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Paper Citation Record · LEDGER

Improving Multimodal Reasoning via Worst Dimension Optimization

As of 22 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2606.07801.

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

pith.paper-citation-record.v1
2606.07801 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T21:55:57.691185Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

  • verified exact19
  • verified fuzzy0
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e99716a8-8d0d-4069-95af-b38b06c19a9c · outbound

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

Improving Multimodal Reasoning via Worst Dimension Optimization Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 1

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local_arxiv, observed 2026-07-02T17:37:14.804063Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 42ee378d-0bf6-42a0-b4d0-4eaeb16dfbb3 · outbound

This paper cites Dense point clouds matter: Dust-gs for scene reconstruction from sparse viewpoints.

Improving Multimodal Reasoning via Worst Dimension Optimization Dense point clouds matter: Dust-gs for scene reconstruction from sparse viewpoints

Reference 2

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:75e55934c70126245dd0fd9402e70fbb35ad69ba7657ad0e667b32677423d1fd

Observation 1e87c439-2e8c-479d-b3b7-fb1e0b63ebf1 · outbound

This paper cites Benchmarking multimodal cot reward model stepwise by visual program.

Improving Multimodal Reasoning via Worst Dimension Optimization Benchmarking multimodal cot reward model stepwise by visual program

Reference 3

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:c98eaacb846169f5e856835b30a0dae10bc7f57065914b85380194ba2aacb595

Observation 90d15e96-d409-4d4a-9b50-c4a9c5f5f5ca · outbound

This paper cites rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking.

Improving Multimodal Reasoning via Worst Dimension Optimization rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 4

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local_arxiv, observed 2026-07-02T17:37:14.796624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:a8f8300f8b9af0ced785b341c7ac428f37c6ec16b661ce29aff367b9ffedaaf9

Observation 19bb96d0-9e8c-4f33-afbe-a965f5575564 · outbound

This paper cites Learning an efficient optimizer via hybrid-policy sub-trajectory balance.arXiv preprint arXiv:2511.00543, 2025a.

Improving Multimodal Reasoning via Worst Dimension Optimization Learning an efficient optimizer via hybrid-policy sub-trajectory balance.arXiv preprint arXiv:2511.00543, 2025a

Reference 5

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arxiv_id, observed 2026-07-02T17:37:14.799262Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:e393d56704521085f0f386a7f352b95861e3e373f3b06f5c7be7e293ecafc07f

Observation 24ae5da2-89f5-40b5-8ac2-44bdda8cd960 · outbound

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

Improving Multimodal Reasoning via Worst Dimension Optimization Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 6

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local_arxiv, observed 2026-07-02T17:37:14.801732Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation c4b1e95f-ddcc-40fe-9b71-065d8c920170 · outbound

This paper cites RAM: Recover Any 3D Human Motion in-the-Wild.

Improving Multimodal Reasoning via Worst Dimension Optimization RAM: Recover Any 3D Human Motion in-the-Wild

Reference 7

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:fe0947bb5ac17b49ef8064ea568290ba7c8d531357b8e5f7e9d8f86f88d84d8c

Observation 25bd7bbc-51e2-4960-a9a7-2369903036db · outbound

This paper cites A diagram is worth a dozen images.

Improving Multimodal Reasoning via Worst Dimension Optimization A diagram is worth a dozen images

Reference 8

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Observation df5a02d2-53bd-4e78-9d48-61a9d1396adb · outbound

This paper cites Nv-embed: Improved techniques for train- ing llms as generalist embedding models.

Improving Multimodal Reasoning via Worst Dimension Optimization Nv-embed: Improved techniques for train- ing llms as generalist embedding models

Reference 9

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:3daf1bd4b475fe6644e1c255076e8e06474125faa502d4446243423f0d925b3b

Observation b252fc26-6f34-4ea1-a859-b48504e39f71 · outbound

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

Improving Multimodal Reasoning via Worst Dimension Optimization LLaVA-OneVision: Easy Visual Task Transfer

Reference 10

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation d8c4b3ab-19e6-4b6c-b1d3-b51974ff04ed · outbound

This paper cites Human motion instruction tuning.

