Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TimeGPT-1
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 85 inbound Pith citation observations for arXiv:2310.03589.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:10:55.796302Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
23
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 741e0c07-cab5-4929-8f69-ca69c3476438 · inbound
A decoder-only foundation model for time-series forecasting cites this paper.
A decoder-only foundation model for time-series forecasting TimeGPT-1
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T18:07:21.305025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e42ed69a-9d9d-4a6f-9d83-57b3a76c07bc · inbound
Deep Time Series Models: A Comprehensive Survey and Benchmark cites this paper.
Deep Time Series Models: A Comprehensive Survey and Benchmark TimeGPT-1
Reference 199
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T23:05:51.326646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 10f81e10-196d-4afb-9648-ad53da79c612 · inbound
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis TimeGPT-1
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T19:45:47.230675Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 22cf518e-ee45-4847-b93a-85e36c5883cc · inbound
Causal Time-Series Synchronization for Multi-Dimensional Forecasting cites this paper.
Causal Time-Series Synchronization for Multi-Dimensional Forecasting TimeGPT-1
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T20:01:55.746616Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f2643bf-0da5-47b8-ab5e-f04db8df77ce · inbound
On Foundation Models for Dynamical Systems from Purely Synthetic Data cites this paper.
On Foundation Models for Dynamical Systems from Purely Synthetic Data TimeGPT-1
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:29:02.552522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ad170c2-1ff8-49e8-ad6b-cd94e9e7ed77 · inbound
Leveraging Time-Series Foundation Model for Subsurface Well Logs Prediction and Anomaly Detection cites this paper.
Leveraging Time-Series Foundation Model for Subsurface Well Logs Prediction and Anomaly Detection TimeGPT-1
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:31:30.208718Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5cf3bf9-2181-4e62-97d3-da682543fbf1 · inbound
Tube Loss: A Novel Approach for Prediction Interval Estimation cites this paper.
Tube Loss: A Novel Approach for Prediction Interval Estimation TimeGPT-1
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T07:47:42.593880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c12c4d3d-2dd2-4ac6-8870-7017209ea21b · inbound
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting cites this paper.
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting TimeGPT-1
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T18:18:54.830131Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 508638e7-6adb-4cc4-b4c0-bc4ac1d7dc7e · inbound
Federated Foundation Models on Heterogeneous Time Series cites this paper.
Federated Foundation Models on Heterogeneous Time Series TimeGPT-1
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T17:31:07.022374Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 489e688a-f26f-40b2-8adb-cd29e4c1e9f4 · inbound
Financial Fine-tuning a Large Time Series Model cites this paper.
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:43:21.397655Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22caccdb-e3b0-4a37-a350-a89f399ba206 · inbound
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data cites this paper.
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data TimeGPT-1
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:04:55.919643Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d882338-7047-4449-82df-a10f9060b345 · inbound
Comparative Analysis of Zero-Shot Capability of Time-Series Foundation Models in Short-Term Load Prediction cites this paper.
Comparative Analysis of Zero-Shot Capability of Time-Series Foundation Models in Short-Term Load Prediction TimeGPT-1
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:43:06.563433Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 384e4d26-321d-411a-bae7-ed9d10a51772 · inbound
Time Series Foundational Models: Their Role in Anomaly Detection and Prediction cites this paper.
Time Series Foundational Models: Their Role in Anomaly Detection and Prediction TimeGPT-1
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:48:13.084035Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9f4281c-ba6f-445f-800a-3c582cb83a23 · inbound
A Survey on Time-Series Distance Measures cites this paper.
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:20:49.604422Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82124b00-a9b9-4174-b74a-3e8d5486613f · inbound
TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting cites this paper.
TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting TimeGPT-1
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:21:23.637561Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a3e0525-1255-4b51-8f8b-ab8e3a0d4224 · inbound
DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework cites this paper.
DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework TimeGPT-1
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:52:11.011595Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df04bff1-a941-4726-a4fd-e6f2d586f64e · inbound
Time Series Language Model for Descriptive Caption Generation cites this paper.
Time Series Language Model for Descriptive Caption Generation TimeGPT-1
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:25:24.622723Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e814cc7-24e6-4aa4-827c-8e6952481b18 · inbound
Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation cites this paper.
Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation TimeGPT-1
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:27:51.698074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf08562c-67de-4af0-95d2-c4a002ae8f9d · inbound
MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models cites this paper.
MoE$^2$: Optimizing Collaborative Inference for Edge Large Language Models TimeGPT-1
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:13:14.790654Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4cc52edc-b183-4284-88ac-6d66cc27d3d7 · inbound
Artificial Neural Networks for Magnetoencephalography: A review of an emerging field cites this paper.
Artificial Neural Networks for Magnetoencephalography: A review of an emerging field TimeGPT-1
Reference 216
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T18:10:55.273421Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d99806b3-c931-49db-92e5-1c172be45403 · inbound
Multi-source Multi-level Multi-token Ethereum Dataset and Benchmark Platform cites this paper.
Multi-source Multi-level Multi-token Ethereum Dataset and Benchmark Platform TimeGPT-1
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:48:58.070144Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 537eb3c4-b497-4493-8775-1530b5b5a5ed · inbound
One Fits All: General Mobility Trajectory Modeling via Masked Conditional Diffusion cites this paper.
One Fits All: General Mobility Trajectory Modeling via Masked Conditional Diffusion TimeGPT-1
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:18:38.969814Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31d9c9b9-25f4-4554-aefd-25b2cfee3ef7 · inbound
Foundation Models for CPS-IoT: Opportunities and Challenges cites this paper.
Foundation Models for CPS-IoT: Opportunities and Challenges TimeGPT-1
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:30:41.513041Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8de66fc6-5dce-4b6a-9e8e-48d9e2a11903 · inbound
A Novel Hybrid Approach to Contraceptive Demand Forecasting: Integrating Point Predictions with Probabilistic Distributions cites this paper.
A Novel Hybrid Approach to Contraceptive Demand Forecasting: Integrating Point Predictions with Probabilistic Distributions TimeGPT-1
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:52:20.545700Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 60ce9eeb-2195-453a-87bd-20fcd5e57ac4 · inbound
Out-of-Distribution Generalization in Time Series: A Survey cites this paper.
Out-of-Distribution Generalization in Time Series: A Survey TimeGPT-1
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T00:22:18.377467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1cc7001f-1a5e-472c-9161-eea435196a94 · inbound
Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics cites this paper.
Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics TimeGPT-1
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:10:55.796302Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed7fca74-0a58-41b4-b9e6-3787aeabcd4e · inbound
Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts cites this paper.
Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts TimeGPT-1
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T04:27:56.019336Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 61b5ef2b-72f7-4a7c-a80f-dd5b3f1c0911 · inbound
How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades cites this paper.
How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades TimeGPT-1
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T04:24:33.666088Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 88106994-e37c-46eb-b8a6-500fe4de2d27 · inbound
Does Scaling Law Apply in Time Series Forecasting? cites this paper.
Does Scaling Law Apply in Time Series Forecasting? TimeGPT-1
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:19:04.641030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 048ab425-1422-456d-b747-8be202518b50 · inbound
Zero-Shot Forecasting Mortality Rates: A Global Study cites this paper.
Zero-Shot Forecasting Mortality Rates: A Global Study TimeGPT-1
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:46:44.269096Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8a0ee13-8c53-4301-9c12-6f7c120df91b · inbound
Byte Pair Encoding for Efficient Time Series Forecasting cites this paper.
Byte Pair Encoding for Efficient Time Series Forecasting TimeGPT-1
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:39:35.611785Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2d401c2-3cd8-4940-9643-ddc997643626 · inbound
Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions cites this paper.
Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions TimeGPT-1
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:37:40.026957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d0bac1d-27dc-4e3e-b8b4-0ae36e08de12 · inbound
When can isotropy help adapt LLMs' next word prediction to numerical domains? cites this paper.
When can isotropy help adapt LLMs' next word prediction to numerical domains? TimeGPT-1
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:52.058405Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 485b35e0-0352-4d86-b9b2-53a2f65ae916 · inbound
BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models cites this paper.
BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models TimeGPT-1
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:45:24.708103Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c02b98b9-3b9d-419c-9de6-c0e12b8ea640 · inbound
Tube Loss based Deep Networks For Improving the Probabilistic Forecasting of Wind Speed cites this paper.
