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Paper Citation Record · LEDGER

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs

As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2506.00991.

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

pith.paper-citation-record.v1
2506.00991 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:55:23.813168Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

49 of 49 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved46
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 75de73e0-4ef0-4608-b89b-2c82480c529d · outbound

This paper cites INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:21.444549Z digest=sha256:9c1c1a4abfe57a39db5542dfa97f4211f57610f0d8d464d109a322c0ddac9f60

Observation cbeea8c4-3873-4d68-ab10-b5b52f0260d2 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:21.542457Z digest=sha256:9091ee156ab2be85e59d03002ebaf0bcb1f31b225f566a85cbed46060ca2afd1

Observation 3aee32aa-315c-434a-bc53-2130c1bf840d · outbound

This paper cites Qwen Technical Report.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Qwen Technical Report

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:21.690031Z digest=sha256:748cebe32b429cfe250c71470bddd8f79ca61e159b14804ef5f24164296c5352

Observation 5b3bceb4-bfae-4fed-a89d-80a6f6dfa5da · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:21.882413Z digest=sha256:d2934509323f574f1486ae9cb835ba83d9053a2e9c7a62895b17431de5f12163

Observation 739dd308-94bd-41ae-920a-d8a164809f42 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 5

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no resolver link, observed 2026-08-07T11:55:22.074429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:22.074429Z digest=sha256:b5c91cefb39d049ecf324087ad094d268e1511150c077ef71f4f3a0d72f51ce3

Observation 560d1f71-bebb-409f-9a05-5dd50b484d19 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:22.217598Z digest=sha256:4dd2e97c5c3153b0433a2490394baf0ac1e18612291efaffb02c04f45d70cb1f

Observation f31ac5c4-621a-4222-b920-3fad0a1866de · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:22.317478Z digest=sha256:7fc241206c93bd7c9fec247ed28a2f4ee415486602ed85c001d6f53affb663ed

Observation 7230ae3c-1cea-4a47-b71f-d48c68157952 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 8

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:22.439885Z digest=sha256:fd0111267916c9819eea8e75cff34de25c877ca7c83f9daff339ce42f627bb21

Observation ab8e573d-873b-48be-9752-18db9539102f · outbound

This paper cites LLMPhy: Parameter-Identifiable Physical Reasoning Combining Large Language Models and Physics Engines.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs LLMPhy: Parameter-Identifiable Physical Reasoning Combining Large Language Models and Physics Engines

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:22.577645Z digest=sha256:90fbdd70d1c910e8a2bca61290f24ce435c870c7d943c35c7bd4bd6f84ffe8af

Observation 034dfe7f-12e1-441d-938c-625749f617b6 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:22.687250Z digest=sha256:1689cc42124ba4ca427a17875d8523fdff6149f243d0a2ddea39260b7ae618cb

Observation 7b98a1a1-990d-4a26-bef6-0e0e0399cefb · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 11

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:55:22.794829Z digest=sha256:adf522b29acb57926bf53c936a1edcbfb27796ff051bb711ffc2525014e6f94a

Observation 0afc2af1-a090-47bd-b444-bb2a2ea19321 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:22.914833Z digest=sha256:699c46fc0357ed12204d74367345ef061c772957d869fa18181b9faabdc2efad

Observation ca2a8551-2e2a-4c72-8dc0-4e9f244b3bbe · outbound

This paper cites LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.056581Z digest=sha256:6ea35c16047aacf621b81bc31ea091a9af1df551c287c373654234501fd86684

Observation 5257ebcf-df47-4210-9a07-9265c0d80240 · outbound

This paper cites Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents

Reference 14

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no resolver link, observed 2026-08-07T11:55:23.187041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.187041Z digest=sha256:e38e6e2f4f64d5e7c2270799453c11fa76b5bd42c702f23db829a89e63257423

Observation 8824123e-c79d-4469-be14-d9f2bf90e14a · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 15

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raw_fallback, observed 2026-08-07T11:55:27.220602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.355822Z digest=sha256:e6183601ddab3b735836c0ffe5b35e816d155bd8463253c91b3ebf99785d9d95

Observation 4f089d59-e8ff-437f-8cda-a6149121c462 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.534867Z digest=sha256:c87accb4b9308c98cd7a119f8432c731c7d2e736dcc32ff4bf61afd1b0e5fbbe

Observation 8d794475-5b78-48a6-9ad6-cbca8d7d57bb · outbound

This paper cites CogVLM2: Visual Language Models for Image and Video Understanding.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs CogVLM2: Visual Language Models for Image and Video Understanding

Reference 17

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:55:23.590215Z digest=sha256:9706fd8a089d538909e4ab73bcc0ba75ed17a7294bf5aaa25520aee2778b4c4e

