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Paper Citation Record · LEDGER

Multimodal Function Vectors for Visual Relations

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2510.02528.

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

pith.paper-citation-record.v1
2510.02528 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:44:42.337781Z

measured 19 of 19 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 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

19 of 19 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f13b2e2d-c20d-445b-9103-e55efb8cabcd · outbound

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

Multimodal Function Vectors for Visual Relations Eliciting Latent Predictions from Transformers with the Tuned Lens

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:44:41.324937Z digest=sha256:4a03943d66f973a3ba5f3f8a8a9cfe2f70000c346de531fdb9e16a052c559ad5

Observation ef4c30a3-9983-491b-b1f1-65b4e19d96f3 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

Multimodal Function Vectors for Visual Relations Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 5

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source=pdf_text observed=2026-08-04T12:44:41.471583Z digest=sha256:8cd8cdd5f082280f059a7b3cedc8d3fe135f1f2a996e0dba0d1f872a3fad926a

Observation 471bf564-8b18-4611-9926-538ddd761c18 · outbound

This paper cites In-Context Learning Creates Task Vectors.

Multimodal Function Vectors for Visual Relations In-Context Learning Creates Task Vectors

Reference 8

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source=pdf_text observed=2026-08-04T12:44:41.828160Z digest=sha256:c881f205d3a9941600b068cf4083f86aa0b585713f12213eeb98165cab907ed8

Observation 357b3f12-c6c0-4d03-bf30-9fac226e18a6 · outbound

This paper cites Multimodal task vectors enable many-shot multimodal in-context learning.

Multimodal Function Vectors for Visual Relations Multimodal task vectors enable many-shot multimodal in-context learning

Reference 9

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source=pdf_text observed=2026-08-04T12:44:41.860652Z digest=sha256:c1fa0951fef3b9d2844f18393be62bb7c88a917c1ca992db28b2d0c3da4b9ccb

Observation 047a46ae-68fa-4009-ac25-d380589c31be · outbound

This paper cites Linguistic regularities in continuous space word representations.

Multimodal Function Vectors for Visual Relations Linguistic regularities in continuous space word representations

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:44:41.922600Z digest=sha256:992725340ab32d91d453dc1c08b0af193d6a7497a33577beec13ed51f6cc1096

Observation 56fa0c16-5ee1-4918-b368-1651308262ce · outbound

This paper cites The Linear Representation Hypothesis and the Geometry of Large Language Models.

Multimodal Function Vectors for Visual Relations The Linear Representation Hypothesis and the Geometry of Large Language Models

Reference 12

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no resolver link, observed 2026-08-04T12:44:41.944932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:44:41.944932Z digest=sha256:e4f93e77c5e76312b920df0df75f0906693908fcbecfccbfc0a209602e791510

Observation 38d9874e-9fa0-4c22-a9b9-1634b3db42e3 · outbound

This paper cites Automatic Discovery of Visual Circuits.

Multimodal Function Vectors for Visual Relations Automatic Discovery of Visual Circuits

Reference 13

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source=pdf_text observed=2026-08-04T12:44:42.010766Z digest=sha256:4eb1853901715add19543d0260934bbc79f7489d1f41ed8f5eebbc768712c21c

Observation 0c98764d-d507-417a-9f62-c5331986484f · outbound

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

Multimodal Function Vectors for Visual Relations Li, Arnab Sen Sharma, Aaron Mueller, Byron C

Reference 14

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source=pdf_text observed=2026-08-04T12:44:42.062353Z digest=sha256:91dbd86ffe8ebd12bfda8d4b3b2af20be01e80b528f0aad5efd0c1e3ad37ee0b

Observation 881effc7-d9ee-45dc-b7f4-b27185076dc3 · outbound

This paper cites Function Vectors in Large Language Models.

Multimodal Function Vectors for Visual Relations Function Vectors in Large Language Models

Reference 15

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source=pdf_text observed=2026-08-04T12:44:42.073130Z digest=sha256:1796d4e47151add796bf17ec47896acf93f689ee4b02a48887348e4c27d7152d

Observation e83c6a99-8aa7-4f0b-aad7-9544aca42ce5 · outbound

This paper cites Steering Language Models With Activation Engineering.

