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Paper Citation Record · LEDGER

Resa: Transparent Reasoning Models via SAEs

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 3 inbound Pith citation observations for arXiv:2506.09967.

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

pith.paper-citation-record.v1
2506.09967 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:45:42.760281Z

measured 32 of 32 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T13:34:46.646854Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:26:24.053617Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved27
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da21b129-774f-4fb0-ba65-753705cbb947 · outbound

This paper cites Steering Large Language Model Activations in Sparse Spaces.

Resa: Transparent Reasoning Models via SAEs Steering Large Language Model Activations in Sparse Spaces

Reference 3

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:45:42.688318Z digest=sha256:fe216b4660a6fbeb20ab69f48d2f50638c645c09eea11634d0c0a2c430bf5caa

Observation a07c02d3-86f8-4ddc-a234-f26edc18ed46 · outbound

This paper cites Toward universal steering and monitoring of AI models.

Resa: Transparent Reasoning Models via SAEs Toward universal steering and monitoring of AI models

Reference 4

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source=pdf_text observed=2026-08-07T04:45:42.691479Z digest=sha256:dd96f6ad075ed74f4cfcf31b5aba2d005a1cb8744630fb39146dde881a9c57fe

Observation ae5cf393-4ed4-46e6-9c7a-82c4691bf7ab · outbound

This paper cites Low-Rank Adapting Models for Sparse Autoencoders.

Resa: Transparent Reasoning Models via SAEs Low-Rank Adapting Models for Sparse Autoencoders

Reference 5

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local_arxiv, observed 2026-08-07T04:45:43.042912Z

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.

source=pdf_text observed=2026-08-07T04:45:42.694548Z digest=sha256:7323505c8e740e1db3ce19eeea95fe05048e90f747502151e1ea1e0b916e4044

Observation 27bf7515-76e3-4733-ab40-c10989d45b65 · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

Resa: Transparent Reasoning Models via SAEs SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 6

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source=pdf_text observed=2026-08-07T04:45:42.697452Z digest=sha256:1e5a6576c4c2972f6d501d24d79bb3ec54abcbc0b8574d72b237da633c37ea1d

Observation f6f50ba9-ed7f-4c08-a85e-87cf96ce073b · outbound

This paper cites DeepSeek-AI.

Resa: Transparent Reasoning Models via SAEs DeepSeek-AI

Reference 8

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source=pdf_text observed=2026-08-07T04:45:42.703202Z digest=sha256:32cefa9a19dfa7142ec97e33f204f9d48d1ba3c34b4b8fa90bc36d1a26151270

Observation 2821cc5b-ea27-4f4a-aa03-ba0842b9cf3d · outbound

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

Resa: Transparent Reasoning Models via SAEs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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source=pdf_text observed=2026-08-07T04:45:42.705693Z digest=sha256:c92316d2f6233ba4bc45f974032ac90f678f53a568bc9dea599d98edcf5be29f

Observation e4e68646-ed60-4f23-a0a8-2c927f4350f9 · outbound

This paper cites Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models.

Resa: Transparent Reasoning Models via SAEs Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models

Reference 10

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source=pdf_text observed=2026-08-07T04:45:42.708353Z digest=sha256:6199b3318ebe7cbf0c8081c9310bdeac91aee0980d049db208925e00c65a5665

Observation b4211921-223d-40b6-b350-a775b8f549c7 · outbound

This paper cites OpenThoughts: Data Recipes for Reasoning Models.

Resa: Transparent Reasoning Models via SAEs OpenThoughts: Data Recipes for Reasoning Models

Reference 12

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source=pdf_text observed=2026-08-07T04:45:42.713944Z digest=sha256:fbffa278ddb4eaead0c887541801e25cbb068e05a0a2879da9d69573a1500dbc

Observation 620053fa-a4fe-44e0-a804-5c35444fc6ec · outbound

This paper cites SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability.

Resa: Transparent Reasoning Models via SAEs SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability

Reference 14

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source=pdf_text observed=2026-08-07T04:45:42.719642Z digest=sha256:fc2374e89759801d787c7b86ed07d50b282464cdada193c6771d5f3caab10e51

Observation efd70a8a-1886-4823-b9e0-b852906d5ea7 · outbound

This paper cites s1: Simple test-time scaling.

Resa: Transparent Reasoning Models via SAEs s1: Simple test-time scaling

Reference 15

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source=pdf_text observed=2026-08-07T04:45:42.722628Z digest=sha256:3cd37edcc5367c15baf7476b437859be3979c294bca1034237e5993a10502297

Observation 079557b3-ec61-4220-b289-83d8193b0886 · outbound

This paper cites Steering Language Model Refusal with Sparse Autoencoders.

