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Paper Citation Record · LEDGER

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis

As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2608.05249.

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

pith.paper-citation-record.v1
2608.05249 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:13:26.922092Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

61 of 61 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bbbd0fb4-85f1-454b-b22f-ca54c55ef7ad · outbound

This paper cites Introducing GPT-5.4.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Introducing GPT-5.4

Reference 1

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:25.189539Z digest=sha256:77a25d0d8223fc6ece25deacbde31f03063bde0ed6cea9495c6e2456d8a9fc88

Observation d4f4be81-3b5c-4eb9-8d6d-d70c159e3316 · outbound

This paper cites Qwen3-VL Technical Report.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Qwen3-VL Technical Report

Reference 2

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source=pdf_text observed=2026-08-08T17:13:25.253066Z digest=sha256:9fa724aad157925c170c86d26bab5464c3e919c1fb974b40ad08b7f761fcc6f7

Observation eab7a051-d5bd-43fb-9752-d1bf0a820f14 · outbound

This paper cites MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct

Reference 3

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source=pdf_text observed=2026-08-08T17:13:25.317701Z digest=sha256:1905bba8f759f19bcdd5a32d2f5f804c87b6c864cd5d8b2a963e69d77ba79b02

Observation fa99a0dc-e1d9-476c-a108-b9acad9731f4 · outbound

This paper cites Mulberry: Empowering MLLM with o1-like reasoning and reflection via collective monte carlo tree search.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Mulberry: Empowering MLLM with o1-like reasoning and reflection via collective monte carlo tree search

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:25.350439Z digest=sha256:01141927c1940952a98ed016c1d1a5c256d9aefcddc9560bbe17f1043a34d420

Observation aee064f1-f62c-4416-acf7-cba6b9c06572 · outbound

This paper cites LLaVA-CoT: Let Vision Language Models Reason Step-by-Step.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis LLaVA-CoT: Let Vision Language Models Reason Step-by-Step

Reference 5

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source=pdf_text observed=2026-08-08T17:13:25.356753Z digest=sha256:78bb59ef93deced628d9180a676dec8fe5a97de8ff63a353199a260e6583831e

Observation 4d77cb9a-dc1b-4476-9f86-10805ddb2bde · outbound

This paper cites Oasis: One Image is All You Need for Multimodal Instruction Data Synthesis.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Oasis: One Image is All You Need for Multimodal Instruction Data Synthesis

Reference 6

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source=pdf_text observed=2026-08-08T17:13:25.434877Z digest=sha256:67de066b62c506afe53d143c8a2c3649c711e7b062fba7005531caaeda27e4c3

Observation c94405ad-f735-413f-b423-fcf14d6c2427 · outbound

This paper cites an unresolved cited work.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-08T17:13:25.504828Z digest=sha256:2df360209e8b8a1c480d05565709ee938892eed218029f3c24dbaf637c9001ba

Observation 20378077-12fd-4c83-a0e5-e7f1a8d56942 · outbound

This paper cites Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains

Reference 9

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source=pdf_text observed=2026-08-08T17:13:25.538597Z digest=sha256:72dd0d228f3031550f94d5bd2eaa0e164bc9e600f1c203a889dc519aec41dcaf

Observation d3ed71d4-d9be-44bd-af14-320fad3b5962 · outbound

This paper cites Alternating reinforcement learning for rubric-based reward modeling in non-verifiable LLM post-training.arXiv preprint arXiv:2602.01511, 2026.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Alternating reinforcement learning for rubric-based reward modeling in non-verifiable LLM post-training.arXiv preprint arXiv:2602.01511, 2026

Reference 10

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source=pdf_text observed=2026-08-08T17:13:25.611475Z digest=sha256:71a96b3335686a55e086ea91561d09c6047db2254dedeac2937da302a3caf0d3

Observation 074c7df1-d63a-4cde-be05-0ab561f3d6cd · outbound

This paper cites Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Reference 11

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source=pdf_text observed=2026-08-08T17:13:25.668223Z digest=sha256:32067e0be1910ce2b917f20e89dc588e1416136ac17314fb8c3616fe88552503

Observation 31454cc5-5533-4379-aa2c-3d8b75e05f3a · outbound

This paper cites InFoBench: Evaluating instruction following ability in large language models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis InFoBench: Evaluating instruction following ability in large language models

Reference 12

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source=pdf_text observed=2026-08-08T17:13:25.696284Z digest=sha256:251721f0215a0dfeec67fa6e67e55ef3131a718bcb6dbfdba1c6c54c2d7af977

