Paper Citation Record · LEDGER

MoTime: A Dataset Suite for Multimodal Time Series Forecasting

As of 11 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2505.15072.

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

pith.paper-citation-record.v1
2505.15072 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:27:22.560254Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:49:34.989871Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

verified exact2
verified fuzzy43
unresolved19
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6c93e9b6-4e57-4084-8cbf-a89262a9c07f · outbound

This paper cites https://en.wikipedia.org/wiki/Dow_Jones_ Industrial_Average.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting https://en.wikipedia.org/wiki/Dow_Jones_ Industrial_Average

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.778724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1f1841ee-02b2-49db-8326-2f98685e2415 · outbound

This paper cites https://www.kaggle.com/competitions/ web-traffic-time-series-forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting https://www.kaggle.com/competitions/ web-traffic-time-series-forecasting

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.766884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c91f1d01-5cba-425a-a017-7f4bcdd7cb2c · outbound

This paper cites DreamDiffusion: Generating High-Quality Images from Brain EEG Signals.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting DreamDiffusion: Generating High-Quality Images from Brain EEG Signals

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:18.977117Z

Source-reported events for the cited work

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Observation 5d5a8573-8d24-4b00-9ecb-2a8b923716c0 · outbound

This paper cites Multi-modal financial time-series retrieval through latent space projections.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Multi-modal financial time-series retrieval through latent space projections

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.752913Z

Source-reported events for the cited work

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Observation 61d68120-99cb-495b-a3aa-ffc4ce1fd3d0 · outbound

This paper cites TEMPO: Prompt-based generative pre-trained transformer for time series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting TEMPO: Prompt-based generative pre-trained transformer for time series forecasting

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.101536Z

Source-reported events for the cited work

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Observation 3b7d6a56-2f6f-47e8-b249-cd1acf329d6c · outbound

This paper cites Fashion trend forecasting using machine learning tech- niques: A review.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Fashion trend forecasting using machine learning tech- niques: A review

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.734453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cc6d596e-4dbd-4685-a75e-fc7ab8783f7a · outbound

This paper cites LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.228501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9073af8-c171-463f-b7a0-24e6835666ca · outbound

This paper cites Mtbench: A multimodal time series benchmark for temporal reasoning and question answering, 2025.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Mtbench: A multimodal time series benchmark for temporal reasoning and question answering, 2025

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.722725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f797461-f095-45db-98ba-75420db5f1f6 · outbound

This paper cites Terra: A multimodal spatio-temporal dataset spanning the earth.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Terra: A multimodal spatio-temporal dataset spanning the earth

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.710444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c7cc4116-3c0f-4139-9ae4-91fee0c334f7 · outbound

This paper cites An Image Dataset for Benchmarking Recommender Systems with Raw Pixels.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting An Image Dataset for Benchmarking Recommender Systems with Raw Pixels

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:27:23.016163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 79ef48ad-87d9-4c88-ad67-43dc929c853c · outbound

This paper cites Toto: Time Series Optimized Transformer for Observability.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Toto: Time Series Optimized Transformer for Observability

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.475470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45404ba9-c917-4539-9ca8-fd7b3bdfe3cb · outbound

This paper cites Nyc bike sharing network: Time-series enhanced nodes and edges dataset, 2024.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Nyc bike sharing network: Time-series enhanced nodes and edges dataset, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.699297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 46a947bf-dca9-4d28-8687-e1a45c7d730f · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting A decoder-only foundation model for time-series forecasting

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.687614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ae13b8c1-bf5a-4b58-8ef8-635d8624181a · outbound

This paper cites FNSPID: A Comprehensive Financial News Dataset in Time Series.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting FNSPID: A Comprehensive Financial News Dataset in Time Series

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.638690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc25b241-9427-4422-b950-4c06e9236c28 · outbound

This paper cites Uci machine learning repository.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Uci machine learning repository

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.675515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fa1d415c-78c9-4baf-80c3-3f138197388f · outbound

This paper cites Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.768330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47f9d405-29b6-48f1-a12b-476c6675fb20 · outbound

This paper cites Timegpt: The first foundation model for time series.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Timegpt: The first foundation model for time series

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.662949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5cc004af-feb1-4749-a442-ba529c2d961d · outbound

This paper cites Monash Time Series Forecasting Archive.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Monash Time Series Forecasting Archive

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.898165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57176946-dbce-435f-832b-70bb40773379 · outbound

This paper cites Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.949996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ed57ea3-8783-4c85-b5ce-e613750ab92a · outbound

This paper cites Icbhi 2017 challenge: Respiratory sound database.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Icbhi 2017 challenge: Respiratory sound database

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.650227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fd4e4e20-d7b2-4621-8442-0f5a8ccc118c · outbound

This paper cites GPT4MTS: Prompt-based large language model for multimodal time-series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting GPT4MTS: Prompt-based large language model for multimodal time-series forecasting