Observation 96205219-279a-4e2a-9b2e-f2dfc8d83235 · outbound

This paper cites AutoVFX: Physically Realistic Video Editing from Natural Language Instructions.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs AutoVFX: Physically Realistic Video Editing from Natural Language Instructions

Reference 18

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source=pdf_text observed=2026-08-07T11:55:23.607708Z digest=sha256:8dfc603c79603d6f2f76ea6f7be8517782b74670c73b297ccfe1ef48adbe8543

Observation 6c3de4c6-4853-4310-8db8-08a0e2b10de5 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-07T11:55:23.616553Z digest=sha256:6650027f418da1d07b64fa90544d26c73156e9bbe935a60c4db72aac3434293b

Observation 4275776d-4536-4cde-952d-acc26d9f7a29 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.621859Z digest=sha256:ecb852336cc9e041a1cce5e86413d4405b160cf671359f4508e2521944178ef9

Observation 6edae006-e232-42d3-9b6e-81b1bd8e13e4 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.628214Z digest=sha256:8c6dc316bdf26624516feac0650184318bc62375d17b7fd49a69cdf4155fb22e

Observation 2d44378a-59db-476d-9b05-be5ef96a5df9 · outbound

This paper cites LLM-Assisted Visual Analytics: Opportunities and Challenges.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs LLM-Assisted Visual Analytics: Opportunities and Challenges

Reference 22

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source=pdf_text observed=2026-08-07T11:55:23.635474Z digest=sha256:21623d97f55d619ff953c9b39973efc9d9f4f07104b284856612465c8e4d673b

Observation 13527fbd-0e65-4854-99c4-23413ff52153 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 23

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.643433Z digest=sha256:df97c47f733be130d760093f1fbba0437cfc4aa75cedc03f3b5322e295707a34

Observation db576aa8-4c8e-4069-951d-180da0728f5b · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 24

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raw_fallback, observed 2026-08-07T11:55:25.860422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.649943Z digest=sha256:8af4d786adaed8f9ab611f5b2afbec9140108d55193d63d727cfe534fad603cf

Observation 131de6de-3392-4fe2-a88f-856467737f7b · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-07T11:55:23.655919Z digest=sha256:5653f70bf4b752cd1dd83b160cd0abbf70b983538222271edc07005f2bce1205

Observation 857c2978-5835-4d80-9574-b131dbc86a21 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.662094Z digest=sha256:71046f588cf3499956a46fc723204fd23b62f19b11d42cca175662da3b236503

Observation 5601e2a7-2844-46bf-9e01-bda663249c7b · outbound

This paper cites One for All: Towards Training One Graph Model for All Classification Tasks.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs One for All: Towards Training One Graph Model for All Classification Tasks

Reference 27

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source=pdf_text observed=2026-08-07T11:55:23.669030Z digest=sha256:dba1e7b177981cba4441d28036adda9d36071bdda21da7ee11c58c389bc6673a

Observation 3cbc45e0-2484-4fbd-8186-a200f48d3512 · outbound

This paper cites Visual Instruction Tuning.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Visual Instruction Tuning

Reference 28

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source=pdf_text observed=2026-08-07T11:55:23.677172Z digest=sha256:398da781936fb5e613aa17f2f8ec9428dc182675a6b3b3c1593fcf7d3aadd33c

Observation f89ced25-3f7c-42e7-9c4e-d59866ba5042 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-07T11:55:25.677781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.685349Z digest=sha256:d1432d5b05146c15df570177c9a4f01ba2f29fc1179c654029894930a395cec4

Observation 6611659c-99b0-47da-bf42-feb0a98d754e · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.693171Z digest=sha256:c5f4c690cfc14ec3cadf97fe6928e14e7c3cec4695e198f2f9f2ce7b3a8cfcbd

Observation 5c10ab9b-7207-44a0-b710-b1ec91a7e84f · outbound

This paper cites Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training

Reference 31

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no resolver link, observed 2026-08-07T11:55:23.699416Z

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source=pdf_text observed=2026-08-07T11:55:23.699416Z digest=sha256:394ea9b51a6132756de0822a3571feb10886ffdef9929ec6fcabbd907eb355b5

Observation 6d19a20d-a366-4f75-8608-4d049f129326 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.707386Z digest=sha256:f180137d69f87b6045ef4118e11400c9abb7ce7c91c61fe71c43af77a4c943e5

Observation 2aa36ee9-1569-467b-add6-f5f8938c8819 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 33

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raw_fallback, observed 2026-08-07T11:55:25.428108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.714325Z digest=sha256:0cd465b320993ee5b0bca270291da731e7cda2eda098a1bea13367b41d473631

Observation b9d6403a-7115-4144-a3ad-ffa4cb28d3a3 · outbound

This paper cites Retrieval Augmented Generation with Multi-Modal LLM Framework for Wireless Environments.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Retrieval Augmented Generation with Multi-Modal LLM Framework for Wireless Environments