Observation d6f4bcc6-1055-455a-9355-bf3c0db2bbdf · outbound

This paper cites Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning

Reference 13

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source=pdf_text observed=2026-08-08T17:13:25.707335Z digest=sha256:844ed5c9afb89262e4bbcace8f6510c89989cd8cb72c8b7e9c03c346156893fb

Observation b3002793-658d-414a-90a3-7f8ac7c7dc11 · outbound

This paper cites Cambrian-1: A fully open, vision-centric exploration of multimodal llms.Advances in Neural Information Processing Systems, 37:87310–87356, 2024.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Cambrian-1: A fully open, vision-centric exploration of multimodal llms.Advances in Neural Information Processing Systems, 37:87310–87356, 2024

Reference 14

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source=pdf_text observed=2026-08-08T17:13:25.790380Z digest=sha256:cc6c2269862291c1b153d940887579ea76edde6ad21c50b670e4299091d346cd

Observation 53b67008-da19-4ca7-b9fd-81067528ad38 · outbound

This paper cites Seed 2.0 Model Card.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Seed 2.0 Model Card

Reference 15

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:25.855352Z digest=sha256:c3ff7dea6f9114be16c3e5b689b4444c2511d250f7af0fdc7acf7947dfe38526

Observation 66725781-3aae-42f1-8df6-8a58e16f5012 · outbound

This paper cites ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Reference 16

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source=pdf_text observed=2026-08-08T17:13:25.889313Z digest=sha256:4e6673e420db95953585fa2df725d1b555275870ad9c2b98c86d924837176c06

Observation cb8a6de7-a0d1-4dac-a638-8042208c8c64 · outbound

This paper cites Microsoft coco: Common objects in context.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Microsoft coco: Common objects in context

Reference 17

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source=pdf_text observed=2026-08-08T17:13:25.905148Z digest=sha256:6df47844f518e08030c743b8220097279a01427ca8c3f8378550a7a5eda0fab8

Observation f225b0fa-d5d9-4574-8a25-a4ac93456240 · outbound

This paper cites Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models

Reference 18

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source=pdf_text observed=2026-08-08T17:13:25.910608Z digest=sha256:ab4591552dc630a6e46ffdda505b2d7df58c298fcb50e80e315eafa39db94fc8

Observation 78783983-aa1b-438e-b0e4-4bc3bd6c4482 · outbound

This paper cites an unresolved cited work.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-08T17:13:25.916452Z digest=sha256:7a6c031c8fced20779bef1884d77fd84f79a00bfaafe5a74e31c0e088c234dfb

Observation 2cc8404a-8f16-4ec7-8f39-8bc631564e22 · outbound

This paper cites How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 20

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source=pdf_text observed=2026-08-08T17:13:25.940793Z digest=sha256:40a7c45719b0fc12854ad826627b14133de081dc97163b0b7135542321f14fde

Observation f1f80f45-9484-4442-bc68-1e528424f735 · outbound

This paper cites Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning

Reference 21

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source=pdf_text observed=2026-08-08T17:13:25.992116Z digest=sha256:53d3bc93b30fbc84ea12fa44db4940889db466e3765afacb65b1a6879e5bbd62

Observation 1d615319-06fa-4995-a5f3-564688c3b98c · outbound

This paper cites Vizwiz grand challenge: Answering visual questions from blind people.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Vizwiz grand challenge: Answering visual questions from blind people

Reference 22

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source=pdf_text observed=2026-08-08T17:13:25.996787Z digest=sha256:85138fb6740d9168c2be58e58d0e23c4ac40df9ef1fd3081d8cc5ef01ea24156

Observation d6621171-0bb7-4cf9-a371-f652107c6574 · outbound

This paper cites Visually Dehallucinative Instruction Generation: Know What You Don't Know.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Visually Dehallucinative Instruction Generation: Know What You Don't Know

Reference 23

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source=pdf_text observed=2026-08-08T17:13:26.001095Z digest=sha256:b57ec793940f293451216bb5af9d15db289ffa7ed82f652516950fd94c8608f9

Observation b6c036b1-8a5a-4a08-810c-667bd23e0559 · outbound

This paper cites Shamma, Michael S.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Shamma, Michael S

Reference 24

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.005536Z digest=sha256:a3290fa781ef6321814965a1432ec85b94534c0f98dffbf84001845f258d50f6

Observation 9ab7595b-4d01-4ca5-ae50-fa5b75d6cea9 · outbound

This paper cites Hudson and Christopher D.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Hudson and Christopher D

