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Paper Citation Record · LEDGER

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.24645.

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

pith.paper-citation-record.v1
2607.24645 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T09:20:47.845917Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

45 of 45 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6c65391e-f91d-41b2-a20f-78766fa26f85 · outbound

This paper cites Journal of Machine Learning Research , year =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Journal of Machine Learning Research , year =

Reference 1

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source=arxiv_source observed=2026-07-31T09:20:46.993566Z digest=sha256:74623611dc0c14cb2e944dc782c398b7e4c2b856192de63f4354667ca8ac8d3b

Observation ea906b2e-24c3-4d22-aa45-22757ce15218 · outbound

This paper cites Do Sparse Autoencoders Capture Concept Manifolds?.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Do Sparse Autoencoders Capture Concept Manifolds?

Reference 2

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source=arxiv_source observed=2026-07-31T09:20:47.008532Z digest=sha256:ebdf66d8fa595dd1fb1a5d7b8c54e7eb3d93daf162bb18cf7b7299318e918c14

Observation 254b586c-279b-46d1-822c-8ee4cba64308 · outbound

This paper cites Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small

Reference 3

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source=arxiv_source observed=2026-07-31T09:20:47.034743Z digest=sha256:7654241084dd21ebf20de9529675ec21d5364a54c98795268b880a83aa8755b9

Observation 27da44f8-9f0c-4982-b77f-84328e813376 · outbound

This paper cites Finding Belief Geometries with Sparse Autoencoders.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Finding Belief Geometries with Sparse Autoencoders

Reference 4

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local_arxiv, observed 2026-07-31T09:21:24.466794Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-31T09:20:47.045872Z digest=sha256:1f3ca05263b06e51f3bf735956e13c914755f14bb6bf0d0bc9aebb0d37c06b26

Observation 52e08275-dffb-49e4-925e-ff004edb4139 · outbound

This paper cites Manning and Christopher Potts , editor =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Manning and Christopher Potts , editor =

Reference 5

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source=arxiv_source observed=2026-07-31T09:20:47.094747Z digest=sha256:81e749d9c0eb7fdf4403e32efb5594d53d8d3cf847fdac8d6800bc1b882a7670

Observation 011314fa-3a07-4982-a59e-238ec2e9f81f · outbound

This paper cites Galichin and Alexey Dontsov and Oleg Rogov and Ivan V.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Galichin and Alexey Dontsov and Oleg Rogov and Ivan V

Reference 6

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source=arxiv_source observed=2026-07-31T09:20:47.141888Z digest=sha256:2de7dfcea634fd2462981df277048470964578fa3b5acf84b976bd10c3d67582

Observation 1c1e5277-6362-4f94-9208-30af129195e6 · outbound

This paper cites Li and Suraj Srinivas and Usha Bhalla and Himabindu Lakkaraju , editor =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Li and Suraj Srinivas and Usha Bhalla and Himabindu Lakkaraju , editor =

Reference 7

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doi, observed 2026-07-31T09:21:24.180960Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-31T09:20:47.164639Z digest=sha256:ffa0b63923c31abef52a4485b85ade97c667eea61a33ac26f4e607ea0bafa5ee

Observation 3230cf53-a693-475b-ac2e-8bef6cfb0f6c · outbound

This paper cites and Lubana, Ekdeep S and Fel, Thomas and Ba, Demba , booktitle =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects and Lubana, Ekdeep S and Fel, Thomas and Ba, Demba , booktitle =

Reference 8

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source=arxiv_source observed=2026-07-31T09:20:47.171174Z digest=sha256:0d3db2fcbaa91f9202c395066aa7dedf2bc6307f528a5484c6e03f92cd0527d6

Observation ba75407c-25b1-4b49-9331-8d2332f3b6b2 · outbound

This paper cites Michaud and David D.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Michaud and David D

Reference 9

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source=arxiv_source observed=2026-07-31T09:20:47.182754Z digest=sha256:8284c4284c399dd1ac5e9272d4fa8fea5eab61ad1c3ce8e5949b3e06cc934ae9

Observation efff8438-2061-4280-91c6-2b8b0f6b255b · outbound

This paper cites Transformer Circuits Thread , note=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Transformer Circuits Thread , note=

