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Paper Citation Record · LEDGER

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space

As of 16 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2608.07786.

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

pith.paper-citation-record.v1
2608.07786 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:17:43.248210Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

40 of 40 outbound references displayed

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  • verified fuzzy8
  • unresolved28
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External citation measurements

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Outbound references

Observation 191af9f6-d7a9-40a9-8679-737b00e9f69a · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Constitutional AI: Harmlessness from AI Feedback

Reference 1

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Observation b9af0d40-357f-4959-a5a8-3e8f669bff26 · outbound

This paper cites 3: independent-origin (Scenario 1), same- series (Scenario 2), and shared-base (Scenario 3).

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space 3: independent-origin (Scenario 1), same- series (Scenario 2), and shared-base (Scenario 3)

Reference 2

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 09389d7b-9ce7-4225-9f54-7f4589390743 · outbound

This paper cites We distinguish two subcategories based on fine-grained variation sources.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space We distinguish two subcategories based on fine-grained variation sources

Reference 3

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3ba5c4e5-3667-4f84-85bf-e5d93230d7e5 · outbound

This paper cites The Llama 3 Herd of Models.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space The Llama 3 Herd of Models

Reference 6

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source=pdf_text observed=2026-08-11T04:17:43.028307Z digest=sha256:c477a6520409484bca9d7073cb1ac6761e3eb7689afa87929f934a283b101465

Observation 8751b4d1-d92e-41d1-abdd-3d4635c20d02 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

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Observation d976947b-ea7c-4d61-b02e-a2f74b8430ea · outbound

This paper cites A2 summarizes the proposed Subspace Alignment algorithm.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space A2 summarizes the proposed Subspace Alignment algorithm

Reference 8

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Observation 07c007f2-54a6-49a8-be2a-9d7c49ec8dee · outbound

This paper cites Hide and Seek: Fingerprinting Large Language Models with Evolutionary Learning.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Hide and Seek: Fingerprinting Large Language Models with Evolutionary Learning

Reference 9

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source=pdf_text observed=2026-08-11T04:17:43.048657Z digest=sha256:7e4991284dd32e01b827894c02fae025f5b5719547d07aa02187743987476f70

Observation c0455ac1-17bd-4354-8688-57499095f5b9 · outbound

This paper cites The universal weight subspace hypothesis.arXiv preprint arXiv:2512.05117,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space The universal weight subspace hypothesis.arXiv preprint arXiv:2512.05117,

Reference 10

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source=pdf_text observed=2026-08-11T04:17:43.055311Z digest=sha256:aced7a31c098188b74a9f88e7f4c8d58cf51dd7766d7ddd32758c15cd27e4515

Observation 5cee4766-358d-47ad-a606-e5b045f593bb · outbound

This paper cites Principal angles between subspaces in an a-based scalar product: algorithms and perturbation estimates.SIAM Journal on Scientific Computing, 23(6):2008–2040,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Principal angles between subspaces in an a-based scalar product: algorithms and perturbation estimates.SIAM Journal on Scientific Computing, 23(6):2008–2040,

Reference 11

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 366e1189-552f-4043-8e38-d94cf9b5a073 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 13

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source=pdf_text observed=2026-08-11T04:17:43.072996Z digest=sha256:d15a5216415b23ad92f11f87ad9260a64788cd43ec8b061ef6134d96cff1aab2

Observation e992be82-1eaa-44a5-948d-51d350f67cca · outbound

This paper cites Training language models to follow instructions with human feedback.NeurIPS,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Training language models to follow instructions with human feedback.NeurIPS,

Reference 15

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3eaf8913-6617-440a-a1e7-b289cf12f89f · outbound

This paper cites Proximal Policy Optimization Algorithms.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Proximal Policy Optimization Algorithms

Reference 16

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Observation 1624a781-ca1a-431a-8b19-38091e45402e · outbound

This paper cites Sok: Large language model copyright auditing via fingerprinting.arXiv preprint arXiv:2508.19843,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Sok: Large language model copyright auditing via fingerprinting.arXiv preprint arXiv:2508.19843,

Reference 18

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Observation 86252118-3eb8-431d-9464-c86cb655fa25 · outbound

This paper cites Lora vs full fine-tuning: An illusion of equivalence.arXiv preprint arXiv:2410.21228,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Lora vs full fine-tuning: An illusion of equivalence.arXiv preprint arXiv:2410.21228,

Reference 19

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Observation 4c7944b4-5c2a-4d4a-b281-385a25df8e47 · outbound

