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Paper Citation Record · LEDGER

Resa: Transparent Reasoning Models via SAEs

As of 8 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 2026-08-08T06:32:00.761636+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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:45:42.688318Z digest=sha256:461dfa22941dcd68dac736d33e6b7e9f64b8c5a0ad883f5e0819297c509a0273

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=sha256:777686bc5a83c4470ebcb5337a8bd4c95be5f9dbd3b1f166d2994121fc5a6a9d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:45:42.694548Z digest=sha256:1795eea25c16c5d9d3b9c7c81c41e9868bed26784a097113b0199af12c8dfbc3

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=sha256:05413bd0eb592cc3f71835a7b05ec371f680b51d8efea6d77d3bc4fb50da9d02

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=sha256:856685327d504e86c070ec68472488095321f2a8a53fe8352a86456fddee426d

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=sha256:837eb32b870f4619fba1a63d4db167f383654e854a3c953a727ba3ed4fde095e

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:f03bf5bd2c8ae761c175195a16ed418ca2485a4adca8c67481e2a8d1549482b3

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=sha256:98928ebcf4e64d5215cfd15cec455c43f59f61fa6b901fc0084449155076d882

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:b17b40400a45b9b1bab731c1b9e442cd47edbf27b7b1a69cc7281b971fd376d3

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:cf76fe8416cf1740f39b735e4082e614bfa4e773517cdaa776b55ea025aaa4d0

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=sha256:782b63c53143d898cd0d640c7d41313367849374f6465b8414855cc2b945c392

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:c9e8bd8bed1523432ebd35ba443cf8a780786a8775cc19e2e77ac5eddc1d97f6

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:beecc9e2e3badb97a2524e7389cd1107f4fd6edac11cbd4882ab9cfbe5d8bff3

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=sha256:71bb63865b7986fa3ff0dede1a51064d49697b8b08d8993fa32688bff431ec7f

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=sha256:5c04ed0c46f3a6d4c3e52a01189758111e61e145562d1d8eb756b6a9e368cca2

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:b02ce1534131d9d2d5e9df6e929925e56b95afa14a55803a6a663b359943ac5a

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:c4653844dab3c71c28c1e4791b4ba6c4b0db790944a69e6820e3ce0f6f6aa79d

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=sha256:120cc3b1e1ae9604cddd3188b262ae6cd607f4a668f0b7aeef9aecf568db945a

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=sha256:581fe13286d17cab6c0c68a9fae8ad518eaf4e9f704bdc622a10c0aa11560b0f

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=sha256:67ca3094a222a3ef48003178a02fe03b5771a887ac691c2604e2abfc529c13b5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:45:42.751939Z digest=sha256:f763ecf3a9f8f10ca2c8334533627406c2ec3e4f7782814f2d945c1155e7b4e7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:45:42.754759Z digest=sha256:ecf6a8803292b4551263c9b54469bc52a20cbff65e40417a4b4926242d179e1c

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

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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:ca3a3ecb87fc63ade242efef274bece1ee50e873c0b2134ef1dc6dcd2d2a8dbe

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:45:42.760281Z digest=sha256:f6d375ad53818c5fefb92c98c851a0cca0c5e75a0bd837247db8e815edd4095d

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=sha256:05f7510e2b5323e637b876a495227dbca91f3cfb3aa80aaf01cab219c1fc7c91

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:c0aea872b21bdcbb2c992ebb5e07c63f074a9be499d1ab16b029cc6492f88ce9

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:c3ef5f69fa89dc1f354c8c55d10bfd9d89a685951b610acdb016c959e9ec2546

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:cdc37ed83b6d3e03b34b6f5673b05dc5500446d1c03de6ea7c2aedc59847ad5f

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:adae1d524ce905af7c9c112bfaab5a2e7062bdacc7d628d9ec0a3726ff80c35d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T10:33:02.741857Z digest=sha256:80f652ecba5d258db49a4349a99607da41e85271cd8edf989985fb1b1780da83

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T01:10:54.313745Z digest=sha256:336f3d94a1f84f1774f3e18e2b0f6acf5d0b4c7e8851c65c3756a4d8df9b2a6d

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:eaabce88bcf6ebbbb6cc484f0565d2808d16a05d739bdbd962efcf0bb32c2a99