Paper Citation Record · LEDGER

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting

As of 21 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:2504.13624.

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

pith.paper-citation-record.v1
2504.13624 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:07:03.811045Z

measured 38 of 38 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:10:57.600421Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:08:01.528160Z

Reference resolution

36 of 36 outbound references displayed

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verified fuzzy2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 038fa4fc-f287-4d02-8531-9e4e0c10f1c0 · outbound

This paper cites Solar energy: Potential and future prospects.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Solar energy: Potential and future prospects

Reference 1

Resolution: verified exact; doi, observed 2026-08-16T12:07:04.325753Z

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Observation bb0aeccc-f7f3-4e64-a5ae-ce26694c22de · outbound

This paper cites The values of market -based demand response on improving power system reliability under extreme circumstances.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting The values of market -based demand response on improving power system reliability under extreme circumstances

Reference 2

Resolution: verified exact; doi, observed 2026-08-16T12:07:04.309143Z

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Observation b3a43a33-7069-4bdd-9e6a-db7beec4e66a · outbound

This paper cites Recurrent Spatial Pyramid CNN for Optical Flow Estimation.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Recurrent Spatial Pyramid CNN for Optical Flow Estimation

Reference 3

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Observation ef548d24-7285-4cba-8b7c-08179b9b00d0 · outbound

This paper cites Harvesting spatiotemporal correlation from sky image sequence to improve ultra -short-term solar irradiance forecasting.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Harvesting spatiotemporal correlation from sky image sequence to improve ultra -short-term solar irradiance forecasting

Reference 4

Resolution: verified exact; doi, observed 2026-08-16T12:07:04.293752Z

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Observation 24027dbc-ab3f-463f-aa1d-6b758df6fa5a · outbound

This paper cites Pattern Classification and PSO Optimal Weights Based Sky Images Cloud Motion Speed Calculation Method for Solar PV Power Forecasting.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Pattern Classification and PSO Optimal Weights Based Sky Images Cloud Motion Speed Calculation Method for Solar PV Power Forecasting

Reference 5

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Observation 1b4d9b87-dab9-49ca-8a52-55ad589e9bbd · outbound

This paper cites Hybrid intrahour DNI forecast model based on DNI measurements and sky-imaging data.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Hybrid intrahour DNI forecast model based on DNI measurements and sky-imaging data

Reference 6

Resolution: verified exact; doi, observed 2026-08-16T12:07:04.278686Z

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Observation b3636618-a468-455d-a55b-b8d56607c272 · outbound

This paper cites Short -term solar radiatio n forecasting with a novel image processing -based deep learning approach.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Short -term solar radiatio n forecasting with a novel image processing -based deep learning approach

Reference 7

Resolution: verified exact; doi, observed 2026-08-16T12:07:04.263019Z

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Observation 9eb9095a-3cbb-4254-8786-65cb983b245c · outbound

This paper cites On vision transformer for ultra-short-term forecasting of photovoltaic generation using sky images.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting On vision transformer for ultra-short-term forecasting of photovoltaic generation using sky images

Reference 8

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Observation 1f07db39-dd2c-4c86-84fe-4ef5afd4d93d · outbound

This paper cites Intra -hour PV power forecasting based on sky imagery.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Intra -hour PV power forecasting based on sky imagery

Reference 9

Resolution: metadata mismatch; raw_fallback, observed 2026-08-16T12:07:04.972812Z

Source-reported events for the cited work

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Observation cb47021e-b75f-44f7-97c9-41caec01e5b0 · outbound

This paper cites Sky Image Prediction Model Based on Convolutional Auto-Encoder for Minutely Solar PV Power Forecasting.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Sky Image Prediction Model Based on Convolutional Auto-Encoder for Minutely Solar PV Power Forecasting

Reference 10

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Observation 7e34f732-0b92-4ee1-a9ee-2c4d3996cfad · outbound

This paper cites Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Reference 11

Resolution: verified exact; doi, observed 2026-08-16T12:07:04.246466Z

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Observation 235d6bc7-8b10-461f-8028-1abff36becd2 · outbound

This paper cites CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction

Reference 12

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Observation c6f1bdbb-b39c-4a6b-83fc-366ce820e953 · outbound

This paper cites EdaDet: Open-Vocabulary Object Detection Using Early Dense Alignment.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting EdaDet: Open-Vocabulary Object Detection Using Early Dense Alignment

Reference 13

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Observation 86663468-2a7f-4e64-85c8-9dd0c236e102 · outbound

This paper cites LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors

Reference 14

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Observation 3735c0c8-8a29-4242-b9bd-f06eddbe91a6 · outbound

This paper cites GPT4MTS: Prompt-based Large Language Model for Multimodal Time - series Forecasting.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting GPT4MTS: Prompt-based Large Language Model for Multimodal Time - series Forecasting

Reference 15

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Observation c75bd127-a595-4aa8-a5ca-d5e479912f38 · outbound

This paper cites TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 16

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Observation 22a43af7-8913-4ac7-b007-3538b6b130e3 · outbound

