Pith. sign in

Paper Citation Record · LEDGER

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2507.22918.

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

pith.paper-citation-record.v1
2507.22918 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:39:46.571381Z

measured 30 of 30 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 2026-05-13T06:47:07.137898Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T06:47:25.958696Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact1
  • verified fuzzy5
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 519a4dc5-4849-4ad0-b089-a2c5e0d7bb25 · outbound

This paper cites Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:45.518899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:45.518899Z digest=sha256:f4efea374a3689b4a7b80ca4e70ad997cd100d9c0ea6f024a6042d229436aad5

Observation cd93610f-7be7-4859-9c60-595a4c1a90be · outbound

This paper cites Transformer Circuits Thread.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Transformer Circuits Thread

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:39:47.256031Z

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=2026-08-06T15:39:45.621142Z digest=sha256:73b63833f600326079d3763cbb6e7dd35b1fa05c3b098b95b1e803d02b43ea9a

Observation 43820409-d75e-4925-a2c6-6d2b99bc5ad4 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:45.714033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:45.714033Z digest=sha256:a6ef8c7e6f409dc2914e25725beda3e4b8045dbf7d7e5f87b0aa04baf07f2c6e

Observation 03dec02c-a210-4043-8cf9-d62be9252d95 · outbound

This paper cites A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:45.801972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:45.801972Z digest=sha256:facdc41f513e76170a5b80d20dae88b704ccf33725275b15af9c3f8822722f8e

Observation 6318063c-be19-46fc-9959-9f3c2cecb34a · outbound

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

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:45.924745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:45.924745Z digest=sha256:eb09b5bf2395a2090d776d59254f2ead43a4e891309ffe34773c5bcd3aa26154

Observation 26a5ca13-d50c-4b83-a3e9-4b51b7b60be1 · outbound

This paper cites Neuron to Graph: Interpreting Language Model Neurons at Scale.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Neuron to Graph: Interpreting Language Model Neurons at Scale

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.120420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.120420Z digest=sha256:f2f58c118590a8fa8815a9d1c02ebab09eb1518aaa67c75441e4b300d0c51d32

Observation 0e4885d2-fdcb-4987-8f36-dd4c8378d02f · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Scaling and evaluating sparse autoencoders

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.172788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.172788Z digest=sha256:7e8226a3f7d03ccd9e8c8a1be260a34a3f09128bccb77f59f10f551d2afe596a

Observation 16b17915-0570-48ca-8000-cde092dacb01 · outbound

This paper cites DeepDecipher: Accessing and Investigating Neuron Activation in Large Language Models.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs DeepDecipher: Accessing and Investigating Neuron Activation in Large Language Models

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T15:39:46.965951Z

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=2026-08-06T15:39:46.218173Z digest=sha256:a2e859c9209e9cb9cf48806ea4867ceab306984f6ffe5acc0cd053810daa87cf

Observation 6229ad92-6641-4214-916c-9e71a7a6f4b5 · outbound

This paper cites Alignment faking in large language models.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Alignment faking in large language models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.252176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.252176Z digest=sha256:145505f1f60cbbcf6a6d752c28864d742f023de37cab92de03576e5918514e16

Observation bde823d1-976e-4335-9347-83bace931b12 · outbound

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

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.295668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.295668Z digest=sha256:e0abb16e3d3f7eb402591a3316217befb242f2240f7269ab152cfb4861091d92

Observation 71362254-d1cc-48e2-a11f-600e6a887661 · outbound

This paper cites Universal Neurons in GPT2 Language Models.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Universal Neurons in GPT2 Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.392267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.392267Z digest=sha256:bb39b2d47c724f3aaac967d070d0efb4f1157cf24d0162261463f538897b5a69

Observation bb4cf9d2-c742-4c63-9f55-d3d7174abce0 · outbound

This paper cites An Overview of Catastrophic AI Risks.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs An Overview of Catastrophic AI Risks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.506017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.506017Z digest=sha256:8767ad7d55a2aa12f8b19f8eaa69bf6ae9905a3d9567724280387fdea20cf2f2

Observation f48e4e38-2911-4f02-8a10-83c98296c2ac · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.520999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.520999Z digest=sha256:2d6c94e6be5d759549f263955300c291396330c650d158840f7326883c5c28e3

Observation ce8e6707-d6f6-424d-b6b4-2f8ffd3aea0e · outbound

This paper cites Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.530487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.530487Z digest=sha256:2eb928a8be21e0c52d617572c5323d73d7d7499a4e14a95e0f87a439c8514c55

Observation 26ff7608-7f24-4571-8253-dcddd6dc44c5 · outbound

This paper cites Accessed: 2024-06-19.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Accessed: 2024-06-19

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:39:47.226022Z

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=2026-08-06T15:39:46.539381Z digest=sha256:861bd5a854cf15106da2caa8c3892e6e486aa433727214895e558832b897d382

Observation b86a2244-c5df-4e12-bc22-fbe0aadbd572 · outbound

This paper cites Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.553247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.553247Z digest=sha256:7a0b5a3ede27d91e7bf72ee460fcbf7a4f16ec623776332e000dab06f3a61741

Observation b77f2410-9fa2-44a9-b224-f08a1f5f2797 · outbound

This paper cites Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth´ee Lacroix, Baptiste Rozi `ere, Naman Goyal, Eric Hambro, Faisal Azhar, et al.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth´ee Lacroix, Baptiste Rozi `ere, Naman Goyal, Eric Hambro, Faisal Azhar, et al

