Paper Citation Record · LEDGER

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text

As of 14 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2508.00447.

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

pith.paper-citation-record.v1
2508.00447 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:10:57.654052Z

measured 29 of 29 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 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

29 of 29 outbound references displayed

verified exact2
verified fuzzy18
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 149c51b0-aecb-49d5-a262-ce0a338be6f0 · outbound

This paper cites Large Language Models: A Survey.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Large Language Models: A Survey

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.566045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd2710f2-4dd6-469b-9396-5ac2e867eca4 · outbound

This paper cites Learning transferable visual models from natural language supervision.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Learning transferable visual models from natural language supervision

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.570247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab1a973f-5791-4f81-af60-63ef50eb0d9b · outbound

This paper cites Vlm agents generate their own memories: Distilling experience into embodied programs of thought.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Vlm agents generate their own memories: Distilling experience into embodied programs of thought

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.912864Z

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 ba806b59-659a-4982-92a8-73a7bd038118 · outbound

This paper cites Rethinking vlms and llms for image classification.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Rethinking vlms and llms for image classification

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.904957Z

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 84c0b498-b7a4-40ae-893a-5076fbf49f16 · outbound

This paper cites Regression in EO: Are VLMs Up to the Challenge?.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Regression in EO: Are VLMs Up to the Challenge?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.580373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37c8c514-ea71-4243-888f-106e2da05f68 · outbound

This paper cites From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.584389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06d4ebcc-338b-4ed5-8fcd-de514be79caa · outbound

This paper cites Multi-step time series forecasting with an ensemble of varied length mixture models.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Multi-step time series forecasting with an ensemble of varied length mixture models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.896346Z

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 88a1cdb1-3f66-4c60-9aaf-442fd10cca4d · outbound

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

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text CogVLM2: Visual Language Models for Image and Video Understanding

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.591421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fefd3627-07d8-4bf1-b645-0d9866c49b91 · outbound

This paper cites Integrating llms with its: Recent advances, potentials, challenges, and future directions.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Integrating llms with its: Recent advances, potentials, challenges, and future directions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.889206Z

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 ad8958b7-ae7b-4f20-9d7c-4532d0a30b87 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.597170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 708f493d-fa75-4949-879b-c5ed5b98eb1a · outbound

This paper cites Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.603925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a3baa57-ccf5-416c-b4aa-8ffdbb9b11d3 · outbound

This paper cites Leveraging temporal contextualization for video action recognition.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Leveraging temporal contextualization for video action recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.880538Z

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 200ee217-6049-461d-97c3-20ac5323b43e · outbound

This paper cites C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T10:10:57.611080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3af5bf5a-1e2a-4926-ac49-757828e85738 · outbound

This paper cites Pattern recognition and prediction in time series data through retrieval- augmented techniques.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Pattern recognition and prediction in time series data through retrieval- augmented techniques

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.871564Z

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 30b41a4b-27b0-49a2-8b9e-55a1c9f526df · outbound

This paper cites Driver intention prediction using text prompts with in-cabin and out-cabin cameras.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Driver intention prediction using text prompts with in-cabin and out-cabin cameras

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.862058Z

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 02535a6d-e486-452a-b1d2-2551c8154a34 · outbound

This paper cites Diverse data augmentation with dif- fusions for effective test-time prompt tuning.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Diverse data augmentation with dif- fusions for effective test-time prompt tuning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.851547Z

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 2a3e5744-844b-4eea-a6ae-4b2e99768ebb · outbound

This paper cites FungalZSL: Zero-Shot Fungal Classification with Image Captioning Using a Synthetic Data Approach.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text FungalZSL: Zero-Shot Fungal Classification with Image Captioning Using a Synthetic Data Approach

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:10:57.692926Z

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 e39d859c-8326-4a61-ad81-65683ad4de9a · outbound

This paper cites Fungal biology.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Fungal biology

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.842797Z

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 76d98e21-6e5f-4a84-8f23-c50cecc9dc07 · outbound

This paper cites Assembling the fungal tree of life: progress, classification, and evolution of subcellular traits.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Assembling the fungal tree of life: progress, classification, and evolution of subcellular traits

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.834678Z

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 31ccd902-c5bc-4f0a-8d96-7db992310a9c · outbound

This paper cites Developments in fungal taxonomy.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Developments in fungal taxonomy

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.825328Z

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 26edf3e3-5f98-40be-b0df-33f4c42e9440 · outbound

This paper cites Assessment of fungal spores and spore-like diversity in environmental samples by targeted lysis.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Assessment of fungal spores and spore-like diversity in environmental samples by targeted lysis

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.815366Z

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 5e4e9dc0-eb84-4df6-b842-fdc7a8f03d09 · outbound

This paper cites Architecture and developmental dynamics of the external mycelium of the arbuscular mycorrhizal fungus glomus intraradices grown under monoxenic conditions.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Architecture and developmental dynamics of the external mycelium of the arbuscular mycorrhizal fungus glomus intraradices grown under monoxenic conditions

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.806844Z

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 85fc7581-3e42-4ef4-851f-6102411aadc6 · outbound

This paper cites Study of kinetic model for fungal spore germination under dynamic conditions: Case study on germination of penicillium expansum spores.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Study of kinetic model for fungal spore germination under dynamic conditions: Case study on germination of penicillium expansum spores

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.796630Z

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 662c32db-1362-43e2-916a-dff97d1ddc09 · outbound

This paper cites Pathways of pathogenicity: transcriptional stages of germination in the fatal fungal pathogen rhizopus delemar.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Pathways of pathogenicity: transcriptional stages of germination in the fatal fungal pathogen rhizopus delemar

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.787085Z

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 1f2ddbcc-5c21-465a-a143-ca725ba058e7 · outbound

This paper cites A model for growth of a single fungal hypha based on well-mixed tanks in series: simulation of nutrient and vesicle transport in aerial reproductive hyphae.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text A model for growth of a single fungal hypha based on well-mixed tanks in series: simulation of nutrient and vesicle transport in aerial reproductive hyphae

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.777381Z

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 c75dbd80-d519-4699-9dc0-8a43782189e2 · outbound

This paper cites Neurospora crassa nadph oxidase nox-1 is localized in the vacuolar system and the plasma membrane.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Neurospora crassa nadph oxidase nox-1 is localized in the vacuolar system and the plasma membrane

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.766849Z

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 1f1b6b55-5eea-4796-bb2b-4c01b29d5ef3 · outbound

This paper cites Synthetic Fungi Datasets: A Time-Aligned Approach.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Synthetic Fungi Datasets: A Time-Aligned Approach

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:10:57.680562Z

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 204e3eb2-1690-49f5-bbd4-d825d233d203 · outbound

This paper cites Fungalzsl: A fine-grained synthetic dataset for zero-shot fungi classification.

CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text Fungalzsl: A fine-grained synthetic dataset for zero-shot fungi classification

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:10:57.756848Z

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.

Pith citing papers

No inbound Pith citation observations are available.