Paper Citation Record · LEDGER

Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2403.12966.

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

pith.paper-citation-record.v1
2403.12966 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

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 2026-08-14T06:32:32.682623+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:27:03.174749Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:59:57.253374Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 a0251e79-613a-493e-b49f-b8077e2b6f91 · inbound

Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models cites this paper.

Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T15:17:06.857653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c529c18e-e9da-48dc-b009-f7231aa7fe71 · inbound

VISCO: Benchmarking Fine-Grained Critique and Correction Towards Self-Improvement in Visual Reasoning cites this paper.

VISCO: Benchmarking Fine-Grained Critique and Correction Towards Self-Improvement in Visual Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T23:50:01.313217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a157d044-e05c-4ff9-afad-74503f0d4c9a · inbound

Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives cites this paper.

Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T21:44:55.875468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12ae62c6-8899-485a-86ff-e0ce6deaca68 · inbound

Ola: Pushing the Frontiers of Omni-Modal Language Model cites this paper.

Ola: Pushing the Frontiers of Omni-Modal Language Model Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T22:47:39.212186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd69af3a-c658-4de7-b693-ad706aefd14b · inbound

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey cites this paper.

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-15T17:18:53.710895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f80a9b77-b39d-4501-92d5-8c31e8374029 · inbound

ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding cites this paper.

ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:25:55.262895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3194040f-a74e-4226-818d-3234125cc836 · inbound

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

GThinker: Towards General Multimodal Reasoning via Cue-Guided Rethinking Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:12.978031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0fdd9d3-d2de-4c1f-b2c4-56f6c581b613 · inbound

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning cites this paper.

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:50.881392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb5ea1f2-c357-474d-8ffb-11d85425ac2d · inbound

AD^2-Bench: A Hierarchical CoT Benchmark for MLLM in Autonomous Driving under Adverse Conditions cites this paper.

AD^2-Bench: A Hierarchical CoT Benchmark for MLLM in Autonomous Driving under Adverse Conditions Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T04:49:28.301957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b64d36b5-fdc8-43d7-9c26-6476c5b90630 · inbound

Ego-R1: Chain-of-Tool-Thought for Ultra-Long Egocentric Video Reasoning cites this paper.

Ego-R1: Chain-of-Tool-Thought for Ultra-Long Egocentric Video Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T00:34:32.299228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c23b8a61-b5cb-4a6c-8acc-8171becc0267 · inbound

CoT-Segmenter: Enhancing OOD Detection in Dense Road Scenes via Chain-of-Thought Reasoning cites this paper.

CoT-Segmenter: Enhancing OOD Detection in Dense Road Scenes via Chain-of-Thought Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T20:00:21.639221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd23a595-bf5b-4d0f-8550-15b82f3f5b94 · inbound

High-Resolution Visual Reasoning via Multi-Turn Grounding-Based Reinforcement Learning cites this paper.

High-Resolution Visual Reasoning via Multi-Turn Grounding-Based Reinforcement Learning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:12:07.081795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2e4a3485-1b56-4e99-860b-5402c90fa88f · inbound

LIRA: Inferring Segmentation in Large Multi-modal Models with Local Interleaved Region Assistance cites this paper.

LIRA: Inferring Segmentation in Large Multi-modal Models with Local Interleaved Region Assistance Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:02.779348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c23e29bd-49d4-4ee2-a256-716b3e5727d9 · inbound

Towards Video Thinking Test: A Holistic Benchmark for Advanced Video Reasoning and Understanding cites this paper.

Towards Video Thinking Test: A Holistic Benchmark for Advanced Video Reasoning and Understanding Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T15:48:33.294475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0d61b9f-e1be-4f8d-9c4f-fbb619126a18 · inbound

VisReason: A Large-Scale Dataset for Visual Chain-of-Thought Reasoning cites this paper.

VisReason: A Large-Scale Dataset for Visual Chain-of-Thought Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T20:57:30.540242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc6636ce-071f-46a3-91a6-23c9f979f512 · inbound

M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understanding cites this paper.