This paper cites Idiosyncrasies in Large Language Models.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Idiosyncrasies in Large Language Models

Reference 20

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Observation 4f9d6335-3a6e-4b96-b77b-be0645ae3b6b · outbound

This paper cites Natural fingerprints of large language models.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Natural fingerprints of large language models

Reference 21

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Observation c7078f66-d676-4b8a-87d0-272b3a41e5b7 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space LLaMA: Open and Efficient Foundation Language Models

Reference 22

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Observation f7516c1d-44f6-4f93-8e3c-ab1d39e3d960 · outbound

This paper cites RAFP: Identifying LLM Lineages via Rare-Region Fingerprints.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space RAFP: Identifying LLM Lineages via Rare-Region Fingerprints

Reference 23

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Observation c742a75b-9420-4c02-bd3a-afab4e9d5466 · outbound

This paper cites Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification

Reference 24

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Observation cf0faf0e-5970-4810-bc4b-b77656ad1e62 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 25

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Observation cf80386e-e483-4b99-8a91-5c52ea2e1b95 · outbound

This paper cites Qwen3 Technical Report.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Qwen3 Technical Report

Reference 26

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source=pdf_text observed=2026-08-11T04:17:43.160889Z digest=sha256:cc973a2d2804b739d0feeb1079acbf241ccf9c2a5d1cd0b9683e4ad570331b6c

Observation ed520134-c3f9-4306-8f1d-40af0ad72324 · outbound

This paper cites A fingerprint for large language models.arXiv preprint arXiv:2407.01235,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space A fingerprint for large language models.arXiv preprint arXiv:2407.01235,

Reference 27

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source=pdf_text observed=2026-08-11T04:17:43.168798Z digest=sha256:cfeef96957df8793707bf5270b2574181896c52bcdf2c34ce118530133ee9a52

Observation 21281fa1-442c-4dfd-ba75-8bbc2f9de499 · outbound

This paper cites Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model!.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model!

Reference 28

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source=pdf_text observed=2026-08-11T04:17:43.175034Z digest=sha256:9ca4687732872fcd94cd7be5ecdb0ecb7b1342f028e7b139a24a351f552d5c5f

Observation d8cfb7dd-ff73-4d23-bf9b-fd09ce86d33f · outbound

This paper cites Awm: Accurate weight- matrix fingerprint for large language models.arXiv preprint arXiv:2510.06738,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Awm: Accurate weight- matrix fingerprint for large language models.arXiv preprint arXiv:2510.06738,

Reference 29

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T04:17:43.181035Z digest=sha256:f9ecd5670948ffdcec933b3d5b31c0f86d1648e643a22a78cca3cc89bd1ed689

Observation 7f07be93-c449-4394-a018-3455bb4ee0a4 · outbound

This paper cites Self: A robust singular value and eigenvalue approach for llm fingerprinting.arXiv preprint arXiv:2512.03620,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Self: A robust singular value and eigenvalue approach for llm fingerprinting.arXiv preprint arXiv:2512.03620,

Reference 30

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raw_fallback, observed 2026-08-11T04:17:43.714013Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f20510f4-77d5-4c60-b3cc-236aafbdf3cc · outbound

This paper cites REEF: Representation Encoding Fingerprints for Large Language Models.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space REEF: Representation Encoding Fingerprints for Large Language Models

Reference 31

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Observation 2b8f7976-0297-484e-880a-d25b38bd1177 · outbound

This paper cites Tamm: Triadapter multi-modal learning for 3d shape understanding.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Tamm: Triadapter multi-modal learning for 3d shape understanding

Reference 32

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verified exact
raw_fallback, observed 2026-08-11T04:17:43.596548Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T04:17:43.198723Z digest=sha256:ea228cbf4945b3ee8fdb0dc5454f329e38f13b27027338f438908572aba1ab1c

Observation b801753e-71a4-4d9a-8c5c-b499f39f19dc · outbound

This paper cites The path not taken: Rlvr provably learns off the principals.arXiv preprint arXiv:2511.08567,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space The path not taken: Rlvr provably learns off the principals.arXiv preprint arXiv:2511.08567,

Reference 33

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source=pdf_text observed=2026-08-11T04:17:43.203941Z digest=sha256:6b4715c494464b4fe9ab918ba36a44a2d3e3bbead2e984d068d4ef53236cfd0b

Observation 9c19463a-61a9-464d-b3f6-12941b7d7500 · outbound

This paper cites Angles between subspaces and their tangents.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Angles between subspaces and their tangents

