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Paper Citation Record · LEDGER

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

As of 16 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 7 inbound Pith citation observations for arXiv:2505.02417.

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

pith.paper-citation-record.v1
2505.02417 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:57:28.935266Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:09:55.718164Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:37:36.619113Z

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e98ac32-31c9-478e-90e5-cd58785dde88 · outbound

This paper cites Diffusion-based conditional ecg gen- eration with structured state space models.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Diffusion-based conditional ecg gen- eration with structured state space models

Reference 1

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Observation 6818900b-4183-4a7f-b86d-dde16c798531 · outbound

This paper cites Towards Time Series Reasoning with LLMs.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Towards Time Series Reasoning with LLMs

Reference 4

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Observation e75abe19-04a6-4382-a710-fa23fe7e816c · outbound

This paper cites Semeval-2017 task 5: Fine- grained sentiment analysis on financial microblogs and news.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Semeval-2017 task 5: Fine- grained sentiment analysis on financial microblogs and news

Reference 5

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Observation a84c77d1-d3ff-48fa-9406-2254b7f13886 · outbound

This paper cites Scaling rectified flow transformers for high- resolution image synthesis.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Scaling rectified flow transformers for high- resolution image synthesis

Reference 9

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Source-reported events for the cited work

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Observation 3259dc43-a2c9-4188-abca-32cbe8a6c923 · outbound

This paper cites Creating synthetic energy meter data using conditional diffusion and building metadata.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Creating synthetic energy meter data using conditional diffusion and building metadata

Reference 10

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Source-reported events for the cited work

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Observation 54cce58d-49b5-405c-89f4-974dfe26e1e4 · outbound

This paper cites Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers

Reference 11

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Observation 19c71e63-3ee7-4435-aa98-11c0b565e9ce · outbound

This paper cites Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning

Reference 12

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Observation 17081736-9d28-473c-94ae-2bac213adc04 · outbound

This paper cites Denoising diffusion probabilistic models.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Denoising diffusion probabilistic models

Reference 13

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Observation 4ccb5cdf-5708-4f75-971a-311f17653f35 · outbound

This paper cites Putting the human in the time series analytics loop.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Putting the human in the time series analytics loop

Reference 15

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Source-reported events for the cited work

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Observation ac0edd86-327c-4220-a978-12cd5ff5d39c · outbound

This paper cites Truth-Conditional Captioning of Time Series Data.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Truth-Conditional Captioning of Time Series Data

Reference 17

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Observation 7fe8f1f7-2f89-4ff1-8353-f27cb345cf93 · outbound

This paper cites Mimic-iv, a freely accessible electronic health record dataset.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Mimic-iv, a freely accessible electronic health record dataset

Reference 18

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Source-reported events for the cited work

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Observation 3d39891d-c824-4a8c-932a-996eb59d5045 · outbound

This paper cites Sushi: A system for unified semantic human in- teraction.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Sushi: A system for unified semantic human in- teraction

Reference 19

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verified fuzzy
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Source-reported events for the cited work

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Observation 3a4d0ad0-5856-400a-8b45-0ba14b5341a7 · outbound

This paper cites DiffuSETS: 12-lead ECG Generation Conditioned on Clinical Text Reports and Patient-Specific Information.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models DiffuSETS: 12-lead ECG Generation Conditioned on Clinical Text Reports and Patient-Specific Information

Reference 21

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Source-reported events for the cited work

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Observation bd2340e5-46e9-42d9-8fb7-90641581136d · outbound

This paper cites V oice- box: Text-guided multilingual universal speech generation at scale.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models V oice- box: Text-guided multilingual universal speech generation at scale

Reference 22

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 33365bfb-bdda-4430-af04-6f9ef651480e · outbound

This paper cites Vector Quantized Time Series Generation with a Bidirectional Prior Model.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Vector Quantized Time Series Generation with a Bidirectional Prior Model

Reference 23

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Source-reported events for the cited work

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Observation fc74503c-a33a-4b67-9b6a-5d35d45c5d7b · outbound

This paper cites Flow Matching for Generative Modeling.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Flow Matching for Generative Modeling

Reference 24

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Observation d9c257a7-cb7c-4362-acf5-a2720ab6d720 · outbound

This paper cites Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis

Reference 26

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Observation ffeb7ea0-639a-4146-8a7b-222af251e1d6 · outbound

This paper cites Time weaver: A conditional time se- ries generation model.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Time weaver: A conditional time se- ries generation model

Reference 27

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Observation abcddcae-f6f7-4209-9380-7a4c03a5242f · outbound

