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Paper Citation Record · LEDGER

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models

As of 12 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2608.01263.

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

pith.paper-citation-record.v1
2608.01263 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:07:20.340398Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

17 of 17 outbound references displayed

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  • unresolved15
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  • malformed identifier1
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External citation measurements

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Outbound references

Observation 3443699d-2863-484d-a2aa-5a4f8daabd34 · outbound

This paper cites On-policy distillation of language models: Learning from self- generated mistakes.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models On-policy distillation of language models: Learning from self- generated mistakes

Reference 1

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source=pdf_text observed=2026-08-07T01:07:19.020569Z digest=sha256:c5f09c4c823a09579395c95e28dbf4397e6ad447c45ce242f0b08000be459d1e

Observation f9e64e75-b5f3-426a-9c8f-76e3b3f567a2 · outbound

This paper cites Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe

Reference 6

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source=pdf_text observed=2026-08-07T01:07:19.551657Z digest=sha256:24c7816e637f5d35e171ff20955acb385d8d4386eff0845efad69c61e16cadbf

Observation a36614aa-5b48-4114-b552-b879faf2abc0 · outbound

This paper cites MiMo-V2-Flash Technical Report.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models MiMo-V2-Flash Technical Report

Reference 9

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source=pdf_text observed=2026-08-07T01:07:19.808180Z digest=sha256:55a275b93add438749449b642f4a0a46fd7ea8e1c385a0a19a9f96c7fc59e7cc

Observation 9a66d472-cc11-4aec-94e2-c7c55e0a3c70 · outbound

This paper cites Speculative knowledge distillation: Bridging the teacher-student gap through interleaved sampling.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Speculative knowledge distillation: Bridging the teacher-student gap through interleaved sampling

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-07T01:07:20.918561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T01:07:19.969692Z digest=sha256:c6c60f5b4e6ff925d8e5b3b2d666c68f2168eafddabd1baa475eddaf6ff124c1

Observation 7f47bb7c-74b8-4122-bd1b-822fec281377 · outbound

This paper cites Zhuolin Yang, Zihan Liu, Yang Chen, Wenliang Dai, Boxin Wang, Sheng-Chieh Lin, Chankyu Lee, Yangyi Chen, Dongfu Jiang, Jiafan He, et al.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Zhuolin Yang, Zihan Liu, Yang Chen, Wenliang Dai, Boxin Wang, Sheng-Chieh Lin, Chankyu Lee, Yangyi Chen, Dongfu Jiang, Jiafan He, et al

Reference 12

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source=pdf_text observed=2026-08-07T01:07:20.052201Z digest=sha256:c4b0914e693e7cbb940f675481f64a7ab52ac076396e1da574c3c95aeb905b60

Observation 5e2adf38-7dce-48b9-8149-e3f8ec729621 · outbound

This paper cites Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

Reference 13

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source=pdf_text observed=2026-08-07T01:07:20.131355Z digest=sha256:f1f6978649c788f2cd902cc3b7cca59f0e7be23291b107f4754c57612c1bc551

Observation 45c0744c-75e7-4396-a25d-f086a5aea2bd · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models GLM-5: from Vibe Coding to Agentic Engineering

Reference 14

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source=pdf_text observed=2026-08-07T01:07:20.180755Z digest=sha256:a10339cbccff88b06ec82608acebb296c11c8e95c2e72840211fec9b846207a4

Observation 745391a0-2913-4063-9eda-cb93bfd69b6a · outbound

This paper cites ISBN 979-8-89176-251-0.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models ISBN 979-8-89176-251-0

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T01:07:20.265411Z digest=sha256:4074f3642616dd35e741038112145d9f680f3208fa42a6d1312a84e283d502c5

Observation 8efd3814-dd56-4965-8f4d-2b5d22f0367f · outbound

This paper cites Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 16

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source=pdf_text observed=2026-08-07T01:07:20.292905Z digest=sha256:56b4b2bf58c9dedac70fa23ea9cbf69a1a4174834c4082e19f0d6e6b259dddf1

Observation f8e678bd-309c-4235-ace6-931fc96ab25a · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 17

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source=pdf_text observed=2026-08-07T01:07:20.340398Z digest=sha256:0788b2cb6297dc9f86d99903c184bb965f22ab30861642bb0812190038fa0d5b

Observation fcd84053-ac91-4360-8e34-cdc9f00c8ba5 · outbound

This paper cites Qwen3-VL Technical Report.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Qwen3-VL Technical Report

Reference 1998

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source=pdf_text observed=2026-08-07T01:07:19.198552Z digest=sha256:a03ef75e454b58e92512092c66c549c5a1d42cbb29a4d1f6fdd0dc5134e69e08

Observation 0aba0b8e-4014-4285-96ce-9a1b154a8374 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models LLaVA-OneVision: Easy Visual Task Transfer

Reference 2015

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source=pdf_text observed=2026-08-07T01:07:19.446653Z digest=sha256:872131318fca9702957ba46c0a88e7549383bf7352b3902ad3eebc8571478e13

Observation 6a793f7e-84b2-48c5-b6e3-6427f1be107c · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Distilling the Knowledge in a Neural Network

Reference 2018

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source=pdf_text observed=2026-08-07T01:07:19.361852Z digest=sha256:b2caf9875494872d7e2eb57f27249a44cdc62219d05631d0005145991516c850

Observation 6e639fa0-0d85-4bb8-96dc-5529a712570b · outbound

This paper cites Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts

Reference 2021

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source=pdf_text observed=2026-08-07T01:07:19.772724Z digest=sha256:8fe24cf6e6d4efc2fd22019d033ca5608bd4a117d1d53ae5191148d8a7567c79

Observation 48a97ae8-5be3-4630-911e-7ceed6bc729b · outbound

This paper cites Gradient Descent Happens in a Tiny Subspace.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Gradient Descent Happens in a Tiny Subspace

Reference 2024

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source=pdf_text observed=2026-08-07T01:07:19.320720Z digest=sha256:ed902811ed58ae1e88c21f3f43285c263d8cb70cf3a310c00a9e679012a1ce71

Observation 2915c92e-cc6b-4ae4-aaa4-92a2d2087652 · outbound

This paper cites https://thinkingmachines.ai/blog/on-policy-distillation.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models https://thinkingmachines.ai/blog/on-policy-distillation

Reference 2025

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source=pdf_text observed=2026-08-07T01:07:19.666098Z digest=sha256:d4e97107464f44cdc0003534cda16075b5c47aa1a7e18b06136ae6fe43c587e2

Observation 0706f3b7-bc41-4106-a5aa-0bc62724321c · outbound

This paper cites Deepseek-v4: Towards highly efficient million- token context intelligence.arXiv preprint arXiv:2606.19348,.

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models Deepseek-v4: Towards highly efficient million- token context intelligence.arXiv preprint arXiv:2606.19348,

Reference 2026

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source=pdf_text observed=2026-08-07T01:07:19.887005Z digest=sha256:73f037914d73c221629152b706e64ab88947a2efe1b23eca87c26f5b18fd3c2d

Pith citing papers

No inbound Pith citation observations are available.