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Paper Citation Record · LEDGER

Multimodal Model Diffing for Feature Discovery and Control

As of 11 August 2026, this Paper Citation Record lists 99 of 99 outbound references and 0 inbound Pith citation observations for arXiv:2608.09928.

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

pith.paper-citation-record.v1
2608.09928 v1

Coverage vector

measured 99 of 99 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:17:56.224644Z

measured 99 of 99 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

99 of 99 outbound references displayed

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  • verified fuzzy22
  • unresolved74
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

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Outbound references

Observation 63a68806-aeda-41aa-8974-f329e2ebba67 · outbound

This paper cites Pixtral 12b: A new frontier in image and text understanding.

Multimodal Model Diffing for Feature Discovery and Control Pixtral 12b: A new frontier in image and text understanding

Reference 1

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Observation e980897a-63ad-4ab4-9cae-ab1bace9e2e9 · outbound

This paper cites Golden gate Claude.

Multimodal Model Diffing for Feature Discovery and Control Golden gate Claude

Reference 2

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Observation b478f42b-d307-42c5-b16b-5954735aa5a1 · outbound

This paper cites SAE on activation differences.

Multimodal Model Diffing for Feature Discovery and Control SAE on activation differences

Reference 3

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Observation eed6e3f5-9874-4c87-b480-11f0d9fdb4ad · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

Multimodal Model Diffing for Feature Discovery and Control Refusal in Language Models Is Mediated by a Single Direction

Reference 4

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Observation 15f9a23f-fb05-4140-b13b-89fcd2bd4712 · outbound

This paper cites Revisiting model stitching to compare neural representations.Advances in neural information processing systems, 34:225–236, 2021.

Multimodal Model Diffing for Feature Discovery and Control Revisiting model stitching to compare neural representations.Advances in neural information processing systems, 34:225–236, 2021

Reference 5

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Observation 99bad67a-8f11-4798-a8d3-1e4ee9868bcc · outbound

This paper cites Representation Topology Divergence: A Method for Comparing Neural Network Representations.

Multimodal Model Diffing for Feature Discovery and Control Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 6

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source=pdf_text observed=2026-08-11T04:17:55.758852Z digest=sha256:2c56a5161fae7f4816621b08d3b6c0f6cb210495937866f168d8c321064046de

Observation fb3300c3-6ac8-4870-bef9-0d7a1e819f96 · outbound

This paper cites Understanding information storage and transfer in multi-modal large language models.Advances in Neural Information Processing Systems, 37:7400–7426, 2024.

Multimodal Model Diffing for Feature Discovery and Control Understanding information storage and transfer in multi-modal large language models.Advances in Neural Information Processing Systems, 37:7400–7426, 2024

Reference 7

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source=pdf_text observed=2026-08-11T04:17:55.764254Z digest=sha256:f7376c0eb3b2573a85c84f37d48719a5915a9299e2f4753b78fc744cd8eaac0f

Observation 775b35d7-5787-42c1-b28c-727175dec30e · outbound

This paper cites Towards monosemanticity: Decomposing language models with dictionary learning.Transformer Circuits Thread, 2023.

Multimodal Model Diffing for Feature Discovery and Control Towards monosemanticity: Decomposing language models with dictionary learning.Transformer Circuits Thread, 2023

Reference 8

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Observation bfb2af8f-ac38-41fa-a848-228a761cca3a · outbound

This paper cites Stage-wise model diffing.

Multimodal Model Diffing for Feature Discovery and Control Stage-wise model diffing

Reference 9

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source=pdf_text observed=2026-08-11T04:17:55.773486Z digest=sha256:b785b9a7904ef8d5a5a20226ed13c9a99463f8d19a16f6880bc4f159cff5d287

Observation 96afae2d-fab5-435d-bf48-229175c2211e · outbound

This paper cites Observing and controlling features in vision-language-action models.arXiv preprint arXiv:2603.05487, 2026.

Multimodal Model Diffing for Feature Discovery and Control Observing and controlling features in vision-language-action models.arXiv preprint arXiv:2603.05487, 2026

Reference 10

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Observation bae5706b-c4c3-4713-829f-3cfd8479df19 · outbound

This paper cites Improving Steering Vectors by Targeting Sparse Autoencoder Features.

Multimodal Model Diffing for Feature Discovery and Control Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 11

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Observation 21aef9b8-39d4-4a4a-bb5e-514a373a0a0d · outbound

This paper cites Pappas, Florian Tramer, Hamed Hassani, and Eric Wong.

Multimodal Model Diffing for Feature Discovery and Control Pappas, Florian Tramer, Hamed Hassani, and Eric Wong

Reference 12

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Observation 943068ae-9db0-4d97-a492-eea47ed36f53 · outbound

This paper cites Interpreting and Controlling Vision Foundation Models via Text Explanations.

Multimodal Model Diffing for Feature Discovery and Control Interpreting and Controlling Vision Foundation Models via Text Explanations

Reference 13

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Observation 729e283c-fe58-406d-a371-03d8e94288e4 · outbound

This paper cites LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction Tuning.

Multimodal Model Diffing for Feature Discovery and Control LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction Tuning

Reference 14

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source=pdf_text observed=2026-08-11T04:17:55.798668Z digest=sha256:a06f151437fd1fc8d972f7904c35e6a67afebfc91bc27f72116ad63624cbf16c

Observation 47c9ed4e-1705-4432-9bf6-b809e4061e02 · outbound

This paper cites Explaining How Visual, Textual and Multimodal Encoders Share Concepts.