Reference 25

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.011211Z digest=sha256:6463f48005b3e90a512d96a30e40aa211865643d0f5729bbea66e4d538f449fc

Observation cdfc299c-6d6c-423b-9d5a-1b6f30a74bef · outbound

This paper cites Dvqa: Understanding data visualizations via question answering.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Dvqa: Understanding data visualizations via question answering

Reference 26

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.016063Z digest=sha256:a4c54604b0d562a6c83b2693874e890c8cdc921ce940a7930bc68cf7745acb25

Observation 3baaa5d1-c38b-47e8-a1e6-b337a0f28737 · outbound

This paper cites Donut: Document understanding transformer without ocr.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Donut: Document understanding transformer without ocr

Reference 27

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.020619Z digest=sha256:8b70bc69d7450bfde09dc515f28f6493b1ed4c6c9674207801e2debc0c928cee

Observation c4c2cf58-85e1-4a9c-9d72-cfc0dda00e0d · outbound

This paper cites Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models

Reference 28

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source=pdf_text observed=2026-08-08T17:13:26.025156Z digest=sha256:0670af28946de2bcd4312ad675c6b983d820747ce355ff3427869ade794699c8

Observation 181bbf3e-25e8-4479-8ee5-781dc0e59989 · outbound

This paper cites A diagram is worth a dozen images.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis A diagram is worth a dozen images

Reference 29

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source=pdf_text observed=2026-08-08T17:13:26.029929Z digest=sha256:08a9252f3423a7b4e6f2a418738ec7b9de456ebb795d55b84846dbce154b0087

Observation dd9c2897-ffbc-406d-b54b-63c56c1946b3 · outbound

This paper cites ScreenQA: Large-Scale Question-Answer Pairs over Mobile App Screenshots.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis ScreenQA: Large-Scale Question-Answer Pairs over Mobile App Screenshots

Reference 30

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source=pdf_text observed=2026-08-08T17:13:26.034113Z digest=sha256:8834e24ed0476afd167c7251f897eb8afd3f110786e4e7e8a1d8053df2e0427d

Observation 7cab4f00-62f7-40d1-9b1f-c814d20e9488 · outbound

This paper cites LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding

Reference 31

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source=pdf_text observed=2026-08-08T17:13:26.039380Z digest=sha256:e3ba14b5e4444e6d9f4d6eaab2e4fd1eeb886e177a84646aa3551a3bcdc144f4

Observation 95793b90-2f10-46b9-b5fd-3a9f5965ed85 · outbound

This paper cites Docvqa: A dataset for vqa on document images.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Docvqa: A dataset for vqa on document images

Reference 32

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raw_fallback, observed 2026-08-08T17:13:28.300567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.044061Z digest=sha256:b2624725a9822b5e123ff55b4f647c8d3bc14f111c8d8bd9c1329fc365f59779

Observation 916d1ab7-c5cb-4d7f-97b0-475d858014dc · outbound

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

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Chartqa: A benchmark for question answering about charts with visual and logical reasoning

Reference 33

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source=pdf_text observed=2026-08-08T17:13:26.048832Z digest=sha256:43bee252c4f1f8d0bf3025cf7f07de88d33b937257c9405a148889389ea806e9

Observation a365ac9b-178f-478a-86b1-ad3532ab30f7 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 34

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source=pdf_text observed=2026-08-08T17:13:26.053348Z digest=sha256:80e763f334b62a3d9e91eef1313f5ee863cb4e18026a13dd9fa7b188a11b808a

Observation c122808b-f685-494f-8df5-042bfd420964 · outbound

This paper cites Ocr-vqa: Visual question answering by reading text in images.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Ocr-vqa: Visual question answering by reading text in images

Reference 35

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raw_fallback, observed 2026-08-08T17:13:28.240012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.104862Z digest=sha256:c6dcec1c92c8d3118b3f18283da3d3ae02cee54e821824587ce174c853835d62

Observation f429713f-e621-4efc-b12c-0c68bc3e7a82 · outbound

This paper cites Compositional semantic parsing on semi-structured tables.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Compositional semantic parsing on semi-structured tables

Reference 36

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raw_fallback, observed 2026-08-08T17:13:28.223898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.128073Z digest=sha256:b4216e2d9780e844de62f3b5a716dde74b0007188f5b959e392dddbcb26622df

Observation c4c72c40-40e2-46ad-98d8-04d0ad4ce66b · outbound

This paper cites Iconqa: A new benchmark for abstract diagram understanding and visual language reasoning.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Iconqa: A new benchmark for abstract diagram understanding and visual language reasoning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:28.152949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.155115Z digest=sha256:6bb8a7fd786f6e33126a38d1288a1dcc442ce381ca5734c0a131fe692136f9b0