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.638236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d329883e-9242-4fb1-b6cc-06baace3ad5a · outbound

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

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:20.106054Z

Source-reported events for the cited work

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Observation 1aa0093b-815c-488d-9094-1b1c1712eb13 · outbound

This paper cites Mimic-iv, a freely accessible electronic health record dataset.Scientific data, 10(1):1–8, 2023.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Mimic-iv, a freely accessible electronic health record dataset.Scientific data, 10(1):1–8, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.627176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f8f6a4ec-aa56-4766-8eff-b20cd28dd539 · outbound

This paper cites Mimic-iii, a freely accessible critical care database.Scientific data, 3:160035, 2016.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Mimic-iii, a freely accessible critical care database.Scientific data, 3:160035, 2016

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.614831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ba0b758c-6f87-4030-8608-9fffd4fa9d58 · outbound

This paper cites Gdelt: Global data on events, location, and tone.ISA Annual Convention, 2013.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Gdelt: Global data on events, location, and tone.ISA Annual Convention, 2013

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.602089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a093169b-de37-4c43-acf8-87bf29277757 · outbound

This paper cites Frozen language model helps ecg zero-shot learning.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Frozen language model helps ecg zero-shot learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.590683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dc056bd8-d7c6-44d4-955a-9bef3cd4b60c · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Foundation models for time series analysis: A tutorial and survey

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.579284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a1c921fb-7684-4107-99d8-d73a05a3f9bc · outbound

This paper cites Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, and B.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, and B

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.566719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e1bccf66-24d2-4f31-bccc-0bd4bb089916 · outbound

This paper cites Aditya Prakash.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Aditya Prakash

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.554136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bab97a92-f2ad-46b9-86b5-d6896cdc22f4 · outbound

This paper cites Moirai-moe: Empowering time series foundation models with sparse mixture of experts.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Moirai-moe: Empowering time series foundation models with sparse mixture of experts

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.542838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f05f492-a442-4a94-913b-627464b306e7 · outbound

This paper cites The m3-competition: results, conclusions and implica- tions.International Journal of Forecasting, 16(4):451–476, 2000.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting The m3-competition: results, conclusions and implica- tions.International Journal of Forecasting, 16(4):451–476, 2000

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.531500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 698ea8de-5dfa-4a25-aa69-811a00c8cb76 · outbound

This paper cites The m4 competition: Results, findings, conclusion and way forward.International Journal of Forecasting, 34(4):802– 808, 2018.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting The m4 competition: Results, findings, conclusion and way forward.International Journal of Forecasting, 34(4):802– 808, 2018

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.518882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ef0905af-0ee8-4646-9c5d-fa2ebab8af7f · outbound

This paper cites M5 accuracy competi- tion: Results, findings and conclusions.International Journal of Forecasting, 38(4):1279–1282, 2022.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting M5 accuracy competi- tion: Results, findings and conclusions.International Journal of Forecasting, 38(4):1279–1282, 2022

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.507769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f7f27fd-357c-4cc9-8242-8eb0714e5a65 · outbound

This paper cites Multi-source social feedback of online news feeds, 2018.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Multi-source social feedback of online news feeds, 2018

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.495308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4dd485de-2e1c-4dac-be29-d05cc0eb1beb · outbound

This paper cites WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting WPMixer: Efficient Multi-Resolution Mixing for Long-Term Time Series Forecasting

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:27:22.828202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7c9778b7-74f5-4ca4-a314-ed1e1f675c31 · outbound

This paper cites Taxi and Limousine Commission.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Taxi and Limousine Commission

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.483238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6f15e194-14cb-4a51-a427-0fd41633f3b8 · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting A time series is worth 64 words: Long-term forecasting with transformers

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.470963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5b747426-f306-4d09-a358-dd55b9c9c407 · outbound

This paper cites Nixtla foundation benchmark.Nixtla, 2024.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Nixtla foundation benchmark.Nixtla, 2024

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.458894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5453b5ea-dc16-4e39-928c-7c0373b58a13 · outbound

This paper cites Papadopoulos, Christos Koutlis, Symeon Papadopoulos, and Ioannis Kompatsiaris.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Papadopoulos, Christos Koutlis, Symeon Papadopoulos, and Ioannis Kompatsiaris

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.445033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2abd520d-ed88-49fb-be3c-8335b6fc71a4 · outbound

This paper cites Lag-llama: Towards foundation models for probabilistic time series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Lag-llama: Towards foundation models for probabilistic time series forecasting

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.429462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 75381183-d719-4a79-81b4-b34c2274e50d · outbound

This paper cites Multimodal multi-task financial risk forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Multimodal multi-task financial risk forecasting

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.415966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2499005d-f229-41f1-941f-1d37c9de7e34 · outbound

