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Paper Citation Record · LEDGER

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 3 inbound Pith citation observations for arXiv:2606.15920.

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

pith.paper-citation-record.v1
2606.15920 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T13:55:58.460765Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T04:39:21.018036Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 69213e14-3603-4d74-ab43-bca99ef93821 · outbound

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

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:d3ee28b5f4f18458f459ba57bd6696502af0b3d618fbf4dd459f205b888fdde7

Observation 6f9c81aa-62cf-4196-a525-efc2b9126b92 · outbound

This paper cites Reinforcement Learning via Self-Distillation.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Reinforcement Learning via Self-Distillation

Reference 2

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:193b5e248f00cdbcfbcb97fc563d478ffd7a8c44a1c1c9072b8e3228fb450844

Observation ee0af85b-c1fa-47f0-ae2c-12293accecc9 · outbound

This paper cites D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models

Reference 3

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:6d51b225b6a5c19bc4c22176b36f8ef60e0713bf769f3efad217746b29f47a21

Observation 70849500-5e7e-4f7d-aa6c-25caf480ac13 · outbound

This paper cites Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?

Reference 4

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:49c71d779b488620a3cf01b620fb1495a0231d4b6418bba26915cbd1bff1db18

Observation 4f5a76a2-6de7-468e-802b-acd51a9424cb · outbound

This paper cites Explainable Multimodal Emotion Recognition.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Explainable Multimodal Emotion Recognition

Reference 5

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:b95f73778f799e78cb0d1c49b1ff248399ef14e5111f7c8d2e062e73e1ce891c

Observation 0de157f2-39aa-4fff-aa17-457a6b77ef5a · outbound

This paper cites Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset

Reference 6

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:78c671a65d4abcbaa9784d1ec200d4c586dbaf2115aeec278e99544758a62040

Observation c1460667-fc81-4d47-8e87-a1cb106085b6 · outbound

This paper cites Make acoustic and visual cues matter: Ch-sims v2.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Make acoustic and visual cues matter: Ch-sims v2

Reference 7

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:7b7bb9e2797c0b77a390edc7eb903e678d371e030929616185a45bc82d0eea7f

Observation 7c7c6d80-1046-4346-9d63-4f7685a9326b · outbound

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

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing https://thinkingmachines.ai/blog/on-policy-distillation

Reference 8

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:7fb6146c7406187bf12b8ca9822f319f078ff4b8d4453c8cd14f6caa23270a05

Observation 69835f6e-d958-49fc-b43d-8b05c05e2203 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 9

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:bcbdab00735ad7278ca02e6ced4c5bc0b06a7eeb4e63698e7a4a2a9dece30562

Observation 14a9f8e2-6238-46b3-98db-dbd91c1557b0 · outbound

This paper cites A Survey of On-Policy Distillation for Large Language Models.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing A Survey of On-Policy Distillation for Large Language Models

Reference 10

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:6541834d87ad97d894345e03465ba10578825c4120a68ebb7a4e78abfe9ddf5e

Observation 21f06fd3-f09b-4095-8c17-f109953a2433 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 11

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:5167067a093bc5173480cfb80a84090462b7e8ce6158e51d81356b78332db98c

Observation ccefd188-c327-4a80-b63c-b9172e35fc1a · outbound

This paper cites Ai for service: Proactive assistance with ai glasses.arXiv preprint arXiv:2510.14359,.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Ai for service: Proactive assistance with ai glasses.arXiv preprint arXiv:2510.14359,

Reference 12

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:33a77427ecc00e9104ac5ee21caf673b4a56d5a3d0e41c92ac51199c176028dd

Observation 17f41f85-9d85-43a6-998f-149883ceb145 · outbound

This paper cites Innovator-vl: A multimodal large language model for scientific discovery.arXiv preprint arXiv:2601.19325, 2026a.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Innovator-vl: A multimodal large language model for scientific discovery.arXiv preprint arXiv:2601.19325, 2026a

Reference 13

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:b5db511b13aecd1b8c5b9ba078b5f3da7a8c61eb09a611a1190dd6986228ed50

Observation 814cfe0c-37be-4c88-8ebc-1ba671e6f204 · outbound

This paper cites MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos

Reference 14

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:6b5e6f517c613e7d74ad78bf59ae1aa8571db004276223c3f220e0747d1486f3

Observation c3a8e96b-4143-41ff-b1c2-d9357e445a9c · outbound

This paper cites R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning.

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning

Reference 15

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:63d08670f78b4d060bad50e86581c91e203e2ee9475a99368016a7bd96ff6ac7

Observation d1cb9dc8-ea9c-48a0-805a-3a3d321636c4 · outbound

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

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 16

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unresolved
no resolver link, observed 2026-07-12T13:55:58.460765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:55:58.460765Z digest=sha256:8fb77bf126dee97e929318b0e9a241f5b311d8fbbd7bd255bd465503d848f6b7

Pith citing papers

Observation 3957d440-27e1-46d3-ad1c-e00119a4fe88 · inbound

GMoT: Gated Motion-Aware Tokenization for Fine-Grained Micro-Gesture Video Reasoning with Multimodal LLMs cites this paper.

GMoT: Gated Motion-Aware Tokenization for Fine-Grained Micro-Gesture Video Reasoning with Multimodal LLMs OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

Reference 14

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verified exact
local_arxiv, observed 2026-08-02T04:43:29.970222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-02T04:39:21.018036Z digest=sha256:1bb960aa060e34ad01d5e57097773208299d9733a6009fd73ede5b54b62ab320

Observation 88e80024-90ca-4c16-9aae-fe61899dc746 · inbound

PCA: Persistence-Aware Compression and Aggregation for Fast Video Large Language Models cites this paper.

PCA: Persistence-Aware Compression and Aggregation for Fast Video Large Language Models OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

Reference 7

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no resolver link, observed 2026-08-01T11:49:57.251332Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:49:57.251332Z digest=sha256:6e1321f24385cd50746141be7b364be81352643d03790988a495675b66934400

Observation bac157ec-27c9-4d95-8575-6be50ef1fff2 · inbound

RP-OPSD: Resolution-Privileged On-Policy Self-Distillation for Multimodal Large Language Models cites this paper.

RP-OPSD: Resolution-Privileged On-Policy Self-Distillation for Multimodal Large Language Models OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

Reference 45

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no resolver link, observed 2026-07-31T14:46:28.137510Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T14:46:28.137510Z digest=sha256:6ce68af8a368b004e3694753230361c23d5f63024e2115b5eac6ece6f2066d84