This paper cites TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

Reference 17

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Observation 9b1b3c2a-539e-4d16-b681-817de622303d · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 18

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Observation 6dbcb7f8-7cbe-4629-b5a8-de5ce51864a6 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Learning Transferable Visual Models From Natural Language Supervision

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T12:07:03.731588Z

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Observation 207155fc-79f1-48df-a8be-ea9b8c02c23d · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 20

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Observation 3149170a-f9d5-4f19-8d13-1edcce4270f1 · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 21

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Observation 54912ca9-83cd-4552-9e92-51355cf13949 · outbound

This paper cites Attention Is All You Need.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Attention Is All You Need

Reference 22

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Observation cf0a177c-f772-4609-9dec-7dfca0e508fb · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 23

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Observation 09de65a8-3bb8-4f6b-9ba8-b3c632dccf80 · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 24

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Observation 481fe33d-958a-4f36-8f27-b62ea5048f62 · outbound

This paper cites Language Models are Unsupervised Multitask Learners.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Language Models are Unsupervised Multitask Learners

Reference 25

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Observation 64d67d54-7ccc-4f16-a02c-4dfc18b97fc6 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 26

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Observation 10d78c15-6e9b-4d65-8c23-191e9661abd5 · outbound

This paper cites Qwen2.5 Technical Report.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Qwen2.5 Technical Report

Reference 27

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Observation 6d16a3bd-1360-4357-bd84-2a0f1612502f · outbound

This paper cites Deep Residual Learning for Image Recognition.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Deep Residual Learning for Image Recognition

Reference 28

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Observation 7fcbfc21-c784-4970-a3ba-12b37e970a86 · outbound

This paper cites SKIPP’D: A SKy Images and Photovoltaic Power Generation Dataset for short -term solar forecasting.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting SKIPP’D: A SKy Images and Photovoltaic Power Generation Dataset for short -term solar forecasting

Reference 29

Resolution: verified exact; doi, observed 2026-08-16T12:07:03.880434Z

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.

Observation 4e0d4032-089d-4f56-ac60-bcb44599738e · outbound

This paper cites Sky Images and PV Power Measurements for Irradiance Forecasting 2021.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Sky Images and PV Power Measurements for Irradiance Forecasting 2021

Reference 30

Resolution: verified exact; doi, observed 2026-08-16T12:07:03.865198Z

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.

Observation f52b82aa-1af7-4c54-9380-48be50b4ea68 · outbound

This paper cites CAELUS: Classification of sky conditions from 1 -min time series of global solar irradiance using variability indices and dynamic thresholds.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting CAELUS: Classification of sky conditions from 1 -min time series of global solar irradiance using variability indices and dynamic thresholds

Reference 31

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Observation d68be447-68e3-4b9f-9c08-4d7f41130aba · outbound

This paper cites Deep learning based solar radiation micro forecast by fusion of infrared cloud images and radiation data.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Deep learning based solar radiation micro forecast by fusion of infrared cloud images and radiation data

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T12:07:03.792185Z

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Observation 4f34791b-e6df-47b7-ad0c-268bac754a64 · outbound

This paper cites Photovoltaic Nowcasting With Bi-Level Spatio-Temporal Analysis Incorporating Sky Images.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Photovoltaic Nowcasting With Bi-Level Spatio-Temporal Analysis Incorporating Sky Images

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T12:07:03.796821Z

Source-reported events for the cited work

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Observation 30d45251-950e-40ac-916c-ffeb6dbf3d99 · outbound

This paper cites Sky image-based solar forecasting using deep learning with heterogeneous multi -location data: Dataset fusion versus transfer learning.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Sky image-based solar forecasting using deep learning with heterogeneous multi -location data: Dataset fusion versus transfer learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T12:07:03.801397Z

Source-reported events for the cited work

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Observation ffee58a1-0619-4b12-9003-8692ffc5f182 · outbound

This paper cites Short-term solar power forecast with deep learning: Exploring optimal input and output configuration.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Short-term solar power forecast with deep learning: Exploring optimal input and output configuration

Reference 35

Resolution: verified exact; doi, observed 2026-08-16T12:07:03.849065Z

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.

Observation 92eb9d64-e30f-4053-a10b-944bdf4c7062 · outbound

This paper cites Improving ultra-short-term photovoltaic power forecasting using a novel sky -image-based framework considering spatial -temporal feature interaction.

PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting Improving ultra-short-term photovoltaic power forecasting using a novel sky -image-based framework considering spatial -temporal feature interaction

Reference 36

Resolution: metadata mismatch; raw_fallback, observed 2026-08-16T12:07:04.526700Z

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.

Pith citing papers

Observation 85e09ceb-a398-446b-bfe7-f9155f22000c · inbound

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text cites this paper.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.600421Z

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Observation 638361eb-dff9-4a13-826f-4c3b29f784be · inbound

Solar-VLM: Multimodal Vision-Language Models for Augmented Solar Power Forecasting cites this paper.

Solar-VLM: Multimodal Vision-Language Models for Augmented Solar Power Forecasting PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:08:01.530409Z

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.