Reference 10

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source=arxiv_source observed=2026-07-31T09:20:47.189370Z digest=sha256:c8c6b1456d8a135ef9118515621d881f82b3c84f2a0aaa1d1ff1beb911e144f2

Observation 1e7d4f3e-8881-47d4-85d4-11bc67230147 · outbound

This paper cites Transformer Circuits Thread , note=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Transformer Circuits Thread , note=

Reference 11

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source=arxiv_source observed=2026-07-31T09:20:47.195972Z digest=sha256:c852b48150064c1bf687b03866a23a4ce2c9d4b5b1b6cda6fc726f6a3e834d23

Observation f8dc10b9-07ea-40d0-ad06-e4d20bdc624f · outbound

This paper cites The Twelfth International Conference on Learning Representations,.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Twelfth International Conference on Learning Representations,

Reference 12

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source=arxiv_source observed=2026-07-31T09:20:47.201745Z digest=sha256:5235289db16b9f7123c01ae2a817e7b9e4f485d4f19de51d585afaa858f3b7cd

Observation 5c3f897a-6cf1-4be4-a9e1-5857a4ce39d8 · outbound

This paper cites Daniel and Sumers, Theodore R.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Daniel and Sumers, Theodore R

Reference 13

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source=arxiv_source observed=2026-07-31T09:20:47.224745Z digest=sha256:cc2c59390f18256dea3340b3a6af7b759ff8c70158ea10cb0c26e62296844cb9

Observation ac395899-e9ac-44c5-8dbc-460e536dcc20 · outbound

This paper cites 2024 , url =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2024 , url =

Reference 14

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source=arxiv_source observed=2026-07-31T09:20:47.274747Z digest=sha256:9effb703fa1eaa9d0d124a9b3fae9bdc5761a07f80adb8a843bece75ba2bbb89

Observation 3e31cfd2-c02e-4d7b-b48a-1394ae58444f · outbound

This paper cites 2025 , url =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2025 , url =

Reference 15

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source=arxiv_source observed=2026-07-31T09:20:47.290827Z digest=sha256:9a1ef79e1a7e59c45f137da83da7c642d07b3ee5fcee0c08e3eddb4a08f4cba2

Observation 4773625a-2c48-4fd8-a0c5-5210754bb588 · outbound

This paper cites Eliciting Latent Predictions from Transformers with the Tuned Lens.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Eliciting Latent Predictions from Transformers with the Tuned Lens

Reference 16

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source=arxiv_source observed=2026-07-31T09:20:47.304749Z digest=sha256:b11073435d3239c2dd795d976da64860e8afb9977a5bf3a132816188b4785b12

Observation f947d50e-c2b7-4055-8e2d-ca1137520cf7 · outbound

This paper cites CoRR , volume =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects CoRR , volume =

Reference 17

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source=arxiv_source observed=2026-07-31T09:20:47.354749Z digest=sha256:8354317391e4eef57de6350bba9da5553cfc387a55192a6b5e71778a891cbf73

Observation 55143e60-7c8b-46ca-8725-97ec0ee70f03 · outbound

This paper cites The Thirty-eighth Annual Conference on Neural Information Processing Systems , year=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Thirty-eighth Annual Conference on Neural Information Processing Systems , year=

Reference 18

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source=arxiv_source observed=2026-07-31T09:20:47.404749Z digest=sha256:d2606151cecea3d8e0e3372a019683f70e7d5a5b5e0abd0a01ce3f364436c53f

Observation efd691aa-7496-47e5-be50-cac9d31a390d · outbound

This paper cites 2025 , url=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2025 , url=

Reference 19

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source=arxiv_source observed=2026-07-31T09:20:47.463908Z digest=sha256:2a0a280aa1d994f6b2f027fe2fe660123695d5781f0614445e4d3f3e8ff9c7b8

Observation 7da03c32-1afd-4cf4-b1d7-13db761c5ec5 · outbound

This paper cites 2024 , url=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2024 , url=

Reference 20

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source=arxiv_source observed=2026-07-31T09:20:47.501900Z digest=sha256:d1551ae5ca1e95eca109ff7b5923fca12f1eb80c551e4081749bd3720b8bef03