Multimodal Model Diffing for Feature Discovery and Control Explaining How Visual, Textual and Multimodal Encoders Share Concepts

Reference 15

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source=pdf_text observed=2026-08-11T04:17:55.803988Z digest=sha256:c03dcfc71ef4897cdd9bc9b338a9ad48786a17c6306d1d0b31e6d7f8753e880b

Observation 9ea49434-9b1f-4ea9-b45e-0b22dc3bbf00 · outbound

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

Multimodal Model Diffing for Feature Discovery and Control Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 16

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Observation ef347515-df97-4217-990c-bac9c5c5f962 · outbound

This paper cites Case study: Interpreting, manipulating, and controlling CLIP with sparse autoencoders.

Multimodal Model Diffing for Feature Discovery and Control Case study: Interpreting, manipulating, and controlling CLIP with sparse autoencoders

Reference 17

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Observation c03b7f1f-509a-432a-bf1a-565eab037242 · outbound

This paper cites Toy Models of Superposition.

Multimodal Model Diffing for Feature Discovery and Control Toy Models of Superposition

Reference 18

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Observation 907a2509-8501-4d4e-b1ce-4313ef05a681 · outbound

This paper cites Why does unsupervised pre-training help deep learning? 11:625–660, March.

Multimodal Model Diffing for Feature Discovery and Control Why does unsupervised pre-training help deep learning? 11:625–660, March

Reference 19

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Observation 5dc90ba2-6e4d-4bbf-98b4-ace19979d697 · outbound

This paper cites Interpreting CLIP's Image Representation via Text-Based Decomposition.

Multimodal Model Diffing for Feature Discovery and Control Interpreting CLIP's Image Representation via Text-Based Decomposition

Reference 20

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Observation 4227ee35-1ef9-4683-9e9f-b03e81994704 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Multimodal Model Diffing for Feature Discovery and Control Scaling and evaluating sparse autoencoders

Reference 21

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source=pdf_text observed=2026-08-11T04:17:55.834643Z digest=sha256:d4a476ff3dc82d5b9fd3be122ecb60576ec39128b52601e136b6da9092c7a4e2

Observation a67d0a03-cb2c-48bc-99b6-5077d2ca94a8 · outbound

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

Multimodal Model Diffing for Feature Discovery and Control Gemma 2: Improving Open Language Models at a Practical Size

Reference 22

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source=pdf_text observed=2026-08-11T04:17:55.839825Z digest=sha256:3427e33cbb8dab05adab3c55d80d7bc9f94987547ccf8ed5ad0d408f7082b7e8

Observation 2891bc5a-3300-4926-b5a2-2e673fc4e1d2 · outbound

This paper cites FigStep: Jailbreaking large vision-language models via typographic visual prompts.

Multimodal Model Diffing for Feature Discovery and Control FigStep: Jailbreaking large vision-language models via typographic visual prompts

Reference 23

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source=pdf_text observed=2026-08-11T04:17:55.845475Z digest=sha256:5fb3c5afcb7c9a593b7273eb8b844904dce36ce9ed11c4215dc0f93b191b986c

Observation eb7628dc-8244-471c-97d8-776e74cf4700 · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answering.

Multimodal Model Diffing for Feature Discovery and Control Making the v in vqa matter: Elevating the role of image understanding in visual question answering

Reference 24

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Observation 383f8bd4-0f3d-4f1e-8663-f5c8552e8985 · outbound

This paper cites Not all features are created equal: A mechanistic study of vision-language-action models.

Multimodal Model Diffing for Feature Discovery and Control Not all features are created equal: A mechanistic study of vision-language-action models

Reference 25

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Observation 594550ea-48d5-4b18-a375-73064b1a6c2e · outbound

This paper cites The Llama 3 Herd of Models.

Multimodal Model Diffing for Feature Discovery and Control The Llama 3 Herd of Models

Reference 26

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Observation 51b802d7-af4b-4cde-979e-97fc6d7c7e49 · outbound

This paper cites Mechanistic interpretability for steering vision-language-action models.

Multimodal Model Diffing for Feature Discovery and Control Mechanistic interpretability for steering vision-language-action models

Reference 27

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source=pdf_text observed=2026-08-11T04:17:55.865869Z digest=sha256:0c6026d8504407d928bde92429a6a04baf54a4ae4390ec5a0d9d22cf4499da24

Observation 3b640386-0590-4017-8b10-8dcab1ed9d2b · outbound

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

Multimodal Model Diffing for Feature Discovery and Control Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders

Reference 28

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source=pdf_text observed=2026-08-11T04:17:55.870806Z digest=sha256:3ff3e60c380ba4a0cac2e08fdf9706fd94a8325abd5c4e4d41850dc447aef368

Observation e94666bd-7d15-4980-b0a4-2c789fe46bb3 · outbound

This paper cites In-context learning creates task vectors.

Multimodal Model Diffing for Feature Discovery and Control In-context learning creates task vectors

Reference 29

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source=pdf_text observed=2026-08-11T04:17:55.875585Z digest=sha256:5200ee2daea60b95f59d9e62edaa404472b0766387b44d8a4ec44b4f443a7d54

Observation ed622c66-b2d4-4498-8016-67dc19488d7e · outbound

This paper cites VLSBench: Unveiling Visual Leakage in Multimodal Safety.