This paper cites Chronos: Learning the Language of Time Series.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Chronos: Learning the Language of Time Series

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:21.196334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4b41745-e382-4e36-9412-690233477e64 · outbound

This paper cites Time-moe: Billion-scale time series foundation models with mixture of experts.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Time-moe: Billion-scale time series foundation models with mixture of experts

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.403938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 386f4925-3a09-47cb-babc-116c1ce5f817 · outbound

This paper cites Well googled is half done: Multimodal forecasting of new fashion product sales with image-based google trends.Journal of Forecasting, 43(6):1982–1997, 2024.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Well googled is half done: Multimodal forecasting of new fashion product sales with image-based google trends.Journal of Forecasting, 43(6):1982–1997, 2024

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.392090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e31eeb0-b4cd-4aa8-b341-d894e6356cf2 · outbound

This paper cites The multi-modal universe of fast-fashion: The visuelle 2.0 benchmark.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting The multi-modal universe of fast-fashion: The visuelle 2.0 benchmark

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.379870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a1a2dc02-88a8-441b-948b-e8548e74388d · outbound

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

MoTime: A Dataset Suite for Multimodal Time Series Forecasting TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:21.397057Z

Source-reported events for the cited work

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Observation a6db80ef-d98c-4aa9-9a71-fd02137dbf36 · outbound

This paper cites Ptb-xl, a large publicly available electrocardiography dataset.Scientific Data, 7(1):154, 2020.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Ptb-xl, a large publicly available electrocardiography dataset.Scientific Data, 7(1):154, 2020

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.367302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d3538f75-47f8-4d62-bfc2-fd1db26eefda · outbound

This paper cites Foundation Models for Time Series Analysis: A Tutorial and Survey.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Foundation Models for Time Series Analysis: A Tutorial and Survey

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:21.526188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 449fffe3-00ba-4ecf-a103-1ec635a4a422 · outbound

This paper cites Unified training of universal time series forecasting transformers.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Unified training of universal time series forecasting transformers

Reference 49

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Observation a13c9da7-cd3c-44c3-80a9-85246f14f489 · outbound

This paper cites GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

Reference 50

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This paper cites Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts

Reference 51

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MoTime: A Dataset Suite for Multimodal Time Series Forecasting Unresolved cited work

Reference 52

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Observation 755a93af-3549-4ab4-90bc-25c6b7a1aff3 · outbound

This paper cites Web traffic forecasting with cnn and fibonacci median.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Web traffic forecasting with cnn and fibonacci median

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.328973Z

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This paper cites Community trend prediction on heterogeneous graph in e-commerce.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Community trend prediction on heterogeneous graph in e-commerce

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:24.077498Z

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Observation 5548c072-3bed-4be8-bf2e-49bc4641c4e9 · outbound

This paper cites Are Transformers Effective for Time Series Forecasting?.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Are Transformers Effective for Time Series Forecasting?

Reference 55

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This paper cites Moment: A foundation model for multivariate time series.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Moment: A foundation model for multivariate time series

Reference 56

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This paper cites Deep Time Series Models: A Comprehensive Survey and Benchmark.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Deep Time Series Models: A Comprehensive Survey and Benchmark

Reference 57

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This paper cites From news to forecast: Integrating event analysis in llm-based time series forecasting with reflection.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting From news to forecast: Integrating event analysis in llm-based time series forecasting with reflection

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:23.967886Z

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Observation 57c0cb5d-3849-4ccd-8d51-1a6f4df6e769 · outbound

This paper cites Lemma-rca: A large multi-modal multi-domain dataset for root cause analysis, 2024.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Lemma-rca: A large multi-modal multi-domain dataset for root cause analysis, 2024

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:23.705246Z

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This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:23.621859Z

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Observation 66d66cc3-a962-42a8-9f31-8d99ef31dbf9 · outbound

This paper cites Ccwtf: Codebase for cold-start and varying-length time series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Ccwtf: Codebase for cold-start and varying-length time series forecasting

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:23.443841Z

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Observation 316a8a2e-2cc4-4836-ad2c-c455a86edc44 · outbound

This paper cites Scalable transformer for high dimensional multivariate time series forecast- ing.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Scalable transformer for high dimensional multivariate time series forecast- ing

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:23.340933Z

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Observation ce42ec97-ce05-4d22-8bd4-911e28ba8bb7 · outbound

This paper cites Unveiling the potential of text in high-dimensional time series forecasting.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Unveiling the potential of text in high-dimensional time series forecasting

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:27:23.133430Z

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MoTime: A Dataset Suite for Multimodal Time Series Forecasting Unresolved cited work

Reference 2017

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:27:24.305244Z

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Pith citing papers

Observation 15d3b699-bdd6-4f4e-8162-d2bcbee9c8c8 · inbound

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models cites this paper.

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models MoTime: A Dataset Suite for Multimodal Time Series Forecasting

Reference 153

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