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Paper Citation Record · LEDGER

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.13931.

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

pith.paper-citation-record.v1
2607.13931 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:20:41.241752Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

42 of 42 outbound references displayed

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  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e874b72-8eed-4456-aae6-14333dc9388c · outbound

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

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T03:20:41.069447Z digest=sha256:8adab74fc1871a1130ee2a65dd1d077bc9fbaa1e43f1236f575fb420058bbbe4

Observation 0e6669aa-5bce-441b-a7c8-406a04c220c6 · outbound

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

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

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source=arxiv_source observed=2026-08-02T03:20:41.075686Z digest=sha256:c81cf450111dcb7393b192ac51d6ee412ceaf1963a1e54d5ec847a9afcf238b6

Observation ec268e6a-fbca-434e-99a0-8c764a8fc3d6 · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 3

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source=arxiv_source observed=2026-08-02T03:20:41.080183Z digest=sha256:88605a33c6e94fa4e991e67850f9299443941f6375109d1a9a7c85c9adc258b5

Observation 06dcff5a-f3fd-44cc-b354-a1b8179ffeb8 · outbound

This paper cites R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO

Reference 4

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source=arxiv_source observed=2026-08-02T03:20:41.084534Z digest=sha256:16fa2ee11e2858de71b8411815d0c17c525b3d45b43fbe2bb434fa270832b042

Observation 3a01ce91-20bb-4567-9162-45fec421330f · outbound

This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning

Reference 5

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source=arxiv_source observed=2026-08-02T03:20:41.089080Z digest=sha256:7f64da166fa0b51a294b59b458e6cdf0f38029fce5d0c7e20b516e541182aaf8

Observation 23cd4394-cf7d-4f7a-b7de-d0ea9d71ec76 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 6

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source=arxiv_source observed=2026-08-02T03:20:41.093691Z digest=sha256:ac6bcd1c0ba3d0d2dc99b33a668ff6b183adfe2a072f0b7a3d65ab3b07bf59bf

Observation 58bfba63-0677-4203-8ce8-47278cb26ad3 · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 7

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source=arxiv_source observed=2026-08-02T03:20:41.098234Z digest=sha256:dbf0246d37633f8420a7849b43e3e8e618c7f22890f24aeff9d11dfe336239f4

Observation 93038a30-d193-4c47-b198-b678de52e9c3 · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 8

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source=arxiv_source observed=2026-08-02T03:20:41.102162Z digest=sha256:d1a8875bcde2d3e81d31284c2cc7dc820b162c01c6ed826ce44077fa13d461a6

Observation eebd00f9-9e48-4d19-b9a1-da1e3cc66184 · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 9

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source=arxiv_source observed=2026-08-02T03:20:41.107069Z digest=sha256:1fb2f528c759858ccee80ff64251217556bb548066f26d5a14a2311ab629d463

Observation 52f88b82-711d-432d-948b-3379d87541e4 · outbound

This paper cites arXiv preprint arXiv:2505.14677 , year=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning arXiv preprint arXiv:2505.14677 , year=

Reference 10

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source=arxiv_source observed=2026-08-02T03:20:41.111376Z digest=sha256:64515e8e91fc6f509cbd1be611f7e71c70c39e5878723b490e0c9b4c32d9434b

Observation 82c3c017-6304-47c5-bbae-98c898eda726 · outbound

This paper cites arXiv preprint arXiv:2506.07218 , year=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning arXiv preprint arXiv:2506.07218 , year=

Reference 11

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source=arxiv_source observed=2026-08-02T03:20:41.115488Z digest=sha256:5385a7832ee5bd07cc86250dc7b44bc6f11ee90a381dd2c8647589c280004a03

Observation 37cd9f84-d5c6-4ae7-99ec-9f3df4ec3bf2 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages =.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the IEEE/CVF International Conference on Computer Vision , pages =

Reference 12

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source=arxiv_source observed=2026-08-02T03:20:41.119447Z digest=sha256:e85ae0d61d0672f4ddb7e41c335875e684763e8d445ce0397b9b8e09e3c10a70

Observation 16c75267-7b7e-4d91-8939-5c284401d55e · outbound

This paper cites Perception-Aware Policy Optimization for Multimodal Reasoning.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Perception-Aware Policy Optimization for Multimodal Reasoning

Reference 13

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source=arxiv_source observed=2026-08-02T03:20:41.123647Z digest=sha256:e31b3f6edab3b20ab366b41be5eecc4fcc9c260d0cf63d741ade2a418f550fd6

Observation 5a857210-39a5-4f1c-90db-cfc8e66b6613 · outbound

This paper cites arXiv preprint arXiv:2510.09285 , year=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning arXiv preprint arXiv:2510.09285 , year=

Reference 14

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source=arxiv_source observed=2026-08-02T03:20:41.127728Z digest=sha256:894319aca0bbef2acc9f2df58d784e647c5ef086c6919d5215dea8e4427514d5