Improving Multimodal Reasoning via Worst Dimension Optimization Human motion instruction tuning

Reference 11

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:6436fa778a396e8da83c50d84afdc6fe91d358e1defd3af2ee9e4e96b065eaab

Observation 2da19a14-8f2a-4170-a16d-5140d9c2529b · outbound

This paper cites Multiple human motion understanding.

Improving Multimodal Reasoning via Worst Dimension Optimization Multiple human motion understanding

Reference 12

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:0f75ed95f39283085ac7f7c9787472b8a806a3a67fd252cb5f0eb0c843cee39e

Observation 5123f71f-8df4-4444-b6a4-f8e799718f51 · outbound

This paper cites Image semantic segmentation via chain- of-thought prompts.

Improving Multimodal Reasoning via Worst Dimension Optimization Image semantic segmentation via chain- of-thought prompts

Reference 13

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:b9b3c826870caff7f7dd13f8dd81b43cdeab88ca81d3c53947fbdbc8f2996bc0

Observation dbdd4309-6d32-4d6a-a1b8-24a3a0c1e1f8 · outbound

This paper cites Graph Canvas for Controllable 3D Scene Generation.

Improving Multimodal Reasoning via Worst Dimension Optimization Graph Canvas for Controllable 3D Scene Generation

Reference 14

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arxiv_id, observed 2026-07-02T17:37:14.788803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 3c249712-ad54-499f-be1f-103e69da9a96 · outbound

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

Improving Multimodal Reasoning via Worst Dimension Optimization Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts

Reference 15

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:89566fb641aae39a2ec896d9f588d3491d7ccdfdab8d76d144b80dd1925d0069

Observation 758b02c2-9bbd-4c5b-96f8-58ff6ff3930e · outbound

This paper cites Ovis: Structural Embedding Alignment for Multimodal Large Language Model.

Improving Multimodal Reasoning via Worst Dimension Optimization Ovis: Structural Embedding Alignment for Multimodal Large Language Model

Reference 16

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arxiv_id, observed 2026-07-02T17:37:14.785734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:3a89f8d2360364033a66edb636cda92172d52d4e73b77b9d18dc7ec79e3839f4

Observation 2f0c2787-b8eb-4ac6-ac3b-af4567d8c2c1 · outbound

This paper cites Improve Mathematical Reasoning in Language Models by Automated Process Supervision.

Improving Multimodal Reasoning via Worst Dimension Optimization Improve Mathematical Reasoning in Language Models by Automated Process Supervision

Reference 17

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local_arxiv, observed 2026-07-02T17:37:14.779823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation d3ad855b-e1b8-4020-baf8-8e4dfab5d167 · outbound

This paper cites Ursa: Understanding and verifying chain-of- thought reasoning in multimodal mathematics.arXiv e- prints, pages arXiv–2501,.

Improving Multimodal Reasoning via Worst Dimension Optimization Ursa: Understanding and verifying chain-of- thought reasoning in multimodal mathematics.arXiv e- prints, pages arXiv–2501,

Reference 18

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Observation 42c34cba-879e-4744-bcf6-e8cacf0e4451 · outbound

This paper cites Chartqa: A bench- mark for question answering about charts with visual and logical reasoning.

Improving Multimodal Reasoning via Worst Dimension Optimization Chartqa: A bench- mark for question answering about charts with visual and logical reasoning

Reference 19

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Observation 97037d53-e865-4a65-b893-5b4ac21661ea · outbound

This paper cites Training vision-language pro- cess reward models for test-time scaling in multimodal rea- soning: Key insights and lessons learned.

Improving Multimodal Reasoning via Worst Dimension Optimization Training vision-language pro- cess reward models for test-time scaling in multimodal rea- soning: Key insights and lessons learned

Reference 20

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 33052ebb-9bef-4d81-9bd2-ead709adf165 · outbound

This paper cites Mutual reason- ing makes smaller llms stronger problem-solver.

Improving Multimodal Reasoning via Worst Dimension Optimization Mutual reason- ing makes smaller llms stronger problem-solver

Reference 21

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Observation 929facf5-a1b9-4ebb-8c0d-5f5ea592d403 · outbound

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Improving Multimodal Reasoning via Worst Dimension Optimization Unresolved cited work

Reference 22

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Observation ce4a326d-4a84-4e1d-98fb-fbab353ca368 · outbound

This paper cites Intrinsic entropy of context length scaling in llms.