This paper cites Gpt-4o mini,.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Gpt-4o mini,

Reference 28

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Source-reported events for the cited work

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Observation f7cd0f7e-b61a-4dbd-b26d-48c345fb8c40 · outbound

This paper cites [Peebles and Xie, 2023] William Peebles and Saining Xie.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models [Peebles and Xie, 2023] William Peebles and Saining Xie

Reference 29

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Source-reported events for the cited work

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Observation a7f84deb-8f32-41e1-9bc6-22a90df05f3c · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Movie Gen: A Cast of Media Foundation Models

Reference 30

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Observation 9e9ffb52-2a58-43bb-bac9-cac359117b87 · outbound

This paper cites AstroM$^3$: A self-supervised multimodal model for astronomy.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models AstroM$^3$: A self-supervised multimodal model for astronomy

Reference 31

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Observation 574c9a4e-aae2-4a13-bccc-4f05c2ab5aae · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models High-resolution image synthesis with latent diffusion models

Reference 32

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Observation b9bb04f4-f27b-44db-b4d5-fe1c6af4b0a9 · outbound

This paper cites Exploring progress in mul- tivariate time series forecasting: Comprehensive bench- marking and heterogeneity analysis.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Exploring progress in mul- tivariate time series forecasting: Comprehensive bench- marking and heterogeneity analysis

Reference 33

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Observation b99a823b-51cd-4b6e-8185-ac46182f032f · outbound

This paper cites Medic: Mitigating eeg data scarcity via class-conditioned diffusion model.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Medic: Mitigating eeg data scarcity via class-conditioned diffusion model

Reference 34

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Observation a51eaa34-01b3-43ca-b3dd-9fed0f22c0ca · outbound

This paper cites Multi-modality conditional diffu- sion model for time series forecasting of live sales volume.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Multi-modality conditional diffu- sion model for time series forecasting of live sales volume

Reference 35

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Observation 1a69effb-fdd5-47dc-b50b-d6ab5216106b · outbound

This paper cites Diffstg: Probabilistic spatio-temporal graph forecasting with denoising diffusion models.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Diffstg: Probabilistic spatio-temporal graph forecasting with denoising diffusion models

Reference 36

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Observation 5275c27a-d442-4b00-9cfd-17ac92a42fcb · outbound

This paper cites Context is Key: A Benchmark for Forecasting with Essential Textual Information.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Context is Key: A Benchmark for Forecasting with Essential Textual Information

Reference 37

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Observation f273ac5a-7b0c-42ba-bf5f-a9e24a1941aa · outbound

This paper cites Autoformer: Decomposition transform- ers with auto-correlation for long-term series forecast- ing.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Autoformer: Decomposition transform- ers with auto-correlation for long-term series forecast- ing

Reference 38

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Observation db2a448b-68e3-4b4e-b397-7a57600a5d89 · outbound

This paper cites A survey on diffusion models for time series and spatio-temporal data.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models A survey on diffusion models for time series and spatio-temporal data

Reference 39

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Observation c811979e-ca65-420d-97a3-22880d6c7485 · outbound

This paper cites Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

Reference 40

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Observation cba162c7-0bc3-4d69-9f35-21904233da6a · outbound

This paper cites Diffusion-TS: Interpretable Diffusion for General Time Series Generation.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Diffusion-TS: Interpretable Diffusion for General Time Series Generation

Reference 41

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Observation c37c9277-f4f1-4805-a42b-0cb125cffdf1 · outbound

This paper cites Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition

Reference 42

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Observation eabb79eb-dbd2-4a65-82fc-93dc9827d9a4 · outbound

This paper cites TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation

Reference 2009

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Observation 979fc20f-ed77-47cc-adef-f8973236c0fc · outbound

This paper cites Mean reciprocal rank.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Mean reciprocal rank

Reference 2017

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:57:28.779318Z digest=sha256:d1c3fe103a981e26cc8f801fa44d7aaf4ad0aec42223bce0db0a9de824b0ef3f

Observation cff84350-ccf8-4fdd-a39a-d3827c21503e · outbound

This paper cites CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision

Reference 2019

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no resolver link, observed 2026-08-16T00:57:28.822969Z

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Observation 3896dad3-cfb4-4b37-b694-704ce280dd07 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Arbitrary style transfer in real-time with adaptive instance normalization

Reference 2020

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no resolver link, observed 2026-08-16T00:57:28.814936Z

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source=pdf_text observed=2026-08-16T00:57:28.814936Z digest=sha256:2f19fc5ba29cb0a7b4947419f6a1d7c824af24f8ad2447a164fc0427c6cc41a1