Multimodal Model Diffing for Feature Discovery and Control VLSBench: Unveiling Visual Leakage in Multimodal Safety

Reference 30

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Observation 92e3a5d3-924f-4d22-961c-de23b2368db0 · outbound

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

Multimodal Model Diffing for Feature Discovery and Control Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 31

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source=pdf_text observed=2026-08-11T04:17:55.885168Z digest=sha256:91c715647bf5c2a447234192c3c11c78c8843cecc6f5b8fa468701775a269ab2

Observation 60bfe481-7159-4238-b912-6accdf089da1 · outbound

This paper cites Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations.

Multimodal Model Diffing for Feature Discovery and Control Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations

Reference 32

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source=pdf_text observed=2026-08-11T04:17:55.889674Z digest=sha256:40a33ebca3cb630484a70fdc2ee4135ee249663d15d4afc28da856c54cecbc27

Observation dd219166-8d27-475a-a1c4-06ce11c66684 · outbound

This paper cites A “diff” tool for AI: Finding behavioral differences in new models.

Multimodal Model Diffing for Feature Discovery and Control A “diff” tool for AI: Finding behavioral differences in new models

Reference 33

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source=pdf_text observed=2026-08-11T04:17:55.894475Z digest=sha256:d637c8cfcc9bfbfc9a1d2fd4b73fbe3d3ca6f3317dc15ceee52bdf6fc5e51621

Observation 7bdee4c9-2165-49f5-a2c8-8a114e2a8644 · outbound

This paper cites Bridging the VLM and mech interp communities for multimodal interpretability.

Multimodal Model Diffing for Feature Discovery and Control Bridging the VLM and mech interp communities for multimodal interpretability

Reference 34

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source=pdf_text observed=2026-08-11T04:17:55.900408Z digest=sha256:4090dc363899d12c70c8086986289dad02b113433e8d0848d86b976ba98022c4

Observation 0a1b3935-db61-4b7d-b663-d9f6cdf18b9d · outbound

This paper cites Steering CLIP's vision transformer with sparse autoencoders.

Multimodal Model Diffing for Feature Discovery and Control Steering CLIP's vision transformer with sparse autoencoders

Reference 35

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source=pdf_text observed=2026-08-11T04:17:55.905911Z digest=sha256:ac0e7a3ec92c927ed009b4728167f5e0fa6f0114b8c8666573a97cf9602cf5dd

Observation 02d7cbe7-c662-4f20-a2f1-8f252dca6f28 · outbound

This paper cites Prisma: An Open Source Toolkit for Mechanistic Interpretability in Vision and Video.

Multimodal Model Diffing for Feature Discovery and Control Prisma: An Open Source Toolkit for Mechanistic Interpretability in Vision and Video

Reference 36

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source=pdf_text observed=2026-08-11T04:17:55.911157Z digest=sha256:e2f70c4fa11c552b922df712c564ebd630fb7deb68348eb6c8c9e7c9678f0688

Observation 4e56b9bf-2caf-4a64-8b63-4fffadd4fa48 · outbound

This paper cites Analyzing Finetuning Representation Shift for Multimodal LLMs Steering.

Multimodal Model Diffing for Feature Discovery and Control Analyzing Finetuning Representation Shift for Multimodal LLMs Steering

Reference 37

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source=pdf_text observed=2026-08-11T04:17:55.916191Z digest=sha256:949cfa4ea54c40825a4aceb892afe5b435b0bc7d0c39777cc0718c1ee8278a5f

Observation bb729be5-e31f-4c6f-95d7-d9726ae0138e · outbound

This paper cites Saes (usually) transfer between base and chat models.

Multimodal Model Diffing for Feature Discovery and Control Saes (usually) transfer between base and chat models

Reference 38

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source=pdf_text observed=2026-08-11T04:17:55.921070Z digest=sha256:743b31fda602e8ba4ab71a16cf65337a19a539977c20f9f99e482565e674385b

Observation 16f919f1-5867-4ed1-b1a8-49dea9800dbf · outbound

This paper cites Similarity of neural network representations revisited.

Multimodal Model Diffing for Feature Discovery and Control Similarity of neural network representations revisited

Reference 39

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source=pdf_text observed=2026-08-11T04:17:55.926358Z digest=sha256:eeaa5c486b47ca8a33d997ca9618f581568d9f10ee1c565216ad1197d571f08d

Observation 07a5bec2-b757-4592-8d0b-4eccf85b6d89 · outbound

This paper cites Sakla, and Kowshik Thopalli.

Multimodal Model Diffing for Feature Discovery and Control Sakla, and Kowshik Thopalli

Reference 40

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source=pdf_text observed=2026-08-11T04:17:55.931559Z digest=sha256:f2607a331f1ea19425ab94c04fb88c8db06f9f46726c72bc3c37bcba8a96453d

Observation 62157067-b288-4ad7-97cb-c5b4e1633c98 · outbound

This paper cites Understanding image representations by measuring their equivariance and equivalence.

Multimodal Model Diffing for Feature Discovery and Control Understanding image representations by measuring their equivariance and equivalence

Reference 41

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no resolver link, observed 2026-08-11T04:17:55.936739Z

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source=pdf_text observed=2026-08-11T04:17:55.936739Z digest=sha256:be4d4fde96c957c1428237cc45f62ab7fab3e40e8dc1b668d5eb0c20d4b76148

Observation ef4f6fd3-9c05-4ffc-8be7-8a071882afe6 · outbound

This paper cites LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models.