Tube Loss based Deep Networks For Improving the Probabilistic Forecasting of Wind Speed TimeGPT-1
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:37:50.128128Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6da20ae3-08ea-4d5c-9efc-5c2919b6b37f · inbound
DELPHYNE: A Pre-Trained Model for General and Financial Time Series cites this paper.
DELPHYNE: A Pre-Trained Model for General and Financial Time Series TimeGPT-1
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:15:53.294808Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0db9cfab-b5de-4839-a3db-60d7ff91c9b0 · inbound
From Transformers to Large Language Models: A systematic review of AI applications in the energy sector towards Agentic Digital Twins cites this paper.
From Transformers to Large Language Models: A systematic review of AI applications in the energy sector towards Agentic Digital Twins TimeGPT-1
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:21:52.958296Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a369834d-7161-44a5-9429-3313fde7872a · inbound
Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting cites this paper.
Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting TimeGPT-1
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:23:43.233445Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c36acae8-4ca9-47ea-8cc8-2da8391ec8d4 · inbound
Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics cites this paper.
Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics TimeGPT-1
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:09:33.242473Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a829294-7624-43eb-a810-be018f89cc28 · inbound
Forecast-Then-Optimize Deep Learning Methods cites this paper.
Reference 468
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:42:52.484961Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d243b9a0-411e-45bc-8b76-99b6c246f24f · inbound
SEED: A Structural Encoder for Embedding-Driven Decoding in Time Series Prediction with LLMs cites this paper.
SEED: A Structural Encoder for Embedding-Driven Decoding in Time Series Prediction with LLMs TimeGPT-1
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:58:51.205523Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c16f3b36-77a0-4f66-9b3e-cabb226d798f · inbound
Towards Time Series Generation Conditioned on Unstructured Natural Language cites this paper.
Towards Time Series Generation Conditioned on Unstructured Natural Language TimeGPT-1
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:59:18.312623Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dac50c5c-63fd-4ebb-8777-4d35dc284b73 · inbound
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions cites this paper.
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions TimeGPT-1
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:27:49.052504Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5737f86-07d4-4b73-ada0-1a3e23a7953e · inbound
Towards Foundation Auto-Encoders for Time-Series Anomaly Detection cites this paper.
Towards Foundation Auto-Encoders for Time-Series Anomaly Detection TimeGPT-1
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:47:09.360142Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 50ebe2c6-9892-4347-b176-1771797074a0 · inbound
Time Series Foundation Models for Multivariate Financial Time Series Forecasting cites this paper.
Time Series Foundation Models for Multivariate Financial Time Series Forecasting TimeGPT-1
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:49:23.421044Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation acb79544-af94-4b0e-adb3-125022c1fd04 · inbound
A Survey of AIOps in the Era of Large Language Models cites this paper.
A Survey of AIOps in the Era of Large Language Models TimeGPT-1
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:26:36.610800Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c787580-e45c-42aa-8cd4-ffffa41d99b5 · inbound
Foundation Models for Demand Forecasting via Dual-Strategy Ensembling cites this paper.
Foundation Models for Demand Forecasting via Dual-Strategy Ensembling TimeGPT-1
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:09:39.457548Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d87a90c-8052-41f9-a9cc-190e694f08a2 · inbound
Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models cites this paper.
Hallucination Detection and Mitigation with Diffusion in Multi-Variate Time-Series Foundation Models TimeGPT-1
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:54:25.374333Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e578e2c-0b11-40f6-99a7-fc7a273e2436 · inbound
Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles cites this paper.
Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles TimeGPT-1
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:27:46.288869Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7792c090-9eda-4c44-bece-1d8cce6c748f · inbound
On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating cites this paper.
On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating TimeGPT-1
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:10:28.332238Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c5c5b43-e23c-4579-9405-2e16353d7e23 · inbound
CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams cites this paper.
CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams TimeGPT-1
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:28:02.542035Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14ac2c0e-190a-4f0f-a57d-df64a42472f3 · inbound
Foundation vs. Specialized Models: Evaluating Catastrophic Forgetting in Continual Time Series Forecasting cites this paper.