Observation f98cdd13-0216-445d-b6e3-37c4c0544e5e · outbound

This paper cites The Llama 3 Herd of Models.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models The Llama 3 Herd of Models

Reference 2021

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no resolver link, observed 2026-08-16T00:57:28.789072Z

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source=pdf_text observed=2026-08-16T00:57:28.789072Z digest=sha256:aec2a44c66b79e5bde7491802c8425fef63a9b26ed33d392548e8ed44a6bde02

Observation ad4c5e66-f943-430e-b33e-e8e8f56d8bc5 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 2022

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no resolver link, observed 2026-08-16T00:57:28.861669Z

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source=pdf_text observed=2026-08-16T00:57:28.861669Z digest=sha256:df7328c97f4cd3203c6cb4b432916effcbc804a4029b061bd0557d52f4181f76

Observation f2990d26-928e-4c77-88bd-3639cb4071bd · outbound

This paper cites TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model

Reference 2023

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no resolver link, observed 2026-08-16T00:57:28.758485Z

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source=pdf_text observed=2026-08-16T00:57:28.758485Z digest=sha256:acd28b0132259a93c5d419bc31a8dc7f9fccc34ef64459e4367a3e3f77dfd70e

Observation 06226aaf-2e49-498e-aed0-6690344cdcbc · outbound

This paper cites VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters

Reference 2024

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no resolver link, observed 2026-08-16T00:57:28.763902Z

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source=pdf_text observed=2026-08-16T00:57:28.763902Z digest=sha256:2e6be394a4ad1808ded38c82f7120a4a073af7f7324dafbb49c81ff3388b164c

Observation 830355e8-80d0-4898-a050-6eb056709991 · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 2025

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unresolved
no resolver link, observed 2026-08-16T00:57:28.839943Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T00:57:28.839943Z digest=sha256:548d99872560bc07ac1cf5112820e26575663b6b7377456c59d83468a81deebf

Pith citing papers

Observation 52fc1035-caa7-4fb6-95c7-c1f4c6fc9e79 · inbound

Diff-MN: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations cites this paper.

Diff-MN: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 15

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unresolved
no resolver link, observed 2026-08-03T09:34:54.180089Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:34:54.180089Z digest=sha256:59225c03a884918b4417b8ea4b201d00acb3453f4ec9dff428a2c3ae9afc3185

Observation 2171e34c-c8cc-4154-b52b-52469c391d9b · inbound

Overcoming the Modality Gap in Context-Aided Forecasting cites this paper.

Overcoming the Modality Gap in Context-Aided Forecasting T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:30:00.189444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 966e7e88-577d-4762-838b-f58e7040973e · inbound

Overcoming the Modality Gap in Context-Aided Forecasting cites this paper.

Overcoming the Modality Gap in Context-Aided Forecasting T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 2025

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no resolver link, observed 2026-08-02T18:22:22.850498Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-02T18:22:22.850498Z digest=sha256:f985689add7655f26e2087c7e543fddf68d2a3b2dd256fe0ef0dc09df0746dd4

Observation 0c352256-316f-4d3b-8d66-c226172a4848 · inbound

Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework cites this paper.

Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 13

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verified exact
arxiv_id, observed 2026-05-12T09:26:25.868732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-07T10:58:36.216692Z digest=sha256:5dd1a47364da8c710e4c5f182d465911a249b824558c93a6502886c6baaddf4f

Observation eb695a18-fb8b-4e4e-b6c4-2118899b2da1 · inbound

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation cites this paper.

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 41

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verified exact
arxiv_id, observed 2026-06-30T16:35:12.750504Z

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source=pdf_text observed=2026-06-30T16:27:45.767100Z digest=sha256:779b9feae8e5efa542473fb2741fddab8d7d34c657ce6b81041e546c8c714533

Observation 5892a3e9-901d-406e-a0be-05fd7ab862f9 · inbound

UPLOTS: A Unified Pretrained Language Model for Constrained Time-series Generation cites this paper.

UPLOTS: A Unified Pretrained Language Model for Constrained Time-series Generation T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 18

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verified exact
arxiv_id, observed 2026-07-03T04:37:36.620879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-27T13:49:51.450921Z digest=sha256:aed87273fe4351e89bb1ee4172597f897290decdec71e03a062d3618e36ef35c

Observation e4cdf594-ab22-4a57-aae4-19e8c56b2aec · inbound

Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness cites this paper.

Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models

Reference 20

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