Multimodal Model Diffing for Feature Discovery and Control LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 42

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source=pdf_text observed=2026-08-11T04:17:55.941614Z digest=sha256:9efbdde4a62b84d6112f87116ad707da19b12470766a1d0bb8e18c67bbc79e3e

Observation ae34dab8-af93-4449-8e3a-061503ffd727 · outbound

This paper cites Inference- time intervention: Eliciting truthful answers from a language model.

Multimodal Model Diffing for Feature Discovery and Control Inference- time intervention: Eliciting truthful answers from a language model

Reference 43

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no resolver link, observed 2026-08-11T04:17:55.946783Z

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source=pdf_text observed=2026-08-11T04:17:55.946783Z digest=sha256:c38b6ec1c0fa464500af3ffa656d79b12efc635d3491c5f211698fe274b8476b

Observation f66078d7-2322-48be-8ac4-5c1c808c4191 · outbound

This paper cites Images are Achilles’ heel of alignment: Exploiting visual vulnerabilities for jailbreaking multimodal large language models.

Multimodal Model Diffing for Feature Discovery and Control Images are Achilles’ heel of alignment: Exploiting visual vulnerabilities for jailbreaking multimodal large language models

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.969271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:55.951510Z digest=sha256:05b00b1a4c067fd7606d26dcb706f01bccc27915e8dcf3af2f39eb9ef5dab622

Observation 7c5cf49e-69d0-46fc-b00c-d062e287ae2c · outbound

This paper cites Convergent Learning: Do different neural networks learn the same representations?.

Multimodal Model Diffing for Feature Discovery and Control Convergent Learning: Do different neural networks learn the same representations?

Reference 45

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no resolver link, observed 2026-08-11T04:17:55.956223Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:55.956223Z digest=sha256:e1a5c85f1bf73d978861795721ff150053ffe9c31dd8cb9a079b41943d1c3640

Observation b362ad44-4a2b-4a9d-9394-b8618f4cc42d · outbound

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

Multimodal Model Diffing for Feature Discovery and Control Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 46

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no resolver link, observed 2026-08-11T04:17:55.961255Z

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source=pdf_text observed=2026-08-11T04:17:55.961255Z digest=sha256:d96ec8890bc44de69b6c8d6d4052b776e09a70ac27e1897f4c1d515e7eff5f61

Observation f5eddaa7-8d8b-40f1-9231-425afcca5f9e · outbound

This paper cites Sparse autoencoders reveal selective remapping of visual concepts during adaptation.

Multimodal Model Diffing for Feature Discovery and Control Sparse autoencoders reveal selective remapping of visual concepts during adaptation

Reference 47

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no resolver link, observed 2026-08-11T04:17:55.967019Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:55.967019Z digest=sha256:4d2533c40b6a845e7210536529c20966f6c0e8063417905aa015193eda196786

Observation 74cb08c5-3e38-4f66-b5a3-cf3e6d9061f1 · outbound

This paper cites A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models.

Multimodal Model Diffing for Feature Discovery and Control A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models

Reference 48

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no resolver link, observed 2026-08-11T04:17:55.972218Z

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source=pdf_text observed=2026-08-11T04:17:55.972218Z digest=sha256:6d329889693c15aad7148056d1b71971701e6dee9f95a39da2894950c64512ed

Observation 50c39459-8359-4d8a-8f3b-06a5764fccdb · outbound

This paper cites Sparse crosscoders for cross-layer features and model diffing, October 25 2024.

Multimodal Model Diffing for Feature Discovery and Control Sparse crosscoders for cross-layer features and model diffing, October 25 2024

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.952495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:55.977277Z digest=sha256:0e24e0a0b7b1bec85340b8b5d383dec0a64b2293c3d7b4fe8c5dba49ff5c19da

Observation e242e417-d6d1-466c-8c67-75d87eb17f48 · outbound

This paper cites Visual spatial reasoning.Transactions of the Association for Computational Linguistics, 2023.

Multimodal Model Diffing for Feature Discovery and Control Visual spatial reasoning.Transactions of the Association for Computational Linguistics, 2023

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.934987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:55.981926Z digest=sha256:0473de3d9a0cbd0bd1e9723c978a4f01ac31b8b4127962ae791d48d684e638dd

Observation 428d81df-84f7-4297-95c6-84ba78dfca31 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Multimodal Model Diffing for Feature Discovery and Control Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 51

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no resolver link, observed 2026-08-11T04:17:55.986160Z

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source=pdf_text observed=2026-08-11T04:17:55.986160Z digest=sha256:63f307c65d13ae310c59b9a96b9dac085f83b81c71eabf8920e9b739d5501ac9

Observation 159ce224-eb30-4005-bd03-3e7034b33e31 · outbound

This paper cites Improved baselines with visual instruction tuning.

Multimodal Model Diffing for Feature Discovery and Control Improved baselines with visual instruction tuning

Reference 52

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no resolver link, observed 2026-08-11T04:17:55.990284Z

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source=pdf_text observed=2026-08-11T04:17:55.990284Z digest=sha256:b5e9b02a59bd914620646c3a8061894cb4faa67a5640294b123d5a48889991c3

Observation a8f7a635-04af-41c1-9058-446d263e58fb · outbound

This paper cites MM-SafetyBench: A benchmark for safety evaluation of multimodal large language models.

