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Paper Citation Record · LEDGER

Linear representations of grammaticality in neural language models

As of 9 August 2026, this Paper Citation Record lists 100 of 234 outbound references and 0 inbound Pith citation observations for arXiv:2607.15175.

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

pith.paper-citation-record.v1
2607.15175 v1

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measured 100 of 234 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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Source: cited_works

Reference resolution

100 of 234 outbound references displayed

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External citation measurements

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Outbound references

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This paper cites Language Acquisition , booktitle =.

Linear representations of grammaticality in neural language models Language Acquisition , booktitle =

Reference 1

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Linear representations of grammaticality in neural language models and Murty, Shikhar , year = 2025, month = nov, number =

Reference 2

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Linear representations of grammaticality in neural language models Transactions on Machine Learning Research , issn =

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Linear representations of grammaticality in neural language models Proceedings of the 2023

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Linear representations of grammaticality in neural language models Modeling

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Linear representations of grammaticality in neural language models Rules vs

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Linear representations of grammaticality in neural language models Naturalistic

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Linear representations of grammaticality in neural language models Unresolved cited work

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Reference 9

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Linear representations of grammaticality in neural language models Constraint-Based

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Linear representations of grammaticality in neural language models Unresolved cited work

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Linear representations of grammaticality in neural language models Analyzing

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Linear representations of grammaticality in neural language models Analysis

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Linear representations of grammaticality in neural language models and Flickinger, Dan and Oepen, Stephan and Packard, Woodley and Copestake, Ann , editor =

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Linear representations of grammaticality in neural language models and Gebru, Timnit and

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Linear representations of grammaticality in neural language models Cognitive Psychology , volume =

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Linear representations of grammaticality in neural language models Paradigm

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Linear representations of grammaticality in neural language models Explanatory Models in Neuroscience,

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Linear representations of grammaticality in neural language models Meaning and

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Linear representations of grammaticality in neural language models Syntactic

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Linear representations of grammaticality in neural language models Aspects of the

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Linear representations of grammaticality in neural language models Systematic Testing of Three

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Linear representations of grammaticality in neural language models Proceedings of the 2019

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Linear representations of grammaticality in neural language models How Syntax Specialization Emerges in Language Models

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Linear representations of grammaticality in neural language models Probing for

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Linear representations of grammaticality in neural language models Synthesizing Theories of Human Language with

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Linear representations of grammaticality in neural language models Language , volume =

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Linear representations of grammaticality in neural language models and Griffiths, Thomas L

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Linear representations of grammaticality in neural language models Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

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Linear representations of grammaticality in neural language models Meaningful Questions:

Reference 52

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Linear representations of grammaticality in neural language models and Pylyshyn, Zenon W

Reference 53

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Linear representations of grammaticality in neural language models Free Choice and the Theory of Scalar Implicatures , booktitle =

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Linear representations of grammaticality in neural language models Cognition , volume =

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Linear representations of grammaticality in neural language models Sequence-to-

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Linear representations of grammaticality in neural language models , year = 1971, journal =

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Linear representations of grammaticality in neural language models Neural Language Models as Psycholinguistic Subjects:

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Linear representations of grammaticality in neural language models , editor =

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Linear representations of grammaticality in neural language models Compositionality:

Reference 63

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Linear representations of grammaticality in neural language models Bootstrapping Word Order in Prelexical Infants: A

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Linear representations of grammaticality in neural language models From Fieldwork to Linguistic Theory:

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Linear representations of grammaticality in neural language models Information and Control , volume =

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Linear representations of grammaticality in neural language models Reporting Bias and Knowledge Acquisition , booktitle =

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Linear representations of grammaticality in neural language models Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences , volume =

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Linear representations of grammaticality in neural language models The Llama 3 Herd of Models

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Linear representations of grammaticality in neural language models Universals of language , volume =

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Linear representations of grammaticality in neural language models Proceedings of the National Academy of Sciences , volume =

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Linear representations of grammaticality in neural language models , year = 1994, journal =

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Linear representations of grammaticality in neural language models Generative Linguistics, Large Language Models, and the Social Nature of Scientific Success

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Linear representations of grammaticality in neural language models and Gobbini, M

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Reference 78

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Linear representations of grammaticality in neural language models Decoding Probing: Revealing Internal Linguistic Structures in Neural Language Models using Minimal Pairs

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Linear representations of grammaticality in neural language models Proceedings of the National Academy of Sciences , volume =

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Linear representations of grammaticality in neural language models Semantics in

Reference 81

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Linear representations of grammaticality in neural language models Measuring

Reference 82

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Linear representations of grammaticality in neural language models Designing and

Reference 83

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Linear representations of grammaticality in neural language models , editor =

Reference 84

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Observation c85ca04e-ea75-4586-8c27-98f54c7b499f · outbound

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Linear representations of grammaticality in neural language models Unresolved cited work

Reference 85

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This paper cites Proceedings of the National Academy of Sciences , volume =.

