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Paper Citation Record · LEDGER

M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2405.16473.

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

pith.paper-citation-record.v1
2405.16473 v1

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 32 of 32 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 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:24:33.000246Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T13:31:24.804270Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fa2db9a7-bd56-4ed2-8723-7abfc7ee438b · inbound

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

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 16

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arxiv_id, observed 2026-05-16T09:16:17.430760Z

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=2026-05-16T09:16:17.150383Z digest=sha256:4a21a60f48247979cc0efea74f3499b85abaf478ad880a6045d095f3bacd60e6

Observation c8baab00-adc6-4ee9-9422-05ba42110bff · inbound

Interleaved-Modal Chain-of-Thought cites this paper.

Interleaved-Modal Chain-of-Thought M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 6

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source=pdf_text observed=2026-08-12T10:10:38.175313Z digest=sha256:81704089ccbe2446ec259b1730af11c2a440413368f02dc84169ed422cd05d93

Observation df7ad01c-87f9-45a1-9afe-1dd4a27d19dc · inbound

GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? cites this paper.

GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 8

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source=arxiv_source observed=2026-08-11T16:30:34.567451Z digest=sha256:f236689926f2012020d99e6bf1e5fb6467835ad2f95ce1b9e9b31c0dbd09260f

Observation 90671c1b-3e88-46b1-8aa8-74d8d62ec4d3 · inbound

CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models cites this paper.

CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 6

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source=arxiv_source observed=2026-08-11T13:38:13.986574Z digest=sha256:4b8f89666055af132b970dad63b9d9ca5a5cd620b965752267a844f27b62cd54

Observation c2262a3d-47e2-4439-bc02-52c12ec9e78b · inbound

PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding cites this paper.

PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 1

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source=pdf_text observed=2026-08-10T13:32:58.231052Z digest=sha256:9625ef4ad023229ab27e90753f79a876ba47afa8d8381ffea8a28bca8b1db6bf

Observation 3b253375-e068-4098-b7f3-71a665c88a01 · inbound

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models cites this paper.

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 16

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arxiv_id, observed 2026-05-10T13:41:08.233339Z

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=2026-05-10T13:41:07.991012Z digest=sha256:ae72ce3132d96878910c124b79e4548ff0b8c13718eb729708fe3439dbd8fd62

Observation 9bcc6db7-0756-4744-9dee-20b67fa7b085 · inbound

Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models cites this paper.

Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 12

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source=pdf_text observed=2026-08-16T05:12:18.132901Z digest=sha256:cf57efc6a3c6d62d85cdea167479af14e1deddfe0b2e7da30b6598004ba3c31a

Observation a768fc52-f4a4-45e4-8ead-41ade8a9bbb9 · inbound

Bridging the Dynamic Perception Gap: Training-Free Draft Chain-of-Thought for Dynamic Multimodal Spatial Reasoning cites this paper.

Bridging the Dynamic Perception Gap: Training-Free Draft Chain-of-Thought for Dynamic Multimodal Spatial Reasoning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 3

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source=arxiv_source observed=2026-08-07T15:02:24.955656Z digest=sha256:a8cac8621729445f67350460c7a3d1c8d61a7d76b292a686eeadae12d5452ce8

Observation 63d556ef-4e20-4813-b7d4-3824b8e545b1 · inbound

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects cites this paper.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 21

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source=pdf_text observed=2026-08-07T14:02:52.740516Z digest=sha256:f7bf0a42018cba59935e7810497497bdd46466c985eaa80a15ec4f9cc5feaace

Observation 5ef36ba9-0092-47a9-846d-f92be3f14d16 · inbound

Visual Large Language Models Exhibit Human-Level Cognitive Flexibility in the Wisconsin Card Sorting Test cites this paper.

Visual Large Language Models Exhibit Human-Level Cognitive Flexibility in the Wisconsin Card Sorting Test M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 36

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source=pdf_text observed=2026-08-07T13:19:32.456049Z digest=sha256:76a0c3acdb40d364bbe4149ddabf81fa5b6606bae80dd717242ef7eee7863d03

Observation d6e6e4a9-3d92-4866-95c0-a526d30c03aa · inbound

Advancing Multimodal Reasoning via Reinforcement Learning with Cold Start cites this paper.

Advancing Multimodal Reasoning via Reinforcement Learning with Cold Start M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 8

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source=pdf_text observed=2026-08-07T13:12:53.142788Z digest=sha256:2b50c57f4f3d861c88ba1e16cfe1cf37e15e104404c9f4ca69278b85321b0cc3

Observation c9ff8af9-fef5-462a-8545-4a856cbd90e8 · inbound

GThinker: Towards General Multimodal Reasoning via Cue-Guided Rethinking cites this paper.