Improving Multimodal Reasoning via Worst Dimension Optimization Intrinsic entropy of context length scaling in llms

Reference 23

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Observation f87b0301-7f26-4395-b342-8f183e42b82f · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Improving Multimodal Reasoning via Worst Dimension Optimization Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 24

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local_arxiv, observed 2026-07-02T17:37:14.782921Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:2ae1bb347c9078257f0dcf7072ce47a1ca209308c02dfe1fd9a6a0dd217aa6b5

Observation ae37ca32-ec1b-424b-84a7-296d7e773a93 · outbound

This paper cites Llamav-o1: Rethinking step-by-step visual reasoning in llms.

Improving Multimodal Reasoning via Worst Dimension Optimization Llamav-o1: Rethinking step-by-step visual reasoning in llms

Reference 25

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:e47a20b70d64a517395d8b5333d42235a9d1bd8113cece77a9363e8e810b2607

Observation e942fe3f-4786-4ee7-9603-7cfadce43950 · outbound

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

Improving Multimodal Reasoning via Worst Dimension Optimization Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 26

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local_arxiv, observed 2026-07-02T17:37:14.791207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 2a6a6c27-42be-4e86-9480-70f58ec5bcb4 · outbound

This paper cites Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization.

Improving Multimodal Reasoning via Worst Dimension Optimization Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization

Reference 27

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local_arxiv, observed 2026-07-02T17:37:14.795919Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:1cfca529857acb92b3116a8a19aeff83f2753bcdac0bd6fd4e56f2b8d2662e51

Observation b5cdf414-e7bc-41d9-8cf2-6a75999e1cc9 · outbound

This paper cites Multi-step problem solving through a verifier: An empir- ical analysis on model-induced process supervision.

Improving Multimodal Reasoning via Worst Dimension Optimization Multi-step problem solving through a verifier: An empir- ical analysis on model-induced process supervision

Reference 28

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:d3529edac3334e43288c48bdd24d7610a272f7f4fac5831db7c3825d43898609

Observation ed2bd02a-a54d-46d2-bded-3debe6d62791 · outbound

This paper cites VisualPRM: An Effective Process Reward Model for Multimodal Reasoning.

Improving Multimodal Reasoning via Worst Dimension Optimization VisualPRM: An Effective Process Reward Model for Multimodal Reasoning

Reference 29

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arxiv_id, observed 2026-07-02T17:37:14.806679Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:11a098e3a64263dfe76265655156c753723202daed04bf0d249d160eaabede11

Observation 8438769d-4f5a-4628-8cbe-782ad75e184d · outbound

This paper cites Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS.

Improving Multimodal Reasoning via Worst Dimension Optimization Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS

Reference 30

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arxiv_id, observed 2026-07-02T17:37:14.794057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:37db3dd20aa9aba4151a30768cddb7a5524b5680227d31eefabe2bfe131fdd62

Observation 1fa0048c-73b5-486d-9728-3d95bf458f43 · outbound

This paper cites Llava-cot: Let vi- sion language models reason step-by-step.

Improving Multimodal Reasoning via Worst Dimension Optimization Llava-cot: Let vi- sion language models reason step-by-step

Reference 31

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:a149101a2e99c6ab958a059d50874435065084297e32bee6e5bab214843b41ae

Observation c7a61164-452e-48ba-9eb5-6f29d76accd6 · outbound

This paper cites 3dsceneeditor: Controllable 3d scene editing with gaussian splatting.

Improving Multimodal Reasoning via Worst Dimension Optimization 3dsceneeditor: Controllable 3d scene editing with gaussian splatting

Reference 32

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arxiv_id, observed 2026-07-02T17:37:14.777687Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:f0318cc00e2657a733877a9f6188bc259a7dda09d4bf6bc945862d7906082bbc

Observation d65e27b7-5e6a-4f2d-a3cc-ef245e4b60f3 · outbound

This paper cites 3dsceneeditor: Controllable 3d scene editing with gaussian splatting.