Multimodal Model Diffing for Feature Discovery and Control MM-SafetyBench: A benchmark for safety evaluation of multimodal large language models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.897139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:55.994689Z digest=sha256:a768a3e8fe2185467e85ee011029183ed49f7fb1e3f0a0873a3ea4c201da2e1b

Observation 4cc32df0-f6f3-4a06-9080-8ad98d0fa6c4 · outbound

This paper cites OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models.

Multimodal Model Diffing for Feature Discovery and Control OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models

Reference 54

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no resolver link, observed 2026-08-11T04:17:55.999133Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:55.999133Z digest=sha256:5fcbc210b3650a44d179ae47d84df202aa3288d440ecee58955e9fa6c2713818

Observation 2db28554-8e14-41be-8bc8-fc9bd7333573 · outbound

This paper cites Michaud, Yonatan Belinkov, David Bau, and Aaron Mueller.

Multimodal Model Diffing for Feature Discovery and Control Michaud, Yonatan Belinkov, David Bau, and Aaron Mueller

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.880397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.003768Z digest=sha256:6b5b07b4920752a5f204fbd92d0365caa5490998ffa0de4441d8232181a03f23

Observation 1012ade3-0d1d-4240-a17c-094795998f39 · outbound

This paper cites Locating and editing factual associations in GPT.

Multimodal Model Diffing for Feature Discovery and Control Locating and editing factual associations in GPT

Reference 56

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no resolver link, observed 2026-08-11T04:17:56.008128Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:56.008128Z digest=sha256:fcbd333ba1ae972c4e37038f61c866aa5d8e3cf5d2213ff8b50aa6bc395f4ae7

Observation 464d7b55-d456-457f-86c9-7b103017259e · outbound

This paper cites Robustly identifying concepts introduced during chat fine-tuning using crosscoders.arXiv preprint arXiv:2504.02922, 2025.

Multimodal Model Diffing for Feature Discovery and Control Robustly identifying concepts introduced during chat fine-tuning using crosscoders.arXiv preprint arXiv:2504.02922, 2025

Reference 57

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no resolver link, observed 2026-08-11T04:17:56.012960Z

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source=pdf_text observed=2026-08-11T04:17:56.012960Z digest=sha256:70f165055873d3e160b2be661c5488c6e83db102b4dff6bb7a0e2bb67ed42891

Observation cc5bc455-3eba-42e8-901f-b572d332ca4a · outbound

This paper cites What we learned trying to diff base and chat models (and why it matters).LessWrong, 2025.

Multimodal Model Diffing for Feature Discovery and Control What we learned trying to diff base and chat models (and why it matters).LessWrong, 2025

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.853986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.017719Z digest=sha256:d353ccac800704171051acf260c5ec2a26e66ff1cf2636a5176421cf49582c3a

Observation 8451658b-066d-4558-848c-483cfff8b398 · outbound

This paper cites Insights on crosscoder model diffing.

Multimodal Model Diffing for Feature Discovery and Control Insights on crosscoder model diffing

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.837250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.022501Z digest=sha256:a00fcd15963c3782a207ec263ff7a9281609439e42dc9a9f2063616bc0d34c63

Observation 5db2cfa0-3178-48d0-9c2f-245259e280e8 · outbound

This paper cites Attribution patching: Activation patching at industrial scale.

Multimodal Model Diffing for Feature Discovery and Control Attribution patching: Activation patching at industrial scale

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.818307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.027425Z digest=sha256:92fb2e1f4a9e06dc80c416cd2211d049c258d1d1a8e606b140c71d25dec3133e

Observation cdd46c79-02f1-4c4e-86bb-b856ba020424 · outbound

This paper cites Towards Interpreting Visual Information Processing in Vision-Language Models.

Multimodal Model Diffing for Feature Discovery and Control Towards Interpreting Visual Information Processing in Vision-Language Models

Reference 61

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no resolver link, observed 2026-08-11T04:17:56.032176Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:56.032176Z digest=sha256:cb702768b50a8372e8655bbddabb8da7a4f4b9d3c3e81529586f95375334588d

Observation 623a2370-84b8-4f4a-bf0b-0b8c4a7bd95c · outbound

This paper cites Steering Language Model Refusal with Sparse Autoencoders.

Multimodal Model Diffing for Feature Discovery and Control Steering Language Model Refusal with Sparse Autoencoders

Reference 62

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no resolver link, observed 2026-08-11T04:17:56.038373Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:56.038373Z digest=sha256:48b2c4b17095ff81cd5432c6e0d845d5c313af11b98fc6157a6bd0791949cd1e

Observation bbc722ed-96ce-4a69-89d5-624cf509d697 · outbound

This paper cites Zoom in: An introduction to circuits.Distill, 2020.

Multimodal Model Diffing for Feature Discovery and Control Zoom in: An introduction to circuits.Distill, 2020

Reference 63

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no resolver link, observed 2026-08-11T04:17:56.044310Z

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source=pdf_text observed=2026-08-11T04:17:56.044310Z digest=sha256:5335197ddd83835f9a88c45fe91d6c098186963f9e11aa240e27708628c4e9bc

Observation 058d2038-410f-42cd-9c2b-798bf255d421 · outbound

This paper cites Visualizing representations: Deep learning and human beings.