GThinker: Towards General Multimodal Reasoning via Cue-Guided Rethinking M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 7

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source=pdf_text observed=2026-08-07T11:55:12.014182Z digest=sha256:d4425601c7c2c3a7d8b4bb9797c0eefb55c0c542d9327d3359a06b3f2e6c3c42

Observation 2760d9a4-0362-4c1d-a434-7a40e9ef31e0 · inbound

Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark cites this paper.

Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 2024

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source=pdf_text observed=2026-08-07T11:05:19.193447Z digest=sha256:f0d44d8d58a0ee5eafcb55e362b6bd1fce8e627ee722eabec5d9466fd6d01fab

Observation ed76d24d-96d2-40a0-b3f5-854c070f9245 · inbound

Understanding Financial Reasoning in AI: A Multimodal Benchmark and Error Learning Approach cites this paper.

Understanding Financial Reasoning in AI: A Multimodal Benchmark and Error Learning Approach M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 6

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source=arxiv_source observed=2026-08-16T11:24:33.000246Z digest=sha256:1677319255f258108b4561fd74a0e27a7ccc10a88af74fa2d91c051335131d6f

Observation 5cfa213e-4e85-4600-8e5a-d68347522cd7 · inbound

Mimicking or Reasoning: Rethinking Multi-Modal In-Context Learning in Vision-Language Models cites this paper.

Mimicking or Reasoning: Rethinking Multi-Modal In-Context Learning in Vision-Language Models M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 6

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source=pdf_text observed=2026-08-07T05:25:30.344139Z digest=sha256:1d3f7199acd89a5965e8dd047f2e4c06770e4ae07c1b63a2301242cc93a88286

Observation 23ace000-230b-4d70-a2f6-a22c80d74a04 · inbound

VReST: Enhancing Reasoning in Large Vision-Language Models through Tree Search and Self-Reward Mechanism cites this paper.

VReST: Enhancing Reasoning in Large Vision-Language Models through Tree Search and Self-Reward Mechanism M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 1

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source=arxiv_source observed=2026-08-07T05:09:18.196208Z digest=sha256:7e7a7e17f048482e3680f18d433e903eb2d530e8d3726d89e2ecde2cbbc2fe4e

Observation de2f71a6-6d3e-42c6-bc3f-951120f45647 · 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? M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 5

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source=pdf_text observed=2026-08-07T04:07:31.820419Z digest=sha256:4d80bc9e0f69e3ed67e862acf7762b2c73e42ea36175a309beac380fd0464f37

Observation a33dea55-6a26-449c-827b-dc1f4e4603a9 · inbound

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning cites this paper.

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 4

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source=arxiv_source observed=2026-08-15T18:39:18.587552Z digest=sha256:34f51afbcc8bbed653d12b784a9d4fe9b756f0af841b612ffa3626acc1636e5b

Observation c5d95906-1dc0-47af-9f83-a6d76b8c75b1 · inbound

MMAT-1M: A Large Reasoning Dataset for Multimodal Agent Tuning cites this paper.

MMAT-1M: A Large Reasoning Dataset for Multimodal Agent Tuning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 8

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source=pdf_text observed=2026-08-06T12:18:32.202517Z digest=sha256:050f8232efa8b85771fbe02b5e4bbf43b85c4b2fd1ea273026515bc277f6dbb2

Observation 499edf28-5844-4674-ab3d-bcb80ccd7474 · inbound

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent cites this paper.

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 4

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arxiv_id, observed 2026-05-15T18:56:23.872966Z

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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=2026-05-15T18:56:23.817544Z digest=sha256:fe03e471bd67aff82713c30eed3404350168ec5b687e7aa8dd76f4659abffe90

Observation 0fb856ae-46bb-4b18-8f01-dd3c23c85fdf · inbound

HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes cites this paper.

HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 36

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source=pdf_text observed=2026-08-05T19:03:06.028911Z digest=sha256:68d21cf37e462aaa3a8623bb1f7223b3bf8811e840df86cc2b9e2cd2e1d97b40

Observation aa9d3f87-8fbd-4581-9610-9091bce5f87f · inbound

Explain Before You Answer: A Survey on Compositional Visual Reasoning cites this paper.

Explain Before You Answer: A Survey on Compositional Visual Reasoning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 231

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source=pdf_text observed=2026-08-15T17:09:18.386670Z digest=sha256:951435b476330aa422aad1aa48870ee24aca53c7fa02f3bc01f6240d096803e3

Observation 93e0c80a-7cef-40ce-a675-08f108ee77f4 · inbound

Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration cites this paper.

Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 2020

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source=pdf_text observed=2026-08-04T18:17:16.302417Z digest=sha256:363c29e1539447cb282759dfd2dbdf38c84cc50a0c93ebddccc8492c9f4a8bdb

Observation c59e1cb9-f502-49ef-a836-ce4960afb37d · inbound

AIM-CoT: Active Information-driven Multimodal Chain-of-Thought for Vision-Language Reasoning cites this paper.

AIM-CoT: Active Information-driven Multimodal Chain-of-Thought for Vision-Language Reasoning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 2

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arxiv_id, observed 2026-05-18T13:31:24.806625Z

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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=2026-05-18T13:30:10.620448Z digest=sha256:023b4547336b6ec97bde3c478d2f426927205d3bee08c4d9fb28ed392ae7534d

Observation c33ecb02-7b77-4bc5-b8eb-9a0400c2620f · inbound

AIM-CoT: Active Information-driven Multimodal Chain-of-Thought for Vision-Language Reasoning cites this paper.

AIM-CoT: Active Information-driven Multimodal Chain-of-Thought for Vision-Language Reasoning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 2013

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source=pdf_text observed=2026-08-04T13:42:59.320438Z digest=sha256:87af5dc4a0e5f434111226c5661ba9b7e3484a83949744557b2032d1ca0b2b59

Observation bcdf53d7-3650-4256-8c03-e7f7d95c5f10 · inbound

MIND: Multi-rationale INtegrated Discriminative Reasoning Framework for Multi-modal Large Models cites this paper.

MIND: Multi-rationale INtegrated Discriminative Reasoning Framework for Multi-modal Large Models M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 4

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source=pdf_text observed=2026-08-03T18:25:01.437413Z digest=sha256:4534c781a737f5cf8acb3aa8a62da4f79bf04cd87124878e8f42ecb622404b80

Observation 3098d1d8-c620-4482-bc2d-d54d5d21c7de · inbound

Thinking Diffusion: Penalize and Guide Visual-Grounded Reasoning in Diffusion Multimodal Language Models cites this paper.

Thinking Diffusion: Penalize and Guide Visual-Grounded Reasoning in Diffusion Multimodal Language Models M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 2

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arxiv_id, observed 2026-05-10T23:30:50.458940Z

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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=2026-05-10T19:06:45.417233Z digest=sha256:7ba88a7d81a27ee956495bb60e6b78705e989b102f64e30152dd9234870c693b

Observation ce225f1b-afe4-473d-8aa3-b0b5418455d2 · inbound

Targeted Exploration via Unified Entropy Control for Reinforcement Learning cites this paper.

Targeted Exploration via Unified Entropy Control for Reinforcement Learning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 1

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arxiv_id, observed 2026-05-10T10:49:56.104547Z

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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=2026-05-10T10:48:27.733823Z digest=sha256:6b337055817b465705f14ff5c59a9e324e5b5b50b16a4056d8dadc4230471544

Observation d1e68568-458f-4b72-a105-3d1bd065df69 · inbound

Towards Robust Endogenous Reasoning: Unifying Drift Adaptation in Non-Stationary Tuning cites this paper.

Towards Robust Endogenous Reasoning: Unifying Drift Adaptation in Non-Stationary Tuning M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 40

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arxiv_id, observed 2026-05-10T09:03:26.437698Z

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=2026-05-10T08:28:07.531338Z digest=sha256:022a8d885a3c08768ad344eed13c496e403eeaa91a6d3b218b56754dcfa02194

Observation 73f1b7c1-46c2-4eed-bd86-6c79507e911a · inbound

BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception cites this paper.

BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 255

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source=arxiv_source observed=2026-07-12T04:17:40.198357Z digest=sha256:90ce6fb2e0d3fd61383c77b907e24d35f3816bae8057e3992be6192f85033090

Observation ddfb857f-9aa0-4d81-9deb-23b1d1ad7ce0 · inbound

ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding cites this paper.

ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 2021

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source=pdf_text observed=2026-08-01T16:48:35.633314Z digest=sha256:7fbcad2a8efb96d79829c7655861597039c151d80a3d3055bf866ba9ea37c12a

Observation 8e4cad80-e85e-4f78-b76a-ecfb807eb8e1 · inbound

VERDICT: Training-Free Step-Wise Verification of Multimodal Reasoning via Disagreement-Aware Consensus cites this paper.

VERDICT: Training-Free Step-Wise Verification of Multimodal Reasoning via Disagreement-Aware Consensus M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 5

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source=pdf_text observed=2026-08-12T19:56:01.691015Z digest=sha256:7835266a08e823a99cad628c7270f981954f8509dde058c1ec07a9f1a94aa2f0