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Paper Citation Record · LEDGER

MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.10563.

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

pith.paper-citation-record.v1
2410.10563 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:53:29.877318Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.301348Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5a6a623d-9c3f-4aca-8c02-bf6220311344 · inbound

SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models cites this paper.

SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T16:53:29.877318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:53:29.877318Z digest=sha256:188870893de24561db1092a7ce7b377c9fdb4bcd8e746a79f9e87f77e690dd77

Observation 4bbf6cd1-7f28-4e8e-8fd2-d03e9d4c631d · inbound

POINTS1.5: Building a Vision-Language Model towards Real World Applications cites this paper.

POINTS1.5: Building a Vision-Language Model towards Real World Applications MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T17:53:35.587371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:53:35.587371Z digest=sha256:0c826176634918b1d671147eb823b4cf0f2db3960727a8f8ffd66460ffcd8308

Observation eb001b3c-1e32-447c-aac6-58d4f013fa70 · inbound

OmniGenBench: A Benchmark for Omnipotent Multimodal Generation across 50+ Tasks cites this paper.

OmniGenBench: A Benchmark for Omnipotent Multimodal Generation across 50+ Tasks MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:28:29.775775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:28:29.775775Z digest=sha256:678f317772c9cefec3526c7e949cbf6b3b804933778917ac505afddebc319e74

Observation adb9539c-bbe9-4d46-bc61-7e061c22ee24 · inbound

VFaith: Do Large Multimodal Models Really Reason on Seen Images Rather than Previous Memories? cites this paper.

VFaith: Do Large Multimodal Models Really Reason on Seen Images Rather than Previous Memories? MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:31.778408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:07:31.778408Z digest=sha256:d453c12c88688ab18304ef9e42498c98b5eed7d834a409bd29e34d6f4b86e748

Observation 43c1e1de-217a-495a-8173-e0d12cd02b9f · inbound

MARBLE: A Hard Benchmark for Multimodal Spatial Reasoning and Planning cites this paper.

MARBLE: A Hard Benchmark for Multimodal Spatial Reasoning and Planning MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T21:58:34.062989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:58:34.062989Z digest=sha256:9861017ec0e49c8bc65c84f8c3b99d388d6a4544b87d7a5684ad971d16c5f1fd

Observation 1c8db78e-3087-448a-b247-82dc018016e8 · inbound

ADIEE: Automatic Dataset Creation and Scorer for Instruction-Guided Image Editing Evaluation cites this paper.

ADIEE: Automatic Dataset Creation and Scorer for Instruction-Guided Image Editing Evaluation MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T18:48:38.097897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:48:38.097897Z digest=sha256:f1a96756a62a5051d5c74846d3500f76c07b2c338a0f3717126ec05b263874a5

Observation 56ca49fb-875b-40e5-a123-921594857936 · inbound

Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation cites this paper.

Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 191

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:18:43.747618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T04:19:26.332718Z digest=sha256:812458a6fd02c01b40dded71b0db1c5f688616f065a1000b7e8c49af7bd8687b

Observation b9a431f3-7681-4989-872e-0e404a3a7d47 · inbound

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:55.303282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-26T01:50:54.242508Z digest=sha256:834334db147050439b666a0d49467106e57b3bc7dc9a67fdc858dccac9ad05d1