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Paper Citation Record · LEDGER

Understanding Layer Patching in Model Size Interpolation

As of 6 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2607.08170.

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

pith.paper-citation-record.v1
2607.08170 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T11:57:18.311409Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

54 of 54 outbound references displayed

  • verified exact23
  • verified fuzzy24
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fa65313-406d-4a39-981d-59a5075baa5b · outbound

This paper cites Ainsworth, Jonathan Hayase, and Siddhartha S.

Understanding Layer Patching in Model Size Interpolation Ainsworth, Jonathan Hayase, and Siddhartha S

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation a0ea91b2-635a-4a70-8766-ec940537e774 · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

Understanding Layer Patching in Model Size Interpolation Pythia: A suite for analyzing large language models across training and scaling

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 1028b221-3d5d-4ef5-a449-8a63ce43d71e · outbound

This paper cites PIQA: reasoning about physical commonsense in natural language.

Understanding Layer Patching in Model Size Interpolation PIQA: reasoning about physical commonsense in natural language

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f9ed2c96-574f-4cb0-932b-d567d9f437b8 · outbound

This paper cites LL amaflex: Many-in-one LLM s via generalized pruning and weight sharing.

Understanding Layer Patching in Model Size Interpolation LL amaflex: Many-in-one LLM s via generalized pruning and weight sharing

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 00801676-17bb-4cbb-86e9-fb79b2a77fd8 · outbound

This paper cites B ool Q : Exploring the Surprising Difficulty of Natural Yes/No Questions.

Understanding Layer Patching in Model Size Interpolation B ool Q : Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 5

Resolution
verified exact
doi, observed 2026-07-10T12:07:03.406159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation c609ea54-dbef-4602-9f80-fe77aabb2a95 · outbound

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

Understanding Layer Patching in Model Size Interpolation Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.715577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 337f662d-d850-45c0-a642-c4fa805e5ccf · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Understanding Layer Patching in Model Size Interpolation Training Verifiers to Solve Math Word Problems

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.728260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation d5a81ca7-9983-49fe-aa9d-9bb79ee8dfab · outbound

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

Understanding Layer Patching in Model Size Interpolation BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 8

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verified exact
doi, observed 2026-07-10T12:07:03.419449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4df61d97-ead5-41cf-9f09-08c143b108f0 · outbound

This paper cites The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks.

Understanding Layer Patching in Model Size Interpolation The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.721928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4f52c028-f2d0-41e2-a701-3bfb560b9886 · outbound

This paper cites Linear mode connectivity and the lottery ticket hypothesis.

Understanding Layer Patching in Model Size Interpolation Linear mode connectivity and the lottery ticket hypothesis

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 916bff3e-c7ba-40b0-b11a-10b879f95800 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Understanding Layer Patching in Model Size Interpolation The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 11

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5c4da880-6d64-41af-a677-869b52d8132e · outbound

This paper cites Ariel Gera, Odellia Boni, Yotam Perlitz, Roy Bar-Haim, Lilach Eden, and Asaf Yehudai.

Understanding Layer Patching in Model Size Interpolation Ariel Gera, Odellia Boni, Yotam Perlitz, Roy Bar-Haim, Lilach Eden, and Asaf Yehudai

Reference 12

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metadata mismatch
arxiv_id, observed 2026-07-10T12:07:03.689822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 753d90a8-18aa-4def-b467-59b20b1889bc · outbound

This paper cites The Llama 3 Herd of Models.

Understanding Layer Patching in Model Size Interpolation The Llama 3 Herd of Models

Reference 13

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation a28d987c-d547-4b51-8c11-3097845455d2 · outbound

This paper cites an unresolved cited work.

Understanding Layer Patching in Model Size Interpolation Unresolved cited work

Reference 14

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 396b39c4-fd39-4290-aa70-0aec6d4b60b5 · outbound

This paper cites Amc: Automl for model compression and acceleration on mobile devices.

Understanding Layer Patching in Model Size Interpolation Amc: Automl for model compression and acceleration on mobile devices

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation e80836d8-51da-4e68-a284-87ea425abb64 · outbound

This paper cites Measuring massive multitask language understanding.