Linear representations of grammaticality in neural language models Proceedings of the National Academy of Sciences , volume =

Reference 86

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Observation 6d1a6cb6-9cac-49d5-b46d-0ccd46d6f920 · outbound

This paper cites Florian and Arnon, Inbal and Sag, Ivan A.

Linear representations of grammaticality in neural language models Florian and Arnon, Inbal and Sag, Ivan A

Reference 87

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Source-reported events for the cited work

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This paper cites A Closer Look at the Performance of Neural Language Models on Reflexive Anaphor Licensing , booktitle =.

Linear representations of grammaticality in neural language models A Closer Look at the Performance of Neural Language Models on Reflexive Anaphor Licensing , booktitle =

Reference 88

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This paper cites an unresolved cited work.

Linear representations of grammaticality in neural language models Unresolved cited work

Reference 89

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Observation dff6a580-fe38-4d52-adfb-aedb7edcb5ef · outbound

This paper cites Prompting Is Not a Substitute for Probability Measurements in Large Language Models , booktitle =.

Linear representations of grammaticality in neural language models Prompting Is Not a Substitute for Probability Measurements in Large Language Models , booktitle =

Reference 90

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Observation d06c2bae-7471-4182-877b-32d92f7b0284 · outbound

This paper cites Proceedings of the National Academy of Sciences , volume =.

Linear representations of grammaticality in neural language models Proceedings of the National Academy of Sciences , volume =

Reference 91

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Observation 085d4b06-a331-4901-8ec5-165cb1d6ce09 · outbound

This paper cites and Petty, Jackson and Shi, Chuan and Merrill, William and Linzen, Tal , editor =.

Linear representations of grammaticality in neural language models and Petty, Jackson and Shi, Chuan and Merrill, William and Linzen, Tal , editor =

Reference 92

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Observation 380f077e-0e2c-4b78-a9ac-3bf8380e2fd9 · outbound

This paper cites Shades of Zero:.

Linear representations of grammaticality in neural language models Shades of Zero:

Reference 93

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Observation 7a28d91a-8753-430a-9fd5-fe2bd1121441 · outbound

This paper cites Signatures of human-like processing in Transformer forward passes.

Linear representations of grammaticality in neural language models Signatures of human-like processing in Transformer forward passes

Reference 94

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Source-reported events for the cited work

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Observation e12f08c4-6f39-4f70-bae1-335530f3dc06 · outbound

This paper cites , year = 2026, month = jan, journal =.

Linear representations of grammaticality in neural language models , year = 2026, month = jan, journal =

Reference 95

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Observation d3129105-31b0-4aa3-99ca-31d1b5593cec · outbound

This paper cites and Newport, Elissa L.

Linear representations of grammaticality in neural language models and Newport, Elissa L

Reference 96

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Observation dc511850-1e96-4894-9741-e0544d6029b7 · outbound

This paper cites and Newport, Elissa L.

Linear representations of grammaticality in neural language models and Newport, Elissa L

Reference 97

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Observation 37acc48b-3b1a-4128-a139-4f7acbc1a267 · outbound

This paper cites and Sulem, Elior and Cynthia, Fisher and Roth, Dan , editor =.

Linear representations of grammaticality in neural language models and Sulem, Elior and Cynthia, Fisher and Roth, Dan , editor =

Reference 98

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Observation a8bbe862-1078-4200-9006-b3fbe6f316ca · outbound

This paper cites Compositionality.

Linear representations of grammaticality in neural language models Compositionality

Reference 99

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source=arxiv_source observed=2026-08-01T23:59:43.760797Z digest=sha256:fe759551cd98274c12d4be9e44fcdd7fa7bee3902caf65aea1562375c53fcccc

Observation 44fd4e4c-7d50-4616-8b2c-dfa423ab9060 · outbound

This paper cites How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgments.

Linear representations of grammaticality in neural language models How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgments

Reference 100

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verified exact
local_arxiv, observed 2026-08-02T00:04:11.597976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

No inbound Pith citation observations are available.