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Paper Citation Record · LEDGER

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence

As of 6 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.16560.

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

pith.paper-citation-record.v1
2607.16560 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:39:09.547472Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

24 of 24 outbound references displayed

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  • verified fuzzy0
  • unresolved23
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b6370be1-f2e6-496c-96ab-0f152c60a0ac · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 1

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source=pdf_text observed=2026-08-01T20:39:06.564102Z digest=sha256:d5ccb50802da9754522685ecdb32682351a048429217cdffe5d745253082e6de

Observation ddd883f7-a2f9-483e-aeee-277f5a72baca · outbound

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

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Mechanistic Interpretability for AI Safety -- A Review

Reference 2

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source=pdf_text observed=2026-08-01T20:39:06.645877Z digest=sha256:488c5da20dda587846771262871c7a79dc7c30b475b63886808e04ac48187609

Observation 6341219d-f45c-42f8-a5c8-d99f5f848c3b · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence On the Opportunities and Risks of Foundation Models

Reference 3

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source=pdf_text observed=2026-08-01T20:39:06.772075Z digest=sha256:fe5c0c868550e3848fbe7280c9ff4773c45b26e37db3d441353deed5a5afb76c

Observation ba6e7d4b-65b8-4aa5-99ca-55a3650d28d2 · outbound

This paper cites Naver: A neuro-symbolic compositional automaton for visual grounding with explicit logic reasoning.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Naver: A neuro-symbolic compositional automaton for visual grounding with explicit logic reasoning

Reference 4

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source=pdf_text observed=2026-08-01T20:39:06.835553Z digest=sha256:2df5f496f8f0cef36419ac76f128b269cdecd3829b7a558e097d19cd126adedc

Observation a029ce34-3216-4be3-9c22-9898a5cc8d9c · outbound

This paper cites Pseudo-simulation for autonomous driving.arXiv preprint arXiv:2506.04218, 2025.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Pseudo-simulation for autonomous driving.arXiv preprint arXiv:2506.04218, 2025

Reference 5

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source=pdf_text observed=2026-08-01T20:39:06.906540Z digest=sha256:077dd63a74107ea94cb33e2ba27b8b0d07d4b367f57504b7b3e08e338acf878c

Observation 6da47c53-639f-4dc1-8160-2fc2505cda46 · outbound

This paper cites Position: Stop reactively patching your model every time and start proactive test-driven ai development.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Position: Stop reactively patching your model every time and start proactive test-driven ai development

Reference 6

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source=pdf_text observed=2026-08-01T20:39:07.064783Z digest=sha256:c86ecdc2b9ffbdf6a62faad547a738b71eb44dc9a6f6ac82de3156685043b8c7

Observation 1a95ce16-5371-44a3-ae0a-9d2f00bc1cc8 · outbound

This paper cites M3- embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self- knowledge distillation.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence M3- embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self- knowledge distillation

Reference 7

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source=pdf_text observed=2026-08-01T20:39:07.287462Z digest=sha256:e788a7671a04d790366b69eaf1b9451241305e10c18161b1634b4d88d0dfcdbb

Observation c4937fba-4a44-4124-ad81-1fcd8da99c51 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 8

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source=pdf_text observed=2026-08-01T20:39:07.479298Z digest=sha256:d80a3c1545ace0b030efb81603ec91e1514e07f6cf8d135c342b52994d69f6d4

Observation f93ac6a2-d9f3-499f-8771-4984b5bc4fb2 · outbound

This paper cites NAVSIM: Data-driven non-reactive au- tonomous vehicle simulation and benchmarking.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence NAVSIM: Data-driven non-reactive au- tonomous vehicle simulation and benchmarking

Reference 9

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source=pdf_text observed=2026-08-01T20:39:07.564588Z digest=sha256:ff8f92ee0574a8dcf3118bcad249e7dd2264ad8f5939348bc920230e0399b992

Observation 73eeddb1-494d-4cea-ae68-f6407cbbc1cf · outbound

This paper cites Toy Models of Superposition.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Toy Models of Superposition

Reference 10

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source=pdf_text observed=2026-08-01T20:39:07.728361Z digest=sha256:d58b173ad3937e61947bc0201e7ae2c8ec51d7b10a76410b5879d5a359208e36

Observation 4210c4ee-601b-4965-a6c2-51d5139a78a8 · outbound

This paper cites Martin.Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Martin.Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

Reference 11

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source=pdf_text observed=2026-08-01T20:39:07.872921Z digest=sha256:119e52d34ac7b762a04156b56daca76a8c1f024260d2e8e80b0fbf9e5f361e7f

Observation 3e286aa5-4700-4adb-9762-0bb2304cf2b9 · outbound

This paper cites Explainability and vision foundation models: A survey.Information Fusion, 122:103184, 2025.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Explainability and vision foundation models: A survey.Information Fusion, 122:103184, 2025

Reference 12

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source=pdf_text observed=2026-08-01T20:39:07.974982Z digest=sha256:b257f64f704912b16deb9ceedd3454574591970559701c52d64f8c4589c70b21