Understanding Layer Patching in Model Size Interpolation Measuring massive multitask language understanding

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 96cdab90-f6cf-468e-b328-f376721b2003 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

Understanding Layer Patching in Model Size Interpolation Measuring mathematical problem solving with the math dataset

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 0d3c99bc-ccd2-4db1-9db5-f38dbb6eb4da · outbound

This paper cites Rethinking layer relevance in large language models beyond cosine similarity.

Understanding Layer Patching in Model Size Interpolation Rethinking layer relevance in large language models beyond cosine similarity

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5df3f66f-e3c1-411e-a3f8-a0262a8629ef · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Understanding Layer Patching in Model Size Interpolation Distilling the Knowledge in a Neural Network

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.683139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 966089bb-212f-43c4-b41c-a9395960110d · outbound

This paper cites Training Compute-Optimal Large Language Models.

Understanding Layer Patching in Model Size Interpolation Training Compute-Optimal Large Language Models

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.712525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f87028e6-38f2-49b8-aa6c-3f5df5b83b12 · outbound

This paper cites Instruction-Following Pruning for Large Language Models.

Understanding Layer Patching in Model Size Interpolation Instruction-Following Pruning for Large Language Models

Reference 21

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T12:07:03.718737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 955e1785-d3d3-4122-b737-2a6bebb2019a · outbound

This paper cites O'Reilly Media, Inc.

Understanding Layer Patching in Model Size Interpolation O'Reilly Media, Inc

Reference 22

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation e967fbe6-0336-40d8-942c-1efeeb80220f · outbound

This paper cites Nayak, Jonathan Geuter, Marco Fumero, Francesco Locatello, and David Alvarez-Melis.

Understanding Layer Patching in Model Size Interpolation Nayak, Jonathan Geuter, Marco Fumero, Francesco Locatello, and David Alvarez-Melis

Reference 23

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verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.130712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 3a864d06-6e24-4d30-b641-ad7edff167cb · outbound

This paper cites Scaling Laws for Neural Language Models.

Understanding Layer Patching in Model Size Interpolation Scaling Laws for Neural Language Models

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.680095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 81037bef-1336-407a-a0a6-79822c3263b6 · outbound

This paper cites Nayak, Jack Merullo, Stephen Bach, Chen Sun, and Ellie Pavlick.

Understanding Layer Patching in Model Size Interpolation Nayak, Jack Merullo, Stephen Bach, Chen Sun, and Ellie Pavlick

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.128645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 71f85d1c-61c9-435e-99dd-c373e392dcda · outbound

This paper cites doi: 10.18653/v1/D17-1082.

Understanding Layer Patching in Model Size Interpolation doi: 10.18653/v1/D17-1082

Reference 26

Resolution
metadata mismatch
doi, observed 2026-07-10T12:07:03.414162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 7014a3f6-b773-4718-9339-e4472f48ca7d · outbound

This paper cites Optimal brain damage.

Understanding Layer Patching in Model Size Interpolation Optimal brain damage

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.125328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 46aeb89d-b959-4661-92ee-299d1e2954e0 · outbound

This paper cites Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models.

Understanding Layer Patching in Model Size Interpolation Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.403700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 11a21545-5c0f-46a2-b918-614ac0053b22 · outbound

This paper cites an unresolved cited work.

Understanding Layer Patching in Model Size Interpolation Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-07-10T12:07:04.168909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 90b12f9b-e33d-4cf7-b36a-003f54b7a14f · outbound

This paper cites ShortGPT: Layers in Large Language Models are More Redundant Than You Expect.

Understanding Layer Patching in Model Size Interpolation ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.709115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:f277a721647ab9d2d0ee330f11695f125280f28f52ef651fba13351e112133ec

Observation c0c83fa9-16d7-4459-97ad-9f410b59bdc7 · outbound

This paper cites Pointer sentinel mixture models.

Understanding Layer Patching in Model Size Interpolation Pointer sentinel mixture models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.167239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 910130a8-9205-4a55-a587-01cf979e16ec · outbound

This paper cites Can a suit of armor conduct electricity? a new dataset for open book question answering.