Multimodal Model Diffing for Feature Discovery and Control Visualizing representations: Deep learning and human beings

Reference 64

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.798542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.049202Z digest=sha256:cc333050d6f11f4315dcc1c6245331cb49bfc50569afbed356d967955fb68982

Observation 60c5603e-ea1d-40e2-b130-362652456e2b · outbound

This paper cites Probing the representational power of sparse autoencoders in vision models.

Multimodal Model Diffing for Feature Discovery and Control Probing the representational power of sparse autoencoders in vision models

Reference 65

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verified exact
raw_fallback, observed 2026-08-11T04:17:56.747243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.054083Z digest=sha256:a31dd21ca003f3ecb6ef6d147d85715419faf5ba5ed047f062af0dc31016745b

Observation 5b9793e9-4c4a-4e7c-862e-920e5d638bbe · outbound

This paper cites Gpt-4o-mini: Advancing cost-efficient intelligence.

Multimodal Model Diffing for Feature Discovery and Control Gpt-4o-mini: Advancing cost-efficient intelligence

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.782692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.058945Z digest=sha256:906b8f108f5067f0e4ec90f7736b5cafc66f0fa90fa06e6976b6648913ff766f

Observation 377960dc-cb41-4e38-a7f4-d2932749b680 · outbound

This paper cites Sparse autoencoders learn monosemantic features in vision-language models.

Multimodal Model Diffing for Feature Discovery and Control Sparse autoencoders learn monosemantic features in vision-language models

Reference 67

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no resolver link, observed 2026-08-11T04:17:56.063731Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:56.063731Z digest=sha256:099ac9c4e5dc3b8c479592040047b5348d3d013d491859713f1464741cdb6fe6

Observation 1c619101-97ef-42f1-aae8-e70c8d36057a · outbound

This paper cites Towards vision-language mechanistic interpretability: A causal tracing tool for blip.

Multimodal Model Diffing for Feature Discovery and Control Towards vision-language mechanistic interpretability: A causal tracing tool for blip

Reference 68

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.766065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.068462Z digest=sha256:21afe6eb7519bc925473911c7f1ce08a03cd197d2f199853ee6005d6f8275a71

Observation 94b2dead-18bc-4a07-af33-a10015ae3873 · outbound

This paper cites Beyond I'm Sorry, I Can't: Dissecting Large Language Model Refusal.

Multimodal Model Diffing for Feature Discovery and Control Beyond I'm Sorry, I Can't: Dissecting Large Language Model Refusal

Reference 69

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no resolver link, observed 2026-08-11T04:17:56.073278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.073278Z digest=sha256:b25e254b17a618d443446a48c60b7bdcc5dcb9cc4e86fbbe32a61447dae268fe

Observation eacb6670-9287-4508-b7cc-10e65ab0b142 · outbound

This paper cites Visual adversarial examples jailbreak aligned large language models.

Multimodal Model Diffing for Feature Discovery and Control Visual adversarial examples jailbreak aligned large language models

Reference 70

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.750674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.078497Z digest=sha256:8576d488170322889b295328ddcd5c2ce8f80381c7ade64554c596f982b61875

Observation d5566a4c-bbc4-4029-82c9-0268f9e08351 · outbound

This paper cites Qwen-Scope: An open sparse autoencoder suite for the Qwen model family.

Multimodal Model Diffing for Feature Discovery and Control Qwen-Scope: An open sparse autoencoder suite for the Qwen model family

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.733675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.083263Z digest=sha256:5500d3557ca3ac11d5357e0354ba227a9ed948fab756a5f0d56b4a55c940ef75

Observation fe447d69-874d-4cbd-b5a0-ea082f32f82e · outbound

This paper cites Learning transferable visual models from natural language supervision.

Multimodal Model Diffing for Feature Discovery and Control Learning transferable visual models from natural language supervision

Reference 72

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no resolver link, observed 2026-08-11T04:17:56.088107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.088107Z digest=sha256:1c679c8181f6f68822c4147b3c1ea9fed92c034997f130cdfc7ba8df9d2a7923

Observation eadbd835-4e5f-45e3-8fea-de3c5e559122 · outbound

This paper cites Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders.

Multimodal Model Diffing for Feature Discovery and Control Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders

Reference 73

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unresolved
no resolver link, observed 2026-08-11T04:17:56.092721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.092721Z digest=sha256:a7250aecdbb1fa2c73f9faac95e1f3bed170d6d24eb032d087f5d7efe53a0f77

Observation 4641de98-7e7b-4fc5-a4ab-6302312a8412 · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition.

Multimodal Model Diffing for Feature Discovery and Control Steering Llama 2 via Contrastive Activation Addition

Reference 74

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unresolved
no resolver link, observed 2026-08-11T04:17:56.097463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.097463Z digest=sha256:8ca7c6bdd5a4092786d656b35b8f9177e6f16e573ef15e2fd3d4a8a5d2998fa2

Observation 8c892395-c64d-4597-88bb-e01c606b2917 · outbound

This paper cites Multi- modal neurons in pretrained text-only transformers.

Multimodal Model Diffing for Feature Discovery and Control Multi- modal neurons in pretrained text-only transformers

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.705410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.102224Z digest=sha256:fe178b321424795779b78b1448d4dcf2b511b4fb7be4e70eeb5aa3fe820bed30

Observation f298f62e-2df4-4676-8705-f70f9d84fe17 · outbound

This paper cites SteerVLM: Robust model control through lightweight activation steering for vision language models.

