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Paper Citation Record · LEDGER

Teach Old SAEs New Domain Tricks with Boosting

As of 8 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2507.12990.

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

pith.paper-citation-record.v1
2507.12990 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:40:29.681728Z

measured 13 of 13 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T08:14:58.183289Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T08:16:16.162543Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d60d8f4-3f94-4fa9-b990-187622944869 · outbound

This paper cites Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders.

Teach Old SAEs New Domain Tricks with Boosting Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:28.821951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:28.821951Z digest=sha256:043323d8b6b140d11f923443b9a01f95a52db915a05280f3c5e6937288857549

Observation 20a638ac-b106-4a4f-899e-fef1eeb8d33a · outbound

This paper cites Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models.

Teach Old SAEs New Domain Tricks with Boosting Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:29.147549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:29.147549Z digest=sha256:4be37c18feaea4cea9fa76094688ed1b68f6f12683c919bd23126a67c1541c3f

Observation 1fa2e4f4-ff2f-4a37-8432-6e53d00249bd · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

Teach Old SAEs New Domain Tricks with Boosting The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:29.406481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:29.406481Z digest=sha256:5cea9c8c465935ff644492c57c891f9670b3c47e146d2843d3667a123c8c04e1

Observation 372e9581-3871-442d-b829-883b65882908 · outbound

This paper cites The Llama 3 Herd of Models.

Teach Old SAEs New Domain Tricks with Boosting The Llama 3 Herd of Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:29.517427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:29.517427Z digest=sha256:1c6d60791ee08c6bdef1a947150911e4eb5c7a9abac8304a9cf4a4001573690e

Observation 089f207b-d345-4593-bddc-eebe0bd4b1a4 · outbound

This paper cites Qwen2.5 Technical Report.

Teach Old SAEs New Domain Tricks with Boosting Qwen2.5 Technical Report

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:29.601108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:29.601108Z digest=sha256:d2994e5fe799e0301d0402fcb16c37ee83cf1c745e20e7390d918132ea91cb83

Observation a0f9b6f5-2760-42fe-8ec5-240c67a7547e · outbound

This paper cites an unresolved cited work.

Teach Old SAEs New Domain Tricks with Boosting Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:40:30.159519Z

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=2026-08-06T16:40:29.654256Z digest=sha256:2a0239aef69051e7eefaec85f6f4871353f17f7d5fce18e53dc27882f7d8d16b

Observation eb9580bd-d1d6-4acd-8d07-e1ea1f0c7fd6 · outbound

This paper cites an unresolved cited work.

Teach Old SAEs New Domain Tricks with Boosting Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:40:30.076624Z

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=2026-08-06T16:40:29.681728Z digest=sha256:17a6fbb2bebc4dbd67b5c063f99fa28950a5714f1f7678071b12f5495ed89e88

Observation cc944e05-a04d-4239-905f-0ffb17c18ff6 · outbound

This paper cites Automatically Interpreting Millions of Features in Large Language Models.

Teach Old SAEs New Domain Tricks with Boosting Automatically Interpreting Millions of Features in Large Language Models

Reference 1997

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:29.278577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:29.278577Z digest=sha256:c47f7b41b54abdad99d0cf8364851fe07c33757d654c184a69c18fa08e764511

Observation 6529e8df-4036-4420-b4b5-9d44a9550412 · outbound

This paper cites Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset.

Teach Old SAEs New Domain Tricks with Boosting Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:28.933519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:28.933519Z digest=sha256:d131a54e7ceda097bd352631590b26bd5c4b47ee0aab5d1f4d862d2a64599ab3

Observation 5a162d6b-bec4-437f-8c9e-301b39106c74 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Teach Old SAEs New Domain Tricks with Boosting Scaling and evaluating sparse autoencoders

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:28.648847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:28.648847Z digest=sha256:6e9999f71fa3a49eaae7323296bd1c99e65b006b4039e4b8dca77055d7288b71

Observation 503c8aa7-78ce-41e5-a7a7-b42dcd033de9 · outbound

This paper cites BatchTopK Sparse Autoencoders.

Teach Old SAEs New Domain Tricks with Boosting BatchTopK Sparse Autoencoders

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:28.594279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:28.594279Z digest=sha256:d53760f4074423b6b85a6d123813a75f959f87389ac9945bf32dd4dcfb09a37c

Observation 158f39e2-2786-4adc-92dc-0e2a90c0ce6f · outbound

This paper cites Sparse Autoencoders Do Not Find Canonical Units of Analysis.

Teach Old SAEs New Domain Tricks with Boosting Sparse Autoencoders Do Not Find Canonical Units of Analysis

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:29.030274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:29.030274Z digest=sha256:fcc54df1add1a2af33bcba1c9604fe53975c7730a11244dbf8701141e85ebfc1

Pith citing papers

Observation b02d0ced-ac05-4f59-8e64-7569f76f6183 · inbound

Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift cites this paper.

Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift Teach Old SAEs New Domain Tricks with Boosting

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:16:16.165688Z

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=2026-05-22T08:14:58.183289Z digest=sha256:3bf357e37063234729e13dd213e1e9ad1fb4af7d717410a8d6413a053e58d688