Understanding Layer Patching in Model Size Interpolation Can a suit of armor conduct electricity? a new dataset for open book question answering

Reference 32

Resolution
verified exact
doi, observed 2026-07-10T12:07:03.399735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation e43197a6-6d1e-46d7-a9d5-460d6d5cbbd0 · outbound

This paper cites Compact language models via pruning and knowledge distillation.

Understanding Layer Patching in Model Size Interpolation Compact language models via pruning and knowledge distillation

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-07-10T12:07:03.730788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:08374666bb30d21ef40600f39d876635c0691f772562752bd46a7469090194e9

Observation 7b132166-c204-4744-93b2-d2d79b2bc26c · outbound

This paper cites Uniform convergence may be unable to explain generalization in deep learning.

Understanding Layer Patching in Model Size Interpolation Uniform convergence may be unable to explain generalization in deep learning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.163433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:d0ffe06e1b2a114eefe4d8b9b7adc6340da9f4a757b66c1dc1dd7c2b3eb4d8b7

Observation c8d607ee-732a-49f1-80d1-4a60ab499cf0 · outbound

This paper cites Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin.

Understanding Layer Patching in Model Size Interpolation Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin

Reference 35

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metadata mismatch
doi, observed 2026-07-10T12:07:03.416931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:a2e213143519cad81de9df5726f39b005e5b70948a9401701e90b76eabb8fcb6

Observation 1749a420-2d00-45ca-bdac-d9112fb30bda · outbound

This paper cites Interpreting gpt: The logit lens, 2020.

Understanding Layer Patching in Model Size Interpolation Interpreting gpt: The logit lens, 2020

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.158984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:c013dd7bbce663503c685ca15a15ddc66a7d210a2ce4a5fd25fb3910affb41b6

Observation d9efb753-9221-4597-9ff3-bf79d0fc9070 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Understanding Layer Patching in Model Size Interpolation Pytorch: An imperative style, high-performance deep learning library

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.157590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:0059952370f726d1af195749413a40bcb4456bd0e9ccfbb5ab9cad88cedecf1b

Observation f467c4d1-40a4-4c87-9fbc-3761538652e1 · outbound

This paper cites Language models are unsupervised multitask learners.

Understanding Layer Patching in Model Size Interpolation Language models are unsupervised multitask learners

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.155515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:72651a956b2f3204953e55d063f0dc669156490ab42e85956f3593e3eedb4e97

Observation 7bb48c76-fe0e-448c-938d-e0971d15cf0a · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Understanding Layer Patching in Model Size Interpolation Winogrande: An adversarial winograd schema challenge at scale

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.153986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:86a74002c7dfdb046a86819fa9fe1a6fe8bb0bf3f1e644e7d472f73dd8888cfc

Observation 818d213d-fd37-4689-8ec3-c77440f943f6 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Understanding Layer Patching in Model Size Interpolation DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.733882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:6fff282a15b0f52ba2004677f0d87cca7901ee56c4d818224b6b62ba20f6b75b

Observation c9366e22-2b15-4b23-85d0-cff50a68edaf · outbound

This paper cites Model fusion via optimal transport.

Understanding Layer Patching in Model Size Interpolation Model fusion via optimal transport

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.145067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:d9a7edd601b4cb56779edd008c5e7693081dcf8e9fdd966a09b5ea0f124de2da

Observation 877f90ef-a88a-4e85-a253-d2047d6b52b8 · outbound

This paper cites LLM Pruning and Distillation in Practice: The Minitron Approach.

Understanding Layer Patching in Model Size Interpolation LLM Pruning and Distillation in Practice: The Minitron Approach

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.725405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:48a964624d3585a28626db31caf6c273c3631117ab6922490c18b680c94ffc2c

Observation 8caf3e99-830b-426d-bdcf-3042d6ce40f8 · outbound

This paper cites Zico Kolter.

Understanding Layer Patching in Model Size Interpolation Zico Kolter

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.152021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:cec2c517aabe61e499c996f364730f71d0c1504ee6b0754625a4862f7bca9f69

Observation 0c607b40-756c-42cc-886f-327b08e4421b · outbound

This paper cites The bitter lesson.