Multimodal Function Vectors for Visual Relations Steering Language Models With Activation Engineering

Reference 16

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source=pdf_text observed=2026-08-04T12:44:42.102750Z digest=sha256:37f60a0a316951b2a0bc0ab92870f47be206385aeb53e4b5cfcedd7057ed2e88

Observation 5a45c559-da8b-4a11-8938-b7f306abf84d · outbound

This paper cites Look Before You Leap: A Universal Emergent Decomposition of Retrieval Tasks in Language Models.

Multimodal Function Vectors for Visual Relations Look Before You Leap: A Universal Emergent Decomposition of Retrieval Tasks in Language Models

Reference 17

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source=pdf_text observed=2026-08-04T12:44:42.134230Z digest=sha256:5efc7fc1f24ece3996d1897030e1c609abfa964aa76d3e14a4ae835be12512f3

Observation b0ea5ba7-73be-4cd4-8f3d-880d99310da9 · outbound

This paper cites Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning.

Multimodal Function Vectors for Visual Relations Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning

Reference 18

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source=pdf_text observed=2026-08-04T12:44:42.196116Z digest=sha256:564659a25c00842aa843663b9f415e8cc4c2cb5601415b3bd9040855481b023b

Observation 90a2fd80-c948-47a5-ac98-615f5aa172fe · outbound

This paper cites From this dataset, we selected 32 diverse objects spanning various categories and size ranges, which were subsequently mapped to a relatively uniform scale.

Multimodal Function Vectors for Visual Relations From this dataset, we selected 32 diverse objects spanning various categories and size ranges, which were subsequently mapped to a relatively uniform scale

Reference 19

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source=pdf_text observed=2026-08-04T12:44:42.337781Z digest=sha256:66de2cf077baf4c8f58fdb11a95302925338231d92cb0d0915372e83806182bb

Observation 1564b451-a3a0-4ac9-80cf-75dad5e35538 · outbound

This paper cites Improving Activation Steering in Language Models with Mean-Centring.

Multimodal Function Vectors for Visual Relations Improving Activation Steering in Language Models with Mean-Centring

Reference 2019

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source=pdf_text observed=2026-08-04T12:44:41.880589Z digest=sha256:042ac3ddc10c2939a60502033fdacf98973f0c5cd99f3503c4a139526be7577a

Observation 67fde6f4-d426-4769-bb32-61f74d561522 · outbound

This paper cites Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey.

Multimodal Function Vectors for Visual Relations Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey

Reference 2021

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source=pdf_text observed=2026-08-04T12:44:41.600573Z digest=sha256:5f63c6024a7690923f978e10af42f9b2e99b98884757891ed41bb875005fa716

Observation c3ce60a4-f745-44e6-921f-7c994602a1d8 · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

Multimodal Function Vectors for Visual Relations Flamingo: a Visual Language Model for Few-Shot Learning

Reference 2022

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source=pdf_text observed=2026-08-04T12:44:41.101436Z digest=sha256:85989d13c5f71714b846066f9ea61f644e37b0e175da62cd68fa49a5d269dd15

Observation a78a07a3-cce5-4f77-afb8-59206c3f3828 · outbound

This paper cites What learning algorithm is in-context learning? Investigations with linear models.

Multimodal Function Vectors for Visual Relations What learning algorithm is in-context learning? Investigations with linear models

Reference 2023

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source=pdf_text observed=2026-08-04T12:44:41.036447Z digest=sha256:f3603e3cc598d0fc8b3c31794ed9ee5c7c12319c5dfac436cbb6feb6b44449ef

Observation 31d8b188-933d-420e-bb95-d9166820a6b1 · outbound

This paper cites Toy Models of Superposition.

Multimodal Function Vectors for Visual Relations Toy Models of Superposition

Reference 2024

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source=pdf_text observed=2026-08-04T12:44:41.764749Z digest=sha256:13b6dfe321216c95018b20f9ba2e8a7bb715b8d4b47521c68c4b0f4daf8f8247

Observation 1e7dfa0c-e1f1-43f3-9915-c62bcfca6b7c · outbound

This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

Multimodal Function Vectors for Visual Relations OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.