Observation e6f73a19-1da4-41bf-a858-a685e4066792 · outbound

This paper cites Clevr: A diagnostic dataset for compositional language and elementary visual reasoning.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Clevr: A diagnostic dataset for compositional language and elementary visual reasoning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:28.103105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.184297Z digest=sha256:fcf576ad4b6f11d93265ebc2e94aafbbe6eb6a99bf149ff0106abbd1deca9c19

Observation 6d2607da-9cd2-400c-bd00-8d1fff846d10 · outbound

This paper cites Tallyqa: Answering complex counting questions.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Tallyqa: Answering complex counting questions

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:28.088458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.188249Z digest=sha256:afb485d780bb322b315fc0f90a609f50540bc23f1f8b1fd5324c58f2b8ad6f44

Observation bdfc0a12-ee5f-4e2e-bc30-01955c88abf6 · outbound

This paper cites G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.193653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.193653Z digest=sha256:12dea6395d10345e1f89da3b1a316fed508fcc015fbbac997551b94802eb5a24

Observation ab97f596-b2db-4d68-800c-659f9b6dd19c · outbound

This paper cites Measuring multimodal mathematical reasoning with math-vision dataset.Advances in Neural Information Processing Systems, 37:95095–95169, 2024.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Measuring multimodal mathematical reasoning with math-vision dataset.Advances in Neural Information Processing Systems, 37:95095–95169, 2024

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.198541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.198541Z digest=sha256:4b229bb5753637630cad581101632bb5a53387304796ba308ec92a6826dbbc19

Observation 10dc1878-4909-4f33-b1c1-a9e56435416b · outbound

This paper cites Raven: A dataset for relational and analogical visual reasoning.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Raven: A dataset for relational and analogical visual reasoning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:28.064382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.202902Z digest=sha256:a95095e0a73bc2ff22e70ee47f9f71e9a8772efde1692fb8d99175191080cdcc

Observation e1144657-2cef-4a6f-a92f-c5f128c1b7dc · outbound

This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.207581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.207581Z digest=sha256:8c93afbe113d3adbbeb77846551e0d3998a396a7af83650d638a35c2676763fd

Observation f596d7f7-ae26-4293-9dcd-e629250145de · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:28.046794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.236779Z digest=sha256:3ad2a71a8d31bc8e92722d2e8c4af750fffe23ea3a5bfa6b770784eea785f905

Observation 63e9de72-b78a-4f9e-965f-0981542128b0 · outbound

This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.317500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.317500Z digest=sha256:a7f5c8404b10083aac8e2e39fe9401334cb0df3d34bdfdc93b993769a4a046d0

Observation 493a1714-0e5d-42b3-9e73-fa73398c8b58 · outbound

This paper cites Qwen3.5.https://qwen.ai/blog?id=qwen3.5, 2026.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Qwen3.5.https://qwen.ai/blog?id=qwen3.5, 2026

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:27.980922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.415496Z digest=sha256:d67cb74274335c9261b66d9cbab593e8a5941f7cc4bcc499a3adf61c92775e33

Observation 0406641e-16e3-4a65-b912-43c1c0791f4d · outbound

This paper cites LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.532378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.532378Z digest=sha256:4c197d390a2a3faba65b8131a1c6c1ef0849754ea5e43dc501d6b05a4e085445

Observation 8e4efd0d-59eb-416a-9989-6e7aa5f279b0 · outbound

This paper cites Mmbench: Is your multi-modal model an all-around player? In European conference on computer vision, pages 216–233.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Mmbench: Is your multi-modal model an all-around player? In European conference on computer vision, pages 216–233

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.545256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.545256Z digest=sha256:93e20b027a191ab0818f4f3b126205360c4b89fda05bd9a3f190e64112ef7f94

Observation 54d662d8-e2e9-4e53-bf17-da6b1aebd5cf · outbound

This paper cites Mme: A comprehensive evaluation benchmark for multimodal large language models.Advances in Neural Information Processing Systems, 38, 2026.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Mme: A comprehensive evaluation benchmark for multimodal large language models.Advances in Neural Information Processing Systems, 38, 2026

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:27.903221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.557534Z digest=sha256:f3bec319eb837484a8523be300020854b4c59e8f931bb79f9ad1e196965f21f4