Improving Multimodal Reasoning via Worst Dimension Optimization 3dsceneeditor: Controllable 3d scene editing with gaussian splatting

Reference 33

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:2b64fe7782ab2469541223ad47729c91136ace3389fc2fd0047d164b16d4b659

Observation ecabd59b-c43d-436f-9fff-09a342fea043 · outbound

This paper cites R1- onevision: Advancing generalized multimodal reasoning through cross-modal formalization.

Improving Multimodal Reasoning via Worst Dimension Optimization R1- onevision: Advancing generalized multimodal reasoning through cross-modal formalization

Reference 34

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source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:ced210d765cc46d032946ea410c6b9d4c9791dbdb2188a6a8680e684272b5f60

Observation fa942ff7-cf88-43d2-829f-3c3093c309c9 · outbound

This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

Improving Multimodal Reasoning via Worst Dimension Optimization MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 35

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local_arxiv, observed 2026-07-02T17:37:14.800932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:986b055ad63e629f752ab109f76465d4be560804c4e89c1ec0be749be8df6bed

Observation e6e906a0-c40e-4b76-b3fc-8c7fffef406a · outbound

This paper cites CountLLM: Towards Generalizable Repetitive Ac- tion Counting via Large Language Model.

Improving Multimodal Reasoning via Worst Dimension Optimization CountLLM: Towards Generalizable Repetitive Ac- tion Counting via Large Language Model

Reference 36

Resolution
unresolved
no resolver link, observed 2026-06-27T21:55:57.691185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:8978c4bfeff40edaf4925031ad61f2aacc9cb90c7b30c9dec4e923c43154f64b

Observation 6ac6dba7-02a7-4b3a-8b5f-4fd4f7bf9966 · outbound

This paper cites Mulberry: Empowering mllm with o1-like reasoning and reflection via collective monte carlo tree search.Advances in Neural Information Processing Systems, 38:29918–29952,.

Improving Multimodal Reasoning via Worst Dimension Optimization Mulberry: Empowering mllm with o1-like reasoning and reflection via collective monte carlo tree search.Advances in Neural Information Processing Systems, 38:29918–29952,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-06-27T21:55:57.691185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:6e6b943fa94aa17c54bca4edabf83105334905066095c80ae69c57fcba3fedcf

Observation 8834c047-b995-4af3-8186-267c35ef4b62 · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.

Improving Multimodal Reasoning via Worst Dimension Optimization Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

Reference 38

Resolution
unresolved
no resolver link, observed 2026-06-27T21:55:57.691185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:dd1e44efc77c43e9fe421a1c4483165dbc31a847834c5627f63565e37ff9f73e

Observation 38a49562-928f-4857-97b0-29744c044a89 · outbound

This paper cites Birch: an efficient data clustering method for very large databases.ACM sigmod record, 25(2):103–114,.

Improving Multimodal Reasoning via Worst Dimension Optimization Birch: an efficient data clustering method for very large databases.ACM sigmod record, 25(2):103–114,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-06-27T21:55:57.691185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:3cf18a55d5037b06a3a08016b6ae949c38f8910eacb373f54ec55296f9de8471

Observation 771d9f0b-3317-4172-85eb-b6f208f24f83 · outbound

This paper cites InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output.

Improving Multimodal Reasoning via Worst Dimension Optimization InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-07-02T17:37:14.769228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:8a5f5dd766e2e8ec4feca31143359c398f9f815bc8374221049930e907898521

Observation f16d2f8c-7666-4f98-9902-0b828bb51fff · outbound

This paper cites R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization.

Improving Multimodal Reasoning via Worst Dimension Optimization R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-07-02T17:37:14.803241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:77896159bf4eae10b8da09e44a55779a36673a78e7b3caf7f5e44ed56dcc9be0

Observation fc809c8a-8792-4516-8ed5-4ec02286e17d · outbound

This paper cites Psgs: Text-driven panorama sliding scene generation via gaussian splatting.arXiv preprint arXiv:2602.00463, 2026.

Improving Multimodal Reasoning via Worst Dimension Optimization Psgs: Text-driven panorama sliding scene generation via gaussian splatting.arXiv preprint arXiv:2602.00463, 2026

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-07-02T17:37:14.798473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T21:55:57.691185Z digest=sha256:82c53608bef5a02904fd882f8a40798752b6da3cc49a1d2654c8f0236c54110b

Pith citing papers

No inbound Pith citation observations are available.