Resa: Transparent Reasoning Models via SAEs Steering Language Model Refusal with Sparse Autoencoders

Reference 16

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source=pdf_text observed=2026-08-07T04:45:42.725469Z digest=sha256:abb713ae1f0f3710f8ce6f29c12ddf430d23ebe7b9fbd8b7069cc9cd8edfefdb

Observation d3eda194-da27-48d9-898b-586fd7d54d66 · outbound

This paper cites Sparse Autoencoders Enable Scalable and Reliable Circuit Identification in Language Models.

Resa: Transparent Reasoning Models via SAEs Sparse Autoencoders Enable Scalable and Reliable Circuit Identification in Language Models

Reference 17

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source=pdf_text observed=2026-08-07T04:45:42.728069Z digest=sha256:03cbb5e56c20a8a206372c99f708eced5999c129fa56a3a06b748c1a5810a311

Observation 72fef940-81d3-41fb-9e3d-bcf4d053e312 · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition.

Resa: Transparent Reasoning Models via SAEs Steering Llama 2 via Contrastive Activation Addition

Reference 18

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source=pdf_text observed=2026-08-07T04:45:42.730871Z digest=sha256:d554e80b858cb40c93cb41355cd98c1ef1f3f0e1a12096b1cf59e8eb574102d0

Observation d4fae259-1e14-4fbd-bbb9-3e9b85bc85df · outbound

This paper cites Qwen2.5 Technical Report.

Resa: Transparent Reasoning Models via SAEs Qwen2.5 Technical Report

Reference 19

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source=pdf_text observed=2026-08-07T04:45:42.733812Z digest=sha256:69e017f4990db0a645489fd98f38fc77d3296536a15199610c593bda42926745

Observation ef4a27c7-4a71-49ae-ad9a-a491d6e2b6d3 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Resa: Transparent Reasoning Models via SAEs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 20

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source=pdf_text observed=2026-08-07T04:45:42.736285Z digest=sha256:3b1bbf07df852ac092ec5961b3242f576a472c11954cfa6c7c9db89d0f588885

Observation c81686f5-7c51-41d6-8b98-efe0d11c8567 · outbound

This paper cites Tina: Tiny Reasoning Models via LoRA.

Resa: Transparent Reasoning Models via SAEs Tina: Tiny Reasoning Models via LoRA

Reference 21

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source=pdf_text observed=2026-08-07T04:45:42.738769Z digest=sha256:f35e693506cb07db6a030a92c34b66b16866a175c8699be58c704ca2714f2832

Observation 48448f35-3dc6-4cb3-b0e2-fd117fefe50a · outbound

This paper cites AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders.

Resa: Transparent Reasoning Models via SAEs AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders

Reference 22

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source=pdf_text observed=2026-08-07T04:45:42.741450Z digest=sha256:bae1adcbe34566d070e93080b031ff9023e4661188dcbf588a322c50590ee4bb

Observation fa5bc696-b96d-4d4a-a601-0664c31c8d5a · outbound

This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.

Resa: Transparent Reasoning Models via SAEs Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 23

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source=pdf_text observed=2026-08-07T04:45:42.744175Z digest=sha256:34570671a5f3ac352265fb0e23b2986081b271df45a191e5f499cae4f6c4c71d

Observation 1571120e-c6d8-4ab7-b867-36a5f3547c13 · outbound

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

Resa: Transparent Reasoning Models via SAEs Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 24

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source=pdf_text observed=2026-08-07T04:45:42.746793Z digest=sha256:adb4d03863f62475e89fe44aaedc541ddd026bfd915bf23cf8773570fc3eb8eb

Observation 7b7724ee-3cc2-4c91-8daa-3cf638a5b3d5 · outbound

This paper cites Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining.

Resa: Transparent Reasoning Models via SAEs Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining

Reference 25

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source=pdf_text observed=2026-08-07T04:45:42.749398Z digest=sha256:beffd331d90b1dee92eeeb9dad73f67ac54acd0665f00dae52da6f9497034467

Observation 08dc86f5-e57e-48ae-b701-0138da0072bd · outbound

This paper cites an unresolved cited work.

Resa: Transparent Reasoning Models via SAEs Unresolved cited work

Reference 26

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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.

source=pdf_text observed=2026-08-07T04:45:42.751939Z digest=sha256:590005b5452e42f720e5f63bd585f73ee99d6664ae3d90c98a75cf8bb6e0add7

Observation c0e45e74-9ea1-4320-a04b-674b6b3bf690 · outbound

This paper cites an unresolved cited work.