Understanding Layer Patching in Model Size Interpolation The bitter lesson

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.148406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:098017b6cf7b36a63e7d7d7fb3c6009389c0345f0c03f85554a93171ebf2c27d

Observation a602ef30-b476-4a5e-bae9-30870e69b951 · outbound

This paper cites Kimi K2.5: Visual Agentic Intelligence.

Understanding Layer Patching in Model Size Interpolation Kimi K2.5: Visual Agentic Intelligence

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.705479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:ee8959a0fe7b343e80cbe1757b0e3c21d87608c3bee33a073a529a81bc43b87e

Observation 01e7f9c9-dd72-4663-8c18-dcb88f716180 · outbound

This paper cites Qwen3.5: Accelerating productivity with native multimodal agents, February 2026.

Understanding Layer Patching in Model Size Interpolation Qwen3.5: Accelerating productivity with native multimodal agents, February 2026

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.134828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:800403d5330b30788e735faec8f553a3ddfa7981cac90b1b82d81b0d3d017992

Observation 56f614f1-a074-4f79-a4f5-97883e2dea78 · outbound

This paper cites an unresolved cited work.

Understanding Layer Patching in Model Size Interpolation Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-07-10T12:07:04.132064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:0d0ba934f0217df36c267fdac6d73e714aede79d2dd2144ec11e1346bce4abc8

Observation 42051977-8d06-48b6-808a-b3dcbc7f7dc0 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Understanding Layer Patching in Model Size Interpolation HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.695725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:c559973d2e6716c100ae9849615c82d7624bc97caf1ae71316f52f2f3936d736

Observation 02afb929-8c0b-43ed-86a9-c2fa3849fb7d · outbound

This paper cites Sheared llama: Accelerating language model pre-training via structured pruning.

Understanding Layer Patching in Model Size Interpolation Sheared llama: Accelerating language model pre-training via structured pruning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T12:07:04.127141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:1c26d2a6484ba80a4574080473f63e6e827d1dc594c9e770151e83aaa7c4dcb2

Observation b494bd0b-3967-4ac7-8abc-bad887e620f5 · outbound

This paper cites Qwen3 Technical Report.

Understanding Layer Patching in Model Size Interpolation Qwen3 Technical Report

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.702530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:05bd1e5e409d46f4e29e6335bc4841e991ae49b7ca238f521e957988b4233649

Observation 47529697-8b99-448c-92ac-cc6fe713462d · outbound

This paper cites Model merging in llms, mllms, and beyond: Methods, theories, applications, and opportunities.

Understanding Layer Patching in Model Size Interpolation Model merging in llms, mllms, and beyond: Methods, theories, applications, and opportunities

Reference 51

Resolution
verified exact
doi, observed 2026-07-10T12:07:03.411619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:579a24512cb05fba9846ec2f3dd369f1ac518ecca63c1ebeee6b1726b4f8a428

Observation f7c222e6-126e-4317-baa8-203ead158e93 · outbound

This paper cites URL https:// doi.org/10.18653/v1/p19-1472.

Understanding Layer Patching in Model Size Interpolation URL https:// doi.org/10.18653/v1/p19-1472

Reference 52

Resolution
verified exact
doi, observed 2026-07-10T12:07:03.408743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:a92b405716e55c95c700da640913d3894fed76d9cdee31284fe369fdf5216eac

Observation 3dc41cbf-6610-45b7-9cf8-fa08de4600f8 · outbound

This paper cites FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models.

Understanding Layer Patching in Model Size Interpolation FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.686574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:f59d5034f55f02286492b803a5b6b21263a96b56a28a23f6862ac652bc2af9dd

Observation 64a621ed-3d37-416d-bcdf-d08d691fb35c · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Understanding Layer Patching in Model Size Interpolation Instruction-Following Evaluation for Large Language Models

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:07:03.675069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-10T11:57:18.311409Z digest=sha256:9abaa7881296cc289637c3f5086491582e0cb7316ef8b5f62690cf995d5b5123

Pith citing papers

No inbound Pith citation observations are available.