M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understanding Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T10:49:58.803374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 684c86e5-0d91-499a-85b5-0a00f9524f72 · inbound

HART: High-Resolution Annotation-Free Reasoning Technique through a Closed-loop Framework cites this paper.

HART: High-Resolution Annotation-Free Reasoning Technique through a Closed-loop Framework Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T20:19:15.127415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f45d257b-0d11-45a7-813b-85ed3811a840 · inbound

Fully Spiking Neural Networks with Target Awareness for Energy-Efficient UAV Tracking cites this paper.

Fully Spiking Neural Networks with Target Awareness for Energy-Efficient UAV Tracking Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-13T16:55:20.099628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23e646b7-5992-4713-afa8-5cd784aa1b6c · inbound

Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs cites this paper.

Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:38:00.943697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a961c15c-59e3-4194-9a80-6740ef13ffcc · inbound

Beyond Thinking: Imagining in 360$^\circ$ for Humanoid Visual Search cites this paper.

Beyond Thinking: Imagining in 360$^\circ$ for Humanoid Visual Search Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:01:18.293323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 12dd8a4c-9c84-456d-94f0-cd1823df109c · inbound

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation cites this paper.

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:58:13.393013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bbef1c4a-05ba-41c9-84bd-d1f8555e4ab0 · inbound

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation cites this paper.

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:35:00.704886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 02bf47d2-71cf-4189-acf2-9dc74a589aea · inbound

MathVis-Fine: Aligning Visual Supervision with Necessity via Progressive Dependency-Guided Training for Multimodal Mathematical Reasoning cites this paper.

MathVis-Fine: Aligning Visual Supervision with Necessity via Progressive Dependency-Guided Training for Multimodal Mathematical Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 56

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T20:18:57.800982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6fec5a22-b305-436b-9315-e96dc9f8b8d2 · inbound

An LMM for Precisely Grounding Elements in Documents cites this paper.

An LMM for Precisely Grounding Elements in Documents Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-04T15:09:54.732696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b6d50c90-17fe-415b-8956-ed10cf4791f2 · inbound

ActiveScope: Actively Seeking and Correcting Perception for MLLMs cites this paper.

ActiveScope: Actively Seeking and Correcting Perception for MLLMs Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-04T15:59:57.255666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b4d01059-1aac-4bd7-882c-e1b6a0ef5325 · 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 Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-07-04T15:09:55.117287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4cf2e4d6-aaca-4331-a20f-c6aba144b36b · inbound

Perceive-to-Reason: Decoupling Perception and Reasoning for Fine-Grained Visual Reasoning cites this paper.

Perceive-to-Reason: Decoupling Perception and Reasoning for Fine-Grained Visual Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:26:58.461700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4a13e359-7a5d-4ebf-ba38-dea51b07c98f · 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 Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 210

Resolution: unresolved; no resolver link, observed 2026-07-12T04:17:40.198357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 125a6848-5382-4caa-adf9-477492677fed · inbound

Seeing What Is Actually There: PriVE-Bench and PriVE-Tools for Counterfactual Evaluation of Agentic Visual Evidence in VLMs cites this paper.

Seeing What Is Actually There: PriVE-Bench and PriVE-Tools for Counterfactual Evaluation of Agentic Visual Evidence in VLMs Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T06:18:15.882601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43170df6-d614-4c33-94f2-bfce8ce52198 · inbound

Look Where It Matters: Adaptive Visual Refinement for Vision-Language-Action Models cites this paper.

Look Where It Matters: Adaptive Visual Refinement for Vision-Language-Action Models Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T11:57:40.838682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9741293f-4a3e-4b3d-8c62-acc4f2a1ba01 · inbound

ToolVision: Learning When and How to Use Visual Tools with Capability-Aligned Supervision cites this paper.

ToolVision: Learning When and How to Use Visual Tools with Capability-Aligned Supervision Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T04:27:03.174749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fed3ace4-7f7a-4068-a766-df90f1678d4d · inbound

Thinking With Tools, Not With Pixels: Tool Calls as Text Scaffolds for Visual Reasoning cites this paper.

Thinking With Tools, Not With Pixels: Tool Calls as Text Scaffolds for Visual Reasoning Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T12:53:14.107674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.