Multimodal Model Diffing for Feature Discovery and Control SteerVLM: Robust model control through lightweight activation steering for vision language models

Reference 76

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.688536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.106645Z digest=sha256:4526cccdacf3f9dfab8426d09ed6cf00d9cf6adc5c6402cdcb8669691a124dd0

Observation 830f7044-5311-48c7-b4a4-e492efe747ce · outbound

This paper cites LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models.

Multimodal Model Diffing for Feature Discovery and Control LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 77

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no resolver link, observed 2026-08-11T04:17:56.111721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.111721Z digest=sha256:0384c09a3859941fdf9105e45e3f2adf90d9b5e23d564ff9c35c2b28e50bf44d

Observation ea2aabab-eee9-460d-ba2a-2b5538ff20e5 · outbound

This paper cites PaliGemma 2: A Family of Versatile VLMs for Transfer.

Multimodal Model Diffing for Feature Discovery and Control PaliGemma 2: A Family of Versatile VLMs for Transfer

Reference 78

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no resolver link, observed 2026-08-11T04:17:56.116317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.116317Z digest=sha256:519a2cd686b260c8defec05c57d5e68f7340dad9db6686894ed649d5f3010433

Observation 652c6242-0c83-45b3-84c8-a17a7d903b88 · outbound

This paper cites Daniel Freeman, Theodore R.

Multimodal Model Diffing for Feature Discovery and Control Daniel Freeman, Theodore R

Reference 79

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no resolver link, observed 2026-08-11T04:17:56.122564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.122564Z digest=sha256:1562519e0db6781b4d8d134b48e2e8652ccf40e1b9e5854f1ed2abd789e0e6cb

Observation ad666547-3921-415d-9f0d-0f41acd4ac5e · outbound

This paper cites Li, Arnab Sen Sharma, Aaron Mueller, Byron C.

Multimodal Model Diffing for Feature Discovery and Control Li, Arnab Sen Sharma, Aaron Mueller, Byron C

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.659875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.127927Z digest=sha256:35f12b50b04e7dd87a15340065ef2c8da45aecc93522aa678e951bb34dc33c03

Observation d37558b3-dc39-493d-bf70-b84cb8eedef5 · outbound

This paper cites Eyes wide shut? exploring the visual shortcomings of multimodal llms.

Multimodal Model Diffing for Feature Discovery and Control Eyes wide shut? exploring the visual shortcomings of multimodal llms

Reference 81

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no resolver link, observed 2026-08-11T04:17:56.132540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.132540Z digest=sha256:f1fcdbd5cccc05402c5a4c7b3c9f36f8caf3e02decc1ecdc7d476603d96d9337

Observation 4f30b446-4ab4-4a1a-a778-10e1ba21a3ed · outbound

This paper cites Steering Language Models With Activation Engineering.

Multimodal Model Diffing for Feature Discovery and Control Steering Language Models With Activation Engineering

Reference 82

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no resolver link, observed 2026-08-11T04:17:56.137372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.137372Z digest=sha256:652019b704475a23324a2dc9a428eaf186b4774599ab60626960e143397b7a57

Observation a5e3ee40-f7fd-46f4-9da1-684f3115af2c · outbound

This paper cites Too late to recall: The two-hop problem in multimodal knowledge retrieval.

Multimodal Model Diffing for Feature Discovery and Control Too late to recall: The two-hop problem in multimodal knowledge retrieval

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.628662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.142365Z digest=sha256:90b9e8f1edec5aa405779392e0d01f9deee418be2d53f28791bc9ae4664ac320

Observation e97f989c-c33a-4426-8979-5210adbd71a5 · outbound

This paper cites How Visual Representations Map to Language Feature Space in Multimodal LLMs.

Multimodal Model Diffing for Feature Discovery and Control How Visual Representations Map to Language Feature Space in Multimodal LLMs

Reference 84

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no resolver link, observed 2026-08-11T04:17:56.147155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.147155Z digest=sha256:f9d2a88990f730215ae9ec22c417d9cabcfc719fb76756f6cce722019c480355

Observation 9ddfa148-7c15-4249-9c65-72225f1a76bd · outbound

This paper cites Steering away from harm: An adaptive approach to defending vision language model against jailbreaks.

Multimodal Model Diffing for Feature Discovery and Control Steering away from harm: An adaptive approach to defending vision language model against jailbreaks

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.611779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.152172Z digest=sha256:d462f401a5543fdc30e9468cc0817d600a982d293afe00ff2d5f40cf82a71ffa

Observation 3ad407f8-f160-46c8-9936-e40a5904103c · outbound

This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.

Multimodal Model Diffing for Feature Discovery and Control InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Reference 86

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unresolved
no resolver link, observed 2026-08-11T04:17:56.156829Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:56.156829Z digest=sha256:0cc0cd62dc58cd759f12df6f0d727afeafeae6e3271310dbd3c12e1c230416e2

Observation 3b14a2e9-6053-4aa2-9b6a-279769fe4d46 · outbound

This paper cites AdaShield: Safeguarding multimodal large language models from structure-based attack via adaptive shield prompting.

Multimodal Model Diffing for Feature Discovery and Control AdaShield: Safeguarding multimodal large language models from structure-based attack via adaptive shield prompting

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.595098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.162853Z digest=sha256:6e2844fd5470c76b68260e6b335832e0c1f2501e8474259e160102f999546543

Observation 47a8435a-2c41-4f4a-81e8-3c19919d4f69 · outbound

This paper cites LLaVA-CoT: Let Vision Language Models Reason Step-by-Step.