Reference 34

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source=pdf_text observed=2026-08-11T04:17:43.209874Z digest=sha256:2e957ab99cbb0e6b947143d87eefdf5e96e14e07e897d68a31458532cc386b91

Observation 62fcf291-08fb-490b-8b2b-cd0e964c667d · outbound

This paper cites The complete set comprises 27 model pairs across diverse model families: Qwen cross-family pairs (7 pairs): • Qwen/Qwen2.5-7B vs.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space The complete set comprises 27 model pairs across diverse model families: Qwen cross-family pairs (7 pairs): • Qwen/Qwen2.5-7B vs

Reference 37

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raw_fallback, observed 2026-08-11T04:17:44.887788Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a2612305-dbfa-450e-b224-1a3acdab6fdd · outbound

This paper cites • Gradient clipping: max norm 1.0.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space • Gradient clipping: max norm 1.0

Reference 40

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raw_fallback, observed 2026-08-11T04:17:44.846766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T04:17:43.248210Z digest=sha256:80788237f4d7b71e8dbe880941b5b3954c68f416d5b429d579fb4eb72da34e14

Observation c1d3aad4-c779-4368-b89a-ecc00a242e69 · outbound

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

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Gemma: Open Models Based on Gemini Research and Technology

Reference 1980

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source=pdf_text observed=2026-08-11T04:17:43.022436Z digest=sha256:79badda1aae8fa86fe339918db41d984a4e1274ef1227cddc1b52a9fec77120d

Observation d1047bd2-f543-4555-8b5e-fdcf49286358 · outbound

This paper cites Blackbox model provenance via palimpsestic membership inference.arXiv preprint arXiv:2510.19796,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Blackbox model provenance via palimpsestic membership inference.arXiv preprint arXiv:2510.19796,

Reference 2002

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Observation f3047de3-afa7-4fbf-89d0-774d5f5038b2 · outbound

This paper cites Experiment setup is consistent with Fig.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Experiment setup is consistent with Fig

Reference 2012

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:44.928207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T04:17:43.215527Z digest=sha256:0cc46ceafd4b112f151115072e4eaa4a351a6b57db76712f32749fbec8258443

Observation 121801ab-278a-4a21-832b-760f4b6c90ab · outbound

This paper cites Forgetting to forget: Attention sink as a gateway for backdooring llm unlearning.arXiv preprint arXiv:2510.17021,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Forgetting to forget: Attention sink as a gateway for backdooring llm unlearning.arXiv preprint arXiv:2510.17021,

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:43.100292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:43.100292Z digest=sha256:7cc023841f93f1db57a5f90db401d295131ab218b3f45b347f3bbfb3fa2fd050

Observation b1c8cdb7-4964-4f33-9c65-e78969c67226 · outbound

This paper cites Black-box access is insufficient for rigorous ai audits.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Black-box access is insufficient for rigorous ai audits

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:44.991985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T04:17:43.010210Z digest=sha256:54630a7cad63d1449e563fcb4eb59fe5b3874aba748c7844ea14d41b23834404

Observation 7b17ddef-8072-4f86-84d9-8a80a469ef07 · outbound

This paper cites Detecting Stylistic Fingerprints of Large Language Models.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Detecting Stylistic Fingerprints of Large Language Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:43.004115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:43.004115Z digest=sha256:d4ba9dd8ae0d190b18fac738cc338671d4424ad71576b56f2fce8b7f86f43a48

Observation 1df5ad64-06aa-4adf-9680-3102a72e0571 · outbound

This paper cites Model provenance testing for large language models.arXiv preprint arXiv:2502.00706,.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Model provenance testing for large language models.arXiv preprint arXiv:2502.00706,

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:43.080439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:43.080439Z digest=sha256:0999fdfb77aeb69b8fe700f8b9f4f9eb0cb0b556982607e59691c493d06f40e0

Observation e8e29b1f-c4bb-45c5-af18-6f5c7121a9f3 · outbound

This paper cites RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:43.016245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:43.016245Z digest=sha256:85d3c5cee964f22e7afd91d1d328f15bc46d8663ee0e53143ec68c4204dd0e1f

Observation 30dbdda2-230d-4856-b221-79cd0d983d7a · outbound

This paper cites Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning.

Who Built This Model? Tracing LLM Lineage via Spectral Fingerprints in Weight Space Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:43.042560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:43.042560Z digest=sha256:931b81e8422dc0733b91b8b7d5ec8bfe7dfb986a7ddf16c1f44153276a1b3abb

Pith citing papers

No inbound Pith citation observations are available.