Resa: Transparent Reasoning Models via SAEs Unresolved cited work

Reference 27

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

source=pdf_text observed=2026-08-07T04:45:42.754759Z digest=sha256:10a74caf46d128a19ec5fc02d89cc0209744a9350dd84315438bb41776d5b6b8

Observation 7f9ee43f-b00a-4437-98c0-409abd2c08cc · outbound

This paper cites an unresolved cited work.

Resa: Transparent Reasoning Models via SAEs Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-07T04:45:42.757668Z digest=sha256:9c1d22659ad0e583f6ef0d20c24f0744c508809be95898a550aa439d5f2f951e

Observation 23975cb0-81b7-4c48-b19a-1f486b331383 · outbound

This paper cites an unresolved cited work.

Resa: Transparent Reasoning Models via SAEs Unresolved cited work

Reference 29

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

source=pdf_text observed=2026-08-07T04:45:42.760281Z digest=sha256:61d312c8e1d5397015a476be3a91fd5ee8af0d1c2777d7e4ac2d2ddbfaeedc8a

Observation d414bc41-689e-4392-afdf-d0f6b6415096 · outbound

This paper cites Understanding intermediate layers using linear classifier probes.

Resa: Transparent Reasoning Models via SAEs Understanding intermediate layers using linear classifier probes

Reference 2018

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source=pdf_text observed=2026-08-07T04:45:42.680950Z digest=sha256:1c7ad89e0470f02a764a5cef704bf927a975b0eede58dd00a25e04c74d801772

Observation 34e65e63-0c29-472e-b2a3-af4a74c78dd1 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Resa: Transparent Reasoning Models via SAEs Measuring Mathematical Problem Solving With the MATH Dataset

Reference 2021

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source=pdf_text observed=2026-08-07T04:45:42.716780Z digest=sha256:7d5551a4ce7533766c5b93d7cbd1acb4421099b7f7b6cf45c85bb31e9c70dc16

Observation ec43a01e-0e3f-436e-a590-8e62ab4c6a68 · outbound

This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.

Resa: Transparent Reasoning Models via SAEs Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 2023

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source=pdf_text observed=2026-08-07T04:45:42.700387Z digest=sha256:ef348485eb344dd24bb4ab9e533c9b906bd833b6ccee6fa120684a057398c62a

Observation 9b8fbf58-c38e-4115-ae25-db788752bd00 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Resa: Transparent Reasoning Models via SAEs Scaling and evaluating sparse autoencoders

Reference 2024

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source=pdf_text observed=2026-08-07T04:45:42.711316Z digest=sha256:6ed60aa5fae016a44496e4abfae94b3bb4d09228929441ae8a17df130b5ebd38

Observation c5e64d20-73d0-4162-85a7-e0e54c3e6ae9 · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

Resa: Transparent Reasoning Models via SAEs SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 2025

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source=pdf_text observed=2026-08-07T04:45:42.684968Z digest=sha256:b6d402661367a9cbce00a4e8ec344ab497240b624f18ed886bd74ed4eec63bd3

Pith citing papers

Observation dfbbe6fb-5217-415a-acad-826358219ba0 · inbound

Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning cites this paper.

Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning Resa: Transparent Reasoning Models via SAEs

Reference 25

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arxiv_id, observed 2026-05-11T20:01:09.725817Z

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.

source=pdf_text observed=2026-05-08T10:33:02.741857Z digest=sha256:7a56d294468d951510895de0fa358a7cf3bd29ba3ec6b911298f41d49b9c5af6

Observation 0214df2d-e589-4baf-8ff5-71806869d2fa · inbound

Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning cites this paper.

Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning Resa: Transparent Reasoning Models via SAEs

Reference 25

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arxiv_id, observed 2026-05-12T08:26:24.056069Z

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.

source=pdf_text observed=2026-05-12T01:10:54.313745Z digest=sha256:e351b7231dcf53b4cc655fe6f315f90df2bdf545a178e1d970538640b9deddb1

Observation 79dea46d-109d-4c74-8551-c5c9b1f020fe · inbound

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning cites this paper.

From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning Resa: Transparent Reasoning Models via SAEs

Reference 4

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source=pdf_text observed=2026-07-12T13:34:46.646854Z digest=sha256:6aaabc0d075ab4802903e9c217bbdeff247deb0998972dd938de7c4da24ddb09