Multimodal Model Diffing for Feature Discovery and Control LLaVA-CoT: Let Vision Language Models Reason Step-by-Step

Reference 88

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no resolver link, observed 2026-08-11T04:17:56.167527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.167527Z digest=sha256:5e11e9726a7e5442896242e6ff0c0f3b50803adaa3ff58e87bf34e3fec115d58

Observation 95f2b71b-43ef-4498-9931-0584ebf2d855 · outbound

This paper cites Qwen3 Technical Report.

Multimodal Model Diffing for Feature Discovery and Control Qwen3 Technical Report

Reference 89

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no resolver link, observed 2026-08-11T04:17:56.172320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.172320Z digest=sha256:f1d7784e025373bc3a8fbf1fd83d7b43cbc806ccbc1542028da665b2285dad40

Observation 581e9dcf-2c1f-4833-b068-0610fedbe8bf · outbound

This paper cites SafeSteer: Adaptive subspace steering for efficient jailbreak defense in vision-language models.arXiv preprint arXiv:2509.21400, 2025.

Multimodal Model Diffing for Feature Discovery and Control SafeSteer: Adaptive subspace steering for efficient jailbreak defense in vision-language models.arXiv preprint arXiv:2509.21400, 2025

Reference 90

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no resolver link, observed 2026-08-11T04:17:56.177100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.177100Z digest=sha256:b6a3f884594b4fdff4f61d1a8033168c617303e77e8c518939117bc10f3ddd2d

Observation c093c9d3-d5cc-4865-8131-636221f4691f · outbound

This paper cites Sigmoid loss for language image pre-training.

Multimodal Model Diffing for Feature Discovery and Control Sigmoid loss for language image pre-training

Reference 91

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no resolver link, observed 2026-08-11T04:17:56.181619Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T04:17:56.181619Z digest=sha256:a3e95d2a73ab3a01d24cda886840f1d725d74c2e09722760275773316e82382b

Observation 112922d6-827d-42aa-a3d2-3aea70380e8f · outbound

This paper cites Towards Best Practices of Activation Patching in Language Models: Metrics and Methods.

Multimodal Model Diffing for Feature Discovery and Control Towards Best Practices of Activation Patching in Language Models: Metrics and Methods

Reference 92

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no resolver link, observed 2026-08-11T04:17:56.186065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.186065Z digest=sha256:b2ff5c430a33d25e3a65076f7607b265ed263c8d528f3ab814c76952be6c84ff

Observation f2b68228-1a9b-4451-b843-561f9a915118 · outbound

This paper cites Cross-modal information flow in multimodal large language models.

Multimodal Model Diffing for Feature Discovery and Control Cross-modal information flow in multimodal large language models

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.566959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.190937Z digest=sha256:bbcf4ebc8cc4a4247ea2acc2e841deab6641741de4c580bf757c7b381deba7c8

Observation 2619e432-0229-4ce4-9384-2c2445bcae20 · outbound

This paper cites Multimodal situational safety.

Multimodal Model Diffing for Feature Discovery and Control Multimodal situational safety

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.549778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.195809Z digest=sha256:bd8efc7b3dede49aafd88737ebea19791ca5104062e3af81d78aace36cc0822e

Observation e7d95dd4-96b3-42a8-bfa2-b16e8a5e4b3e · outbound

This paper cites Relocated.

Multimodal Model Diffing for Feature Discovery and Control Relocated

Reference 95

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T04:17:57.530047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.201760Z digest=sha256:76347e4f4fbf237d972faa6319ded4230b82007f9ccb360ba357c44dd6688aa4

Observation dd40ce95-4dfb-4b0e-bb9f-d4bfd52a465d · outbound

This paper cites an unresolved cited work.

Multimodal Model Diffing for Feature Discovery and Control Unresolved cited work

Reference 96

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unresolved
raw_fallback, observed 2026-08-11T04:17:57.512239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.208372Z digest=sha256:1cd1617dbff907b5c030260e6026cbab277f523ef6769e74730916075ffb6fb7

Observation 7bbbfb87-1a52-4a94-8530-dc262d50d734 · outbound

This paper cites an unresolved cited work.

Multimodal Model Diffing for Feature Discovery and Control Unresolved cited work

Reference 97

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unresolved
raw_fallback, observed 2026-08-11T04:17:57.494613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.214057Z digest=sha256:519b6be788058237c9070816b75a975bffd74568925195cbc1d873c9408d135a

Observation 418b9983-293a-4b05-83aa-d201d05c83b7 · outbound

This paper cites an unresolved cited work.

Multimodal Model Diffing for Feature Discovery and Control Unresolved cited work

Reference 98

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unresolved
raw_fallback, observed 2026-08-11T04:17:57.478120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.219618Z digest=sha256:337d79ddf169fe6a600c22c9b95b42ebd7656f4a0e737cda2aa4ca8d2a8a57de

Observation 4447cbf9-6ef0-4020-9860-8acf0b877876 · outbound

This paper cites this neuron activates for.

Multimodal Model Diffing for Feature Discovery and Control this neuron activates for

Reference 99

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verified fuzzy
raw_fallback, observed 2026-08-11T04:17:57.462367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T04:17:56.224644Z digest=sha256:da6ce2030ec83b6a9adfc9fc026cbbcf40e0694fad7c8cf971ae59c58fe53428

Pith citing papers

No inbound Pith citation observations are available.