Observation 9560e457-04f6-468d-93ca-02e9cf9ef28d · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Reference 21

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source=arxiv_source observed=2026-07-31T09:20:47.554747Z digest=sha256:848e2e75b83a32f78998ca17ca7510d4580b3d93fbe5be227276045834f57b50

Observation ed897840-c828-469f-a7c1-2622c93c569f · outbound

This paper cites Philosophical Transactions of the Royal Society of London, Series A: Containing Papers of a Mathematical or Physical Character , number =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Philosophical Transactions of the Royal Society of London, Series A: Containing Papers of a Mathematical or Physical Character , number =

Reference 22

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source=arxiv_source observed=2026-07-31T09:20:47.568436Z digest=sha256:d0f1c900b758d2d40ba891aad4afbb8a904c93e2521ac9954dc5ed65c02e560b

Observation 8e4ec658-1bb7-4a87-a916-41c8560806c0 · outbound

This paper cites Neural Comput.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Neural Comput

Reference 23

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source=arxiv_source observed=2026-07-31T09:20:47.585923Z digest=sha256:d6dec0597ae597f82f3e0cf3da7ca2896caf12a89b41f3d3dabb3a85c0d0b119

Observation 43ee47df-e5ad-4473-8302-d11c89e7d5d6 · outbound

This paper cites 2007 , publisher=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2007 , publisher=

Reference 24

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source=arxiv_source observed=2026-07-31T09:20:47.617215Z digest=sha256:d56904b0be0cd25ae87af353cb74d0ae30875a27f8c8b135d7de28e49f423fdf

Observation 8b25c98f-a700-4a8f-b939-1829af77fcf2 · outbound

This paper cites Dhillon and Joydeep Ghosh and Suvrit Sra , title =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Dhillon and Joydeep Ghosh and Suvrit Sra , title =

Reference 25

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source=arxiv_source observed=2026-07-31T09:20:47.622112Z digest=sha256:b0240814868431b975d5352457654d132634496f70561ea98596d79e5fa75407

Observation 2cc76b98-7048-491a-99bc-075b3dda3d51 · outbound

This paper cites 1978 , publisher=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 1978 , publisher=

Reference 26

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source=arxiv_source observed=2026-07-31T09:20:47.626756Z digest=sha256:e86323b5b6379d3d743dc7ae77909ee3c52deafdb99ceb3ee11663db60f83bf8

Observation d482e5f2-9198-491e-a00a-4b1b070f3908 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Gemma 2: Improving Open Language Models at a Practical Size

Reference 27

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source=arxiv_source observed=2026-07-31T09:20:47.631310Z digest=sha256:a2bdaa43c5068d79cb201f279808eb8d7c8304a6748b99b18afeb6d71e397a90

Observation 6a418594-ace3-4227-82a2-68518288acf4 · outbound

This paper cites Open Problems in Mechanistic Interpretability , journal =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Open Problems in Mechanistic Interpretability , journal =

Reference 28

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source=arxiv_source observed=2026-07-31T09:20:47.637750Z digest=sha256:79b7071d7473031acc233699a1eb0a2449fbbbfd28f6e9f32463ac479a304637

Observation 32ac9f4a-49ca-4b98-8429-996334ff1253 · outbound

This paper cites an unresolved cited work.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-07-31T09:20:47.684746Z digest=sha256:938ada4893b4d6707995cf6a274411d3b4cea92753e38698dfec23fd0ba17e61

Observation 2dd65ac7-d348-4a62-8d9e-166c7cff89d8 · outbound

This paper cites Transformer Circuits Thread , note=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Transformer Circuits Thread , note=

Reference 30

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source=arxiv_source observed=2026-07-31T09:20:47.734748Z digest=sha256:8825417ff7d336b3c6eef5ff21c7b9095f116150a7513164a8f47ac70a80146a

Observation 65698af8-2076-4117-8b71-2c1a93df0257 · outbound

This paper cites 2023 , url=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2023 , url=

Reference 31

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source=arxiv_source observed=2026-07-31T09:20:47.765948Z digest=sha256:c5adfe0f88546a02a7051956868c9a16dab7702837155eb16301cb2a653b5315

