cites Contrasting Automated and Human Scoring of Es- says,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Contrasting Automated and Human Scoring of Es- says,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:24.280306Z

Source-reported events for the cited work

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Observation 0366a5d3-14f4-4af1-b2f0-b9e2f4860d6c · outbound

This paper cites Fully automated speaking assessment: changes to pro- ficiency testing and the role of pronunciation,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Fully automated speaking assessment: changes to pro- ficiency testing and the role of pronunciation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:24.028980Z

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Observation b494bd61-4cce-4f31-8617-eabeb3e5ba5a · outbound

This paper cites Limitations of the Common European Framework for developing comparable examinations and tests,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Limitations of the Common European Framework for developing comparable examinations and tests,

Reference 10

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This paper cites Strasbourg: Council of Europe, 2020.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Strasbourg: Council of Europe, 2020

Reference 11

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Observation e173d5ba-372a-494d-8326-346e9b8be6b9 · outbound

This paper cites Facets of Speaking Proficiency,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Facets of Speaking Proficiency,

Reference 12

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Observation c604b6f9-b14b-48ab-84d0-96c243f23394 · outbound

This paper cites Automat- ically assessing the oral proficiency of proficient L2 speakers.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Automat- ically assessing the oral proficiency of proficient L2 speakers

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:23.154519Z

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Observation b0b13542-d97a-43b0-a158-0c8ef4b9a682 · outbound

This paper cites Applications of text analysis tools for spoken response grading.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Applications of text analysis tools for spoken response grading

Reference 14

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Observation 9b7851a9-77cf-43ee-8188-f59f22888ee7 · outbound

This paper cites Towards automatic as- sessment of spontaneous spoken English,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Towards automatic as- sessment of spontaneous spoken English,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:22.676966Z

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Observation 7ebc5339-a293-4236-918b-710991a21b4b · outbound

This paper cites Dolphin: a spoken language proficiency assessment system for elementary education,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Dolphin: a spoken language proficiency assessment system for elementary education,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:22.376031Z

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Observation 5f887bb0-fd34-4b1c-9dae-eb48327579b7 · outbound

This paper cites In- vestigating the Effect of Auxiliary Objectives for the Automated Grading of Learner English Speech Transcriptions,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs In- vestigating the Effect of Auxiliary Objectives for the Automated Grading of Learner English Speech Transcriptions,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:22.160620Z

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Observation f84e9255-ef0b-48a9-aab1-074375d5d3ee · outbound

This paper cites Universal Adversarial Attacks on Spoken Language Assessment Systems,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Universal Adversarial Attacks on Spoken Language Assessment Systems,

Reference 18

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Observation c0e1d985-3018-4dd2-a9fc-e6b8d9eb7ec4 · outbound

This paper cites Automated Scoring of Spontaneous Speech from Young Learners of English Using Transformers,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Automated Scoring of Spontaneous Speech from Young Learners of English Using Transformers,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:21.576210Z

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Observation 6b0fc159-ecb4-42ba-9d4e-ef29bf104b39 · outbound

This paper cites Proficiency assessment of L2 spo- ken English using wav2vec 2.0,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Proficiency assessment of L2 spo- ken English using wav2vec 2.0,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:21.339092Z

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Observation 22e352e8-6cf6-42c6-a01f-6cff92a67fd5 · outbound

This paper cites Assessment of L2 Oral Proficiency Using Self-Supervised Speech Representation Learning,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Assessment of L2 Oral Proficiency Using Self-Supervised Speech Representation Learning,

Reference 21

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Observation 04a2232a-98cf-4295-bf06-6c3decfa9ebb · outbound

This paper cites Automatic Assessment of Conversational Speaking Tests,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Automatic Assessment of Conversational Speaking Tests,

Reference 22

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Observation bba0013d-c17b-4042-8942-bcaff930b096 · outbound

This paper cites Rating nonnative writing: The trouble with holistic scoring,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Rating nonnative writing: The trouble with holistic scoring,

Reference 23

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Observation 4e18fdad-f612-49e8-bdce-3e7aec9dd4e3 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,

Reference 24

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This paper cites Toward Automated Multi-trait Scoring of Essays: Investigating Links among Holistic, Analytic, and Text Feature Scores,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Toward Automated Multi-trait Scoring of Essays: Investigating Links among Holistic, Analytic, and Text Feature Scores,

Reference 25

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This paper cites Weight-Based Classification of Raters and Rater Cognition in an EFL Speaking Test,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Weight-Based Classification of Raters and Rater Cognition in an EFL Speaking Test,

Reference 26

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This paper cites Douglas and J.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Douglas and J

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:20.359612Z

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Observation ddb9cbd2-917f-4dc2-9f2f-054001d4f911 · outbound

This paper cites Speak & Improve Corpus 2025: an L2 English Speech Corpus for Language Assessment and Feedback.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Speak & Improve Corpus 2025: an L2 English Speech Corpus for Language Assessment and Feedback

Reference 28

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This paper cites Emergent Abilities of Large Language Models,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Emergent Abilities of Large Language Models,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:20.028364Z

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Observation 4f813556-e641-4a9c-8a09-16cafaaf56a6 · outbound

This paper cites Qwen2.5 Technical Report.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Qwen2.5 Technical Report

Reference 30

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This paper cites Robust speech recognition via large-scale weak supervision,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Robust speech recognition via large-scale weak supervision,

Reference 31

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Natural Language-based Assessment of L2 Oral Proficiency using LLMs Qwen2-Audio Technical Report

Reference 32

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This paper cites Rating short L2 essays on the CEFR scale with GPT-4,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Rating short L2 essays on the CEFR scale with GPT-4,

Reference 33

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Natural Language-based Assessment of L2 Oral Proficiency using LLMs Distribution-free multiple comparisons,

Reference 34

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This paper cites Can GPT-4 do L2 analytic assessment?.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Can GPT-4 do L2 analytic assessment?

Reference 35

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This paper cites As- sessment of L2 Oral Proficiency Using Speech Large Language Models,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs As- sessment of L2 Oral Proficiency Using Speech Large Language Models,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:18.681100Z

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This paper cites Ludlow, Official Quick Guide to Linguaskill.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Ludlow, Official Quick Guide to Linguaskill

Reference 37

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Observation ba9c11ea-3c95-4a48-a7bb-601058e2c7d9 · outbound

This paper cites Speak & Improve Challenge 2025: Tasks and Baseline Systems.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Speak & Improve Challenge 2025: Tasks and Baseline Systems

Reference 38

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This paper cites LLM comparative assessment: Zero-shot NLG evaluation through pairwise comparisons using large language models,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs LLM comparative assessment: Zero-shot NLG evaluation through pairwise comparisons using large language models,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:18.272917Z

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This paper cites The use of ranks to avoid the assumption of nor- mality implicit in the analysis of variance,.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs The use of ranks to avoid the assumption of nor- mality implicit in the analysis of variance,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:43:18.061531Z

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Observation a56a5dba-d2a7-47a1-863b-86067671048b · outbound

This paper cites Available: https://aclanthology.org/2023.bea-1.49.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Available: https://aclanthology.org/2023.bea-1.49

Reference 584

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Observation ccb0c69f-4848-485a-bbbb-fe421ff923ee · outbound

This paper cites Available: http://www.jstor.org/stable/3588173.

Natural Language-based Assessment of L2 Oral Proficiency using LLMs Available: http://www.jstor.org/stable/3588173

Reference 1995

Resolution: verified exact; raw_fallback, observed 2026-08-06T17:43:17.487708Z

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Pith citing papers

Observation eefaa68c-ccb6-4c1d-9f4e-db326a493b34 · inbound