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:39:47.196891Z

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=2026-08-06T15:39:46.558012Z digest=sha256:27a997c12b9754d195d9472954c32b3f9882ac2a8839243a71d2aadad31b0581

Observation c4444684-b3da-4049-af49-bd14b0852441 · outbound

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

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs LLaMA: Open and Efficient Foundation Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.562349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.562349Z digest=sha256:0c64cebe9bef1535f82d0de3786ae82bac2ec46c01393e24dcc3e6d0863bce45

Observation 0200a562-5331-4b94-b02d-47c6bea20251 · outbound

This paper cites Well-Read Students Learn Better: On the Importance of Pre-training Compact Models.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.566529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.566529Z digest=sha256:72b967fe5c4cee24a117cd7bdf4e2549ae6490d0a3ec04abf144142be97a08bd

Observation 4574d300-80e0-42c7-9296-67bd450788d5 · outbound

This paper cites arXiv preprint arXiv:2412.07334.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs arXiv preprint arXiv:2412.07334

Reference 29

Resolution
verified exact
raw_fallback, observed 2026-08-06T15:39:46.753131Z

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=2026-08-06T15:39:46.571381Z digest=sha256:4000446c7852830e4cd9e40b4a8c00163cf88a47f3dbbb2b6d208c5a14276501

Observation 5e03abfa-1643-43ec-8359-e9f1a3bcc7ff · outbound

This paper cites https://wordnet.princeton.edu/.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs https://wordnet.princeton.edu/

Reference 2010

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:39:47.272118Z

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=2026-08-06T15:39:45.288412Z digest=sha256:05ecee5ece3938785774bc669756506a12e1c8bc2696849dd07e70911c75f96f

Observation f5696380-c4bd-4190-9974-7b2725ae119a · outbound

This paper cites k-Sparse Autoencoders.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs k-Sparse Autoencoders

Reference 2013

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.535005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.535005Z digest=sha256:e4f80ff4c0cc02eb8941a89e0b0912b89b3de26a90e6cd1a117f4ce3d0f0a5ae

Observation aa4d13ad-775b-45d4-a6eb-1019336bf602 · outbound

This paper cites Improving Dictionary Learning with Gated Sparse Autoencoders.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Improving Dictionary Learning with Gated Sparse Autoencoders

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.548154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.548154Z digest=sha256:9ec1d2cb8309c78965733ca7116e5efd99f3b923022ab00ed9e3a875dab7961d

Observation a9aeb7bd-7da7-47ad-bf26-8ea979265d27 · outbound

This paper cites Similarity of Neural Network Representations Revisited.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Similarity of Neural Network Representations Revisited

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.525881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.525881Z digest=sha256:dd1c05ac7d7a847405883bbe70e247e04ab66dec3fe953f5638874d2bf991d5e

Observation 878a8acf-c869-49bf-8ef6-96822e2173b0 · outbound

This paper cites an unresolved cited work.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Unresolved cited work

Reference 2020

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:39:47.211331Z

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=2026-08-06T15:39:46.543606Z digest=sha256:338f91ac25b3e5397924e44842478b7861c20dd5dfbf32e4a91807941f25e1f5

Observation 23c0403c-c302-4fbf-9f78-06acf33d606e · outbound

This paper cites Transformer Circuits Thread.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Transformer Circuits Thread

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:39:47.241196Z

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=2026-08-06T15:39:45.991495Z digest=sha256:5b7f602e039e8b6bc10c83d22ef36c70491260c3116863f6e656f76bf58ee061

Observation 92181f9f-cc1c-481f-8324-0ae22ab7d363 · outbound

This paper cites GPT-4 Technical Report.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs GPT-4 Technical Report

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:45.331713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:45.331713Z digest=sha256:8f0dd71c8ab5066d7119c8772f9afbee124bf68e327c1e175c2f2f9a26c6cdb6

Observation d47b395c-0bae-473b-b953-c562d884cba6 · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs Mechanistic Interpretability for AI Safety -- A Review

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:45.419354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:45.419354Z digest=sha256:677d9e2e9beb29172840cb5629257eaddb3710b8770b36373d73f313c71b7039

Observation c831320b-ceba-4aee-88d6-d1686b8b42c9 · outbound

This paper cites arXiv preprint arXiv:2504.18530.

Semantic Convergence: Investigating Shared Representations Across Scaled LLMs arXiv preprint arXiv:2504.18530

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T15:39:46.084751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:39:46.084751Z digest=sha256:9fc9e020e98ac875534254479b49a8be568d8b1203da32896a46ca3cf85d70e4

Pith citing papers

Observation 9758b934-81d8-440d-9c9f-f481295ffcc2 · inbound

Steering Without Breaking: Mechanistically Informed Interventions for Discrete Diffusion Language Models cites this paper.

Steering Without Breaking: Mechanistically Informed Interventions for Discrete Diffusion Language Models Semantic Convergence: Investigating Shared Representations Across Scaled LLMs

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:47:25.962745Z

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=2026-05-13T06:47:07.137898Z digest=sha256:2734b9ad4471a029674e65ec65c6df88063738c1d50095977734f437752ea789