Observation e2ecc4ea-e9d3-4e8c-b628-0ceaa7e216dd · outbound

This paper cites 2025 , url=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2025 , url=

Reference 32

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source=arxiv_source observed=2026-07-31T09:20:47.774448Z digest=sha256:d8db13d7a29f35bca8c6fa30c50e38a761823f45377b9b0a426b4062ae38d783

Observation 5068be4f-333c-482c-8de0-e040e38e4822 · outbound

This paper cites CoRR , volume =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects CoRR , volume =

Reference 33

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source=arxiv_source observed=2026-07-31T09:20:47.779872Z digest=sha256:7022504a09f9b9efab7120a0a1748079c94d3c377046056b25ac01da38ca9906

Observation f95d9cae-5bc6-408d-add2-257c6b55aac0 · outbound

This paper cites The Rate-Distortion-Polysemanticity Tradeoff in SAEs.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Rate-Distortion-Polysemanticity Tradeoff in SAEs

Reference 34

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local_arxiv, observed 2026-07-31T09:25:51.726172Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-31T09:20:47.787462Z digest=sha256:38a627e054041d23eb7f799a12c5ec11c94fa67e05a79aca96449d62f996116c

Observation b46b3438-de83-42f1-a4f0-a0a7bdce1bb3 · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Fourteenth International Conference on Learning Representations , year=

Reference 35

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source=arxiv_source observed=2026-07-31T09:20:47.795087Z digest=sha256:4e3982609b3b2b55b07c5f9fdc942b0458d48e1098b37b285699f764ac33b96c

Observation 750c85ec-9c20-4096-a189-9059a378a7ef · outbound

This paper cites The Thirteenth International Conference on Learning Representations,.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Thirteenth International Conference on Learning Representations,

Reference 36

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source=arxiv_source observed=2026-07-31T09:20:47.802535Z digest=sha256:384e90247f9f2facc9b87597ba0c412fd825690419ade439f958b427942c9c22

Observation 96c29936-d304-45a3-82d6-eb1c7bcc2a24 · outbound

This paper cites The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=

Reference 37

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Observation 23b23358-df0d-4303-aa0f-52e1324b76c5 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects The Thirteenth International Conference on Learning Representations , year=

Reference 38

Resolution
unresolved
no resolver link, observed 2026-07-31T09:20:47.811716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b4465b8c-aa28-4f5f-bda5-bc8652ede626 · outbound

This paper cites 2023 , howpublished =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2023 , howpublished =

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-31T09:20:47.816708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 21d3fd2c-482a-47bf-9b34-a88242b01f9f · outbound

This paper cites SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-31T09:20:47.823065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T09:20:47.823065Z digest=sha256:01dfd62d64744fb8fcdc47812c5c5ebeee19eb51b25aa258db098882af0ef1bc

Observation 2fe24b5b-c982-476e-9274-c4162b06650b · outbound

This paper cites Lozier , title =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Lozier , title =

Reference 41

Resolution
verified exact
doi, observed 2026-07-31T09:25:51.625759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation b2999ae5-c75b-4a71-b51c-99e4da36c70b · outbound

This paper cites Proceedings of the Eighteenth Annual.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Proceedings of the Eighteenth Annual

Reference 42

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unresolved
no resolver link, observed 2026-07-31T09:20:47.833315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 464f8add-73f7-49c8-8bc3-8021397d4b42 · outbound

This paper cites 2007 , url =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects 2007 , url =

Reference 43

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unresolved
no resolver link, observed 2026-07-31T09:20:47.837475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T09:20:47.837475Z digest=sha256:6ca8e60d8e9bb14c7f809424b1050f4dda91b57f8887c17c6e69e1f60d720194

Observation 69dbeaff-9493-4fd2-8ea4-3104baf46dcd · outbound

This paper cites Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 44

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unresolved
no resolver link, observed 2026-07-31T09:20:47.841420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation be909438-f0f9-4625-be55-6ab79077cbeb · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , pages =.

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects Proceedings of the 42nd International Conference on Machine Learning , pages =

Reference 45

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unresolved
no resolver link, observed 2026-07-31T09:20:47.845917Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.