Observation df2de53d-6001-4909-9b35-3c0a7693d870 · outbound

This paper cites Visually-Guided Policy Optimization for Multimodal Reasoning.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Visually-Guided Policy Optimization for Multimodal Reasoning

Reference 15

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source=arxiv_source observed=2026-08-02T03:20:41.131609Z digest=sha256:2081676eb1cbef1a34c9adc34a7af0f86f4256410349fc10225daf28c3472573

Observation 4e9af9d2-bf31-4dcb-87b6-d3754817e9f1 · outbound

This paper cites PRPO: Perception-Reinforced Policy Optimization via Token-Level Dynamic Advantage Reshaping.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning PRPO: Perception-Reinforced Policy Optimization via Token-Level Dynamic Advantage Reshaping

Reference 16

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source=arxiv_source observed=2026-08-02T03:20:41.136332Z digest=sha256:5c92e8bda29bd3e47b8a6827adec1758ddf7913ef8ec7c60fa00031fc9417a35

Observation 4b2f0927-3c86-4667-8ea6-39c3887b4fd1 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 17

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source=arxiv_source observed=2026-08-02T03:20:41.140552Z digest=sha256:f48d0e3a5e11f9e30865e7eea833af1740820830807639bd83e8b45b9088b801

Observation c1da4876-3877-4c48-8a6d-edcaf33b5370 · outbound

This paper cites arXiv e-prints , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning arXiv e-prints , pages=

Reference 18

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source=arxiv_source observed=2026-08-02T03:20:41.144244Z digest=sha256:6529d4d21a8953673cc4133c2235e9e6216331726b921128d47cd522458575bc

Observation 03766e84-061f-41f4-9881-13016b986e34 · outbound

This paper cites CF-VLM:CounterFactual Vision-Language Fine-tuning.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning CF-VLM:CounterFactual Vision-Language Fine-tuning

Reference 19

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source=arxiv_source observed=2026-08-02T03:20:41.148082Z digest=sha256:a934837c317c845e2a09457ebe1dd70621dedaa4a2c0b868b08e4bab01035729

Observation bade137f-4194-4dfc-bd1d-83c167505483 · outbound

This paper cites an unresolved cited work.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Unresolved cited work

Reference 20

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source=arxiv_source observed=2026-08-02T03:20:41.152152Z digest=sha256:5605c614c9e5b10499b1d752e86d14d1632857b688b3838042bea87572b80bc7

Observation fccf4fab-38cf-48a1-aabc-a5b3c6b591c3 · outbound

This paper cites International Conference on Learning Representations , volume=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning International Conference on Learning Representations , volume=

Reference 21

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source=arxiv_source observed=2026-08-02T03:20:41.156053Z digest=sha256:8394160d4d73b7c62c7546a738edf6cfbc7cdee4c9b0df6936bb98838f841c33

Observation 6c87f0f3-be86-442d-a9a0-e1213ccbdff5 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 22

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source=arxiv_source observed=2026-08-02T03:20:41.159748Z digest=sha256:09a0f1b3cf06211650face402f9569ba514e4dda08923f821f16daf101e0ce26

Observation 23dabc44-cfef-43e4-9455-b34abf979ac4 · outbound

This paper cites European Conference on Computer Vision , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning European Conference on Computer Vision , pages=

Reference 23

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source=arxiv_source observed=2026-08-02T03:20:41.163405Z digest=sha256:a2b7aaf5b31fdfa6ae9104fb5a8be25c2ef991cc953c5f575c1ab8ff6a8b30b9

Observation 050cad7b-6532-42ee-a5b0-791759027144 · outbound

This paper cites LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts

Reference 24

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source=arxiv_source observed=2026-08-02T03:20:41.167563Z digest=sha256:36643d3389a48745e452ad7a8f71dffa3a41b67d90fadb16b315f653820e1454

Observation f0bdd938-5255-4b4a-9df9-04a530486cfc · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 25

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source=arxiv_source observed=2026-08-02T03:20:41.172208Z digest=sha256:7a5707d36a36434825e0dcaffecfd7e8aca66ae20fd45dab77f99fe9bdb5c17e

Observation 30e21131-e30c-4264-a60d-559dbcd68bb5 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 26

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source=arxiv_source observed=2026-08-02T03:20:41.175902Z digest=sha256:46bb1ca0a99897799e3834a787d7c22c93fe19bd100cfdaa0e63b0b5aec3b11a

Observation aa19fba9-2432-4f92-b33b-c042f3423469 · outbound

This paper cites 2024 , month = may, howpublished =.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning 2024 , month = may, howpublished =

Reference 27

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source=arxiv_source observed=2026-08-02T03:20:41.179957Z digest=sha256:f423b2b3e077e63f9f6d3a725b026ec6fc8516c8893fb7bacfcfe415a7677f44

Observation e55873ec-38b4-42b7-ac90-e3268fb95f9b · outbound

This paper cites an unresolved cited work.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Unresolved cited work

Reference 28

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source=arxiv_source observed=2026-08-02T03:20:41.183889Z digest=sha256:ff6dcf6286dcba529bd1dedb282a17c200c73478e12a5455620797d2e550e613