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:55:24.099851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.720648Z digest=sha256:fc936ad7ac973a94a807124a736209cd169e1a6eae00867e457861ba4df64490

Observation 391a81b7-71f6-4be0-928a-0a6835d9f718 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.726255Z digest=sha256:db3ff225e87549c63e3194935f355f8c5ac1cfa47fedf369d2b13e73fa24b0b9

Observation dd315121-aa72-4e83-92dd-af6dad76dda0 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.734530Z digest=sha256:b6ecd2cd9a2128f7baaacdbfd1e18b8c386e48dde8cd4ce36d3d9cae49f7c727

Observation 9b02092c-d015-4e69-83bd-0a76d0158a7a · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Gemini: A Family of Highly Capable Multimodal Models

Reference 37

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.742012Z digest=sha256:cc639c8ea333bb51bab52593e47b3e21c13723df4caa889c6173128fd552fcab

Observation 9cdccee6-0251-4f8e-a12d-fcd22bb5f2b8 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 38

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unresolved
raw_fallback, observed 2026-08-07T11:55:25.162119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.748226Z digest=sha256:5d85cf5bb8b71148fe539a13e6adf2ae0576bc16cbb24204691ed58877fd3c04

Observation c406a7de-dd54-4881-abf9-5296a69d2ed7 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:23.753222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.753222Z digest=sha256:1c2d19fe61b86e23b16b1991b359b2ec0880000c90d1159c775197eb69abe84c

Observation b20bbb00-19d5-46c6-8ba0-5e3ffbe55cbc · outbound

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

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:23.759228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.759228Z digest=sha256:cf4e4940014e67a2fc302c10031b33deaa62b362e673933e19ecbcd3e54d1384

Observation 22ee5733-0893-452e-af7c-2ad5276f4f5b · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Emu3: Next-Token Prediction is All You Need

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:23.765118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.765118Z digest=sha256:a261d662fb1b073de7a38830b1486606392065b484a3de5999a3706cc671acfd

Observation eb300b93-e05b-422c-b9ac-8fc0c0717996 · outbound

This paper cites LLM-Generated Natural Language Meets Scaling Laws: New Explorations and Data Augmentation Methods.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs LLM-Generated Natural Language Meets Scaling Laws: New Explorations and Data Augmentation Methods

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:23.771326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.771326Z digest=sha256:83c74573fab8f8eb9dda4b6bdda798be6900ab53d1b34533dad12633fc95a726

Observation dd3a9d96-f805-4d80-8363-e46d6d86e589 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:55:24.921393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.777949Z digest=sha256:ad00c01125d36e5f4fac8c58b3b8243766525de02c648a842148145b5c37ca80

Observation 7f92eb6c-7988-41e4-8471-352ebeded44e · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:55:24.738701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.783952Z digest=sha256:55092a461d45f4dc1d7e9b2b40f24548ac1e570079e44370c0bc5ee8dc8acca2

Observation e55da766-29d3-429b-829d-06befce89e9d · outbound

This paper cites Simulation as Reality? The Effectiveness of LLM-Generated Data in Open-ended Question Assessment.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Simulation as Reality? The Effectiveness of LLM-Generated Data in Open-ended Question Assessment

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:55:23.899220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.789104Z digest=sha256:7773ba598bf828bf6b8ba012cb914fd210c2cc0cd410aa266fdb4b497e79bc4c

Observation bbcc7bc8-cb9e-44ac-a60f-42f3e3da1c69 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:55:24.670930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.795326Z digest=sha256:20c6b372db8feccac1185bc5df72d38cfefe55cb0de50eefbb4fca9095195857

Observation 252ccfcd-63b3-470f-a272-09c8979bd5bf · outbound

This paper cites LLM-Optic: Unveiling the Capabilities of Large Language Models for Universal Visual Grounding.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs LLM-Optic: Unveiling the Capabilities of Large Language Models for Universal Visual Grounding

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:55:23.873347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.800463Z digest=sha256:b30d4949ebd15eab7e1b61ede546a4a874fef414547a770a9c42817cdb92f0a3

Observation 04860089-b6b7-4a6b-8ee7-e2ea6efa9127 · outbound

This paper cites Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editing.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editing

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T11:55:23.806316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:55:23.806316Z digest=sha256:4586db378f1718595bb323a9163ab5febfa51165057e7defa2adab053c5f2c21

Observation 1fb29b71-6aaf-48aa-8e82-0fe5d43fed01 · outbound

This paper cites an unresolved cited work.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:55:24.602202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:55:23.813168Z digest=sha256:7135c091341f74ec8258464265a4eb1aa79009db3ba163324a43cab45ef0cc4b

Pith citing papers

No inbound Pith citation observations are available.