Observation dc02aaa0-93c2-421f-b76f-5ea8d3104256 · outbound

This paper cites Are we on the right way for evaluating large vision-language models?Advances in Neural Information Processing Systems, 37:27056–27087, 2024.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Are we on the right way for evaluating large vision-language models?Advances in Neural Information Processing Systems, 37:27056–27087, 2024

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.594626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.594626Z digest=sha256:3c5eade5ca11a3b265bc5f812e2ed17ed3d150b8db34e48c1200d03ed65ce70f

Observation c996c68b-0240-4af9-908d-f5fe5e93e808 · outbound

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

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.599460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.599460Z digest=sha256:95cd5567accb72b44c03a8ecf91ee0ef18ea1d39f8356770a332acdba39f54fc

Observation b5ac2766-49ff-4252-b7b6-7f1a9bc6296f · outbound

This paper cites Ocrbench: on the hidden mystery of ocr in large multimodal models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Ocrbench: on the hidden mystery of ocr in large multimodal models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.682248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.682248Z digest=sha256:64bf7928ec7659773e241a514f43aebc52d8bfb8c11291e93325697e5171e391

Observation f85070c1-1962-4b10-9124-6dbfaace9535 · outbound

This paper cites Infographicvqa.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Infographicvqa

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.740499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.740499Z digest=sha256:5b2add73644fcea4dc8cfaa5462e935c5c7c622eea94079a20ebd3cad35028f5

Observation bb23239e-eaa4-4e9a-8a53-7063e9784fc6 · outbound

This paper cites Charxiv: Charting gaps in realistic chart understanding in multimodal llms.Advances in Neural Information Processing Systems, 37:113569–113697, 2024.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Charxiv: Charting gaps in realistic chart understanding in multimodal llms.Advances in Neural Information Processing Systems, 37:113569–113697, 2024

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:27.747015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.790069Z digest=sha256:7ff419dbfe998f8f90c864e46ba1a600a104ba2286ed2f89fead6c775d3e6b90

Observation c5c58c3f-cf17-4536-b405-30d0bd95a173 · outbound

This paper cites Dynamath: A dynamic visual benchmark for evaluating mathematical reasoning robustness of vision language models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Dynamath: A dynamic visual benchmark for evaluating mathematical reasoning robustness of vision language models

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:27.683662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.808841Z digest=sha256:0004cbb62f79d43abf370674aaff7cb5e56791c339c19e00561537aa3ea4fe2c

Observation f055aed7-104b-45c2-b333-5414663d6db0 · outbound

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

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.813213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.813213Z digest=sha256:f333593b90246e4683ecd655aa1e3ad536d3a31432b1b480f50e725be1472dd5

Observation 9c07e80c-8c6e-4c9b-bf64-63ffcb13b6a7 · outbound

This paper cites VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.818239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.818239Z digest=sha256:04e20c5eb73a669f304e051a4a6ecc2e996ffa5ade8d9bc16ad2f40f056c6831

Observation 5a064eed-8027-4c0d-aa53-ed40ede678cc · outbound

This paper cites Teaching CLIP to Count to Ten.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Teaching CLIP to Count to Ten

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.824188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.824188Z digest=sha256:5adc7e870348d28a91f0c4f4dc1f70d060fd818ea09b6ab072f306b7db8ca6ea

Observation 2e65b108-92c2-4bbe-87e8-bdf2f6443239 · outbound

This paper cites Gemini 3 Flash: Frontier intelligence built for speed.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Gemini 3 Flash: Frontier intelligence built for speed

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:13:27.624851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:26.829420Z digest=sha256:5f755f766114ecd6b55980c3dd6e033b924edd503ec76c16e29f080b752b1dcf

Observation f30d611f-84a1-464d-9887-8b5bbaecf849 · outbound

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

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis LLaVA-OneVision: Easy Visual Task Transfer

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:26.922092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:26.922092Z digest=sha256:d243dce51579b6f15fc3836dd44150faaa77c1da557322c538deb78b74a769fd

Observation f90efd05-8d87-4757-830d-b03b58f172ba · outbound

This paper cites an unresolved cited work.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Unresolved cited work

Reference 772

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:13:28.706527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T17:13:25.702217Z digest=sha256:37875099a93237b7e2bc1424c110578efef88396d1ea6b0bacc3aa92c58e0141

Observation 7117009a-84ae-4a84-bcbf-78d3610513e2 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis Instruction-Following Evaluation for Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:25.500185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:25.500185Z digest=sha256:6cfba7f83f4d172a1e93e821282742baccd913bf1964c44aa037996f20714b14

Pith citing papers

No inbound Pith citation observations are available.