Observation 9af9f28d-d6af-4ad8-a238-29f561323f8c · outbound

This paper cites Sekai: A video dataset towardsworldexploration.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Sekai: A video dataset towardsworldexploration

Reference 13

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source=pdf_text observed=2026-08-01T20:39:08.084115Z digest=sha256:5a182ac578111398dd08ae0faf14bd83c9bc8c3010b3d676fc470beeaf8e0e51

Observation 46e624d3-fb2d-40d6-918f-28ddee78c860 · outbound

This paper cites A comprehensive survey and guide to multimodal large language models in vision–language tasks.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence A comprehensive survey and guide to multimodal large language models in vision–language tasks

Reference 14

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source=pdf_text observed=2026-08-01T20:39:08.189469Z digest=sha256:eccf1125ef0353e9eafca345a7f58d5afb8ee171a4bfd14e128452b1a29647be

Observation f7d81587-0c32-4dec-b440-5a500e4093d0 · outbound

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

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Visual instruction tuning.Ad- vances in neural information processing systems, 36:34892–34916, 2023

Reference 15

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source=pdf_text observed=2026-08-01T20:39:08.305294Z digest=sha256:ecf6d6d3a30d649880b1bc17ec066f2ba37f2ef446ab29669faa37063f91688c

Observation c9306c13-a683-403b-b310-863933464145 · outbound

This paper cites Manning and Hinrich Schütze.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Manning and Hinrich Schütze

Reference 16

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source=pdf_text observed=2026-08-01T20:39:08.456014Z digest=sha256:24228a5652355e0005bb1c607aea66e16832a5c4ac7a2795b222cb5f77f91cb3

Observation 989f026c-a2fa-4a8d-b1ea-8d39a9d7fcc2 · outbound

This paper cites Enhancing reason- ing capabilities of llms via principled synthetic logic corpus.Advances in Neural Information Processing Systems, 37:73572–73604, 2024.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Enhancing reason- ing capabilities of llms via principled synthetic logic corpus.Advances in Neural Information Processing Systems, 37:73572–73604, 2024

Reference 17

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source=pdf_text observed=2026-08-01T20:39:08.678816Z digest=sha256:07f5688b5e88e1e1260f73f823b7d75b210e3e89ac9c44ed3cd92126c413f536

Observation baa1a07b-d015-4da9-a7cf-d5aed76c9761 · outbound

This paper cites PhysicalAI–Autonomous Vehicles.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence PhysicalAI–Autonomous Vehicles

Reference 18

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source=pdf_text observed=2026-08-01T20:39:08.818158Z digest=sha256:7e5a2f0ee1ea3f6fa4b55eddc1bfb3be61e5fc809b49a84d5b890ca473a8df57

Observation 54d91eb4-a59e-4fe9-b88a-33af79ec88a1 · outbound

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

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Learning transferable visual models from natural language supervision

Reference 19

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source=pdf_text observed=2026-08-01T20:39:09.091749Z digest=sha256:b38c8af2bf16d5bdb564c6e30dbe7460de575b7131b3ec057a6286ff6780fd2b

Observation 02b5a29d-ebd6-4d6a-a0f5-b91953833842 · outbound

This paper cites Sse: Multimodal semantic data selection and enrichment for industrial-scale data assimilation.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Sse: Multimodal semantic data selection and enrichment for industrial-scale data assimilation

Reference 20

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source=pdf_text observed=2026-08-01T20:39:09.163877Z digest=sha256:7ca7838f64b4dc45ca60b3c9a0682e457112047e32edb6993851212a616c5c8f

Observation 96c48ab9-f19f-4006-8c37-eda66d59e661 · outbound

This paper cites Winoground: Probing vision and language models for visio-linguistic composition- ality.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Winoground: Probing vision and language models for visio-linguistic composition- ality

Reference 21

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source=pdf_text observed=2026-08-01T20:39:09.283159Z digest=sha256:1715147515fdf41d93d0211e6988016499890b8a05db459ac53053201959e2a4

Observation 6490c17d-7445-47f7-9de5-f5432f0e9a4f · outbound

This paper cites Scalable parallel prompting for complex av video captioning.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Scalable parallel prompting for complex av video captioning

Reference 22

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source=pdf_text observed=2026-08-01T20:39:09.446835Z digest=sha256:6a26f11d47f6ff6b62a57fe8bda9f91f39444c3cc02660808913d7740ddb79fc

Observation 51174ffd-5566-43cb-97ef-8249c08996d5 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 23

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source=pdf_text observed=2026-08-01T20:39:09.547472Z digest=sha256:0816b1406e7a95e6ea0650a7940bcb7e31ad556e4043c26d84b83587501f6821

Observation 2e816ba3-5546-4c9a-8afb-7bbccc080456 · outbound

This paper cites Accessed July 16, 2026.

From Modalities to Propositions: A Language-Centric Framework for Multimodal Intelligence Accessed July 16, 2026

Reference 2026

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source=pdf_text observed=2026-08-01T20:39:08.968462Z digest=sha256:cef9f0acad91a408f2a1bcdc4c8165b05fa46e7fc7a92a26af2d2ccaae1d83c0

Pith citing papers

No inbound Pith citation observations are available.