Observation e6afbab4-89b5-4b16-a117-d63251e86a9f · outbound

This paper cites 2024 , month = dec, howpublished =.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning 2024 , month = dec, howpublished =

Reference 29

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source=arxiv_source observed=2026-08-02T03:20:41.187886Z digest=sha256:c5303a06c576f794d5ba587b26797d56510375a4575298899b2dd7c10324168b

Observation 1e0d0e07-0b14-461d-8ecc-7f9e7bc05fbb · outbound

This paper cites an unresolved cited work.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Unresolved cited work

Reference 30

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source=arxiv_source observed=2026-08-02T03:20:41.191755Z digest=sha256:e7b9288c3533de40c6998e546113831096f22b7c13056bb2d05591b0f54cc187

Observation 2d25c3fe-f8cb-4c47-ab89-0e73e75513d3 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 31

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source=arxiv_source observed=2026-08-02T03:20:41.195442Z digest=sha256:cf75a9dd2e10431fd0673d3dbb3e9b86518d67e314b8bf05980d4ba9b7207519

Observation 51611e9f-0453-4014-a84a-a2a6033b3a52 · outbound

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

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning LLaVA-OneVision: Easy Visual Task Transfer

Reference 32

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source=arxiv_source observed=2026-08-02T03:20:41.199785Z digest=sha256:dd596a88e0e88ad4fbf9845d78763fee03424fcce096da711b490edf01b47a77

Observation 1695f712-e412-4c6f-af1d-00176ee54f5e · outbound

This paper cites LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training

Reference 33

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source=arxiv_source observed=2026-08-02T03:20:41.204065Z digest=sha256:a091d689936e64079f03c6404d5816974c984b172686efed10751296eb0bd107

Observation 98c9f657-6b68-4eb6-8288-294bb38a9e9a · outbound

This paper cites LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model

Reference 34

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source=arxiv_source observed=2026-08-02T03:20:41.208153Z digest=sha256:5a1988df3d9340493a9ae027f87a4a68d0b5f49a4783d0fa88e17146df303912

Observation f0ca5672-f31d-48a6-b150-90da9a97faf1 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 35

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source=arxiv_source observed=2026-08-02T03:20:41.212250Z digest=sha256:68cdb82384a5d752002ddc796acc30f64865b401d2618c178986062e9049db52

Observation b5b0b13f-0f76-4cf7-99a4-62422ab98184 · outbound

This paper cites CPGD: Toward Stable Rule-based Reinforcement Learning for Language Models.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning CPGD: Toward Stable Rule-based Reinforcement Learning for Language Models

Reference 36

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source=arxiv_source observed=2026-08-02T03:20:41.216453Z digest=sha256:7b12915a0ef2015d57b62b99757dbb06a9772573e681e64d041ccbd6e7154293

Observation 8eb62959-dc9a-4e5e-8da8-cd81bdc271bc · outbound

This paper cites an unresolved cited work.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Unresolved cited work

Reference 37

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source=arxiv_source observed=2026-08-02T03:20:41.220552Z digest=sha256:7afb5db1a91edfa0772a59761bea50fddc066bdd2d710477048da882ef21750f

Observation 3b2f3b5e-95e9-43e5-89b4-e24edf9eb807 · outbound

This paper cites SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Reference 38

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no resolver link, observed 2026-08-02T03:20:41.224809Z

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source=arxiv_source observed=2026-08-02T03:20:41.224809Z digest=sha256:dc59f02a240c4d85a2ea0974e1065b24b6ce995fd994d9d714c4208fc7fd9c73

Observation 8a3f002b-3c6f-45f7-8151-317c55b11046 · outbound

This paper cites arXiv preprint arXiv:2506.04559 , year=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning arXiv preprint arXiv:2506.04559 , year=

Reference 39

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no resolver link, observed 2026-08-02T03:20:41.229312Z

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source=arxiv_source observed=2026-08-02T03:20:41.229312Z digest=sha256:680084af9fc1fdf540561b67b62d55788d5f06e74a4662c5273fad9b2c825042

Observation 576237ce-1c56-4d04-b8a5-eef74665169d · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 40

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source=arxiv_source observed=2026-08-02T03:20:41.233432Z digest=sha256:835f4ab666167d52312424733a37d3c368d3104f1bd907af98d2f68b1b73152d

Observation 606a8c52-2679-4953-a487-9042aea00642 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 41

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source=arxiv_source observed=2026-08-02T03:20:41.237810Z digest=sha256:f88224955cdf7fb268d3cf4af98dc4ff84970be5f823514897c1a3a16d25457c

Observation 93a670d9-fc5d-47b9-a957-a62cfc7364c6 · outbound

This paper cites arXiv preprint arXiv:2601.06801 , year=.

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning arXiv preprint arXiv:2601.06801 , year=

Reference 42

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source=arxiv_source observed=2026-08-02T03:20:41.241752Z digest=sha256:92fc983e16d060343b8aa8296ce1b4c9f432f4d08aaff8dbcfa3c3e2ec4562da

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