Foundation vs. Specialized Models: Evaluating Catastrophic Forgetting in Continual Time Series Forecasting TimeGPT-1
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:23:09.322846Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 381b5e9a-4509-45b5-9b42-9ce1fd9133b4 · inbound
TimeSAE: Causal Sparse Decoding for Faithful Explanations of Black-Box Time Series Models cites this paper.
TimeSAE: Causal Sparse Decoding for Faithful Explanations of Black-Box Time Series Models TimeGPT-1
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:37:06.818289Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6609867-602c-43d1-b628-f2c35425d329 · inbound
Deep Learning Network-Temporal Models For Traffic Prediction cites this paper.
Deep Learning Network-Temporal Models For Traffic Prediction TimeGPT-1
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T22:51:55.339022Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f90ee967-245b-43ca-aa57-0239fa09bade · inbound
Frequency-Guided Deformable Networks for Continuous Phase Alignment cites this paper.
Frequency-Guided Deformable Networks for Continuous Phase Alignment TimeGPT-1
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T20:39:48.872028Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7700dfef-6ea5-4add-a37f-737204f914ca · inbound
Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook cites this paper.
Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook TimeGPT-1
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T18:53:08.568299Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7462044f-0ae4-487c-ade1-04eb406fa81d · inbound
Discrete Prototypical Memories for Federated Time Series Foundation Models cites this paper.
Discrete Prototypical Memories for Federated Time Series Foundation Models TimeGPT-1
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:35:51.998168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 91f65edb-84a9-499c-92ad-0b684e4fff8c · inbound
Wearable AI in the Era of Large Sensor Models cites this paper.
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T08:30:58.093028Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9eea6a47-becf-456a-b26e-3b7198d584dd · 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 TimeGPT-1
Reference 33
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T09:26:25.918576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ec53823e-9cc7-420e-901f-d581ce86de49 · inbound
TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models cites this paper.
TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models TimeGPT-1
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T12:04:38.796054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 514f374d-55c9-4e1c-a02e-329ce2e22061 · inbound
Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP cites this paper.
Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP TimeGPT-1
Reference 35
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T16:05:48.856087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1318fb0a-62b9-4f28-a21c-c7b7362010e3 · inbound
FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting cites this paper.
FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting TimeGPT-1
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T07:13:17.156311Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0ed8ba2a-37e8-484f-ad8f-02bb87dcb2c7 · inbound
Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling cites this paper.
Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling TimeGPT-1
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T19:33:54.166610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9a55c10e-d5bf-4b3f-a65a-ed10436a9212 · inbound
ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection cites this paper.
ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection TimeGPT-1
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T21:16:14.104647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 723fa841-65b8-46a4-88cb-ba785e4f724e · inbound
Towards Intrusion Detection Systems for RPL-based IoT Networks using Foundation Models cites this paper.
Towards Intrusion Detection Systems for RPL-based IoT Networks using Foundation Models TimeGPT-1
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T03:56:35.006416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e9507ac3-ba9b-4c00-ad28-bfcdf9813204 · inbound
GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series cites this paper.
GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series TimeGPT-1
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T20:47:23.114904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ca34f364-baca-4e8f-ac1d-c30ad2b21f27 · 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 TimeGPT-1
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T04:37:36.606614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0155af0b-ab5a-4cdf-9e7e-8dad719abefa · inbound
WEQA: Wearable hEalth Question Answering with Query-Adaptive Agentic Reasoning cites this paper.
WEQA: Wearable hEalth Question Answering with Query-Adaptive Agentic Reasoning TimeGPT-1
Reference 55
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T21:08:58.454968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e5e117e9-73b2-4582-b02d-8ede89970bba · inbound
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios cites this paper.
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios TimeGPT-1
Reference 27
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T16:09:56.452773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3cf9862e-d4b9-42f9-9e0d-c52ff4abe3b1 · inbound
Pretrained Time-Series Foundation Models for Financial Return Forecasting cites this paper.
Pretrained Time-Series Foundation Models for Financial Return Forecasting TimeGPT-1
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T15:29:56.385723Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2482b7c2-e233-46f6-8b1d-f1a953501597 · inbound
Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings cites this paper.
Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings TimeGPT-1
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T19:13:52.912021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a3dd5446-313e-44e5-aa67-6821f2b3f617 · inbound
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis cites this paper.
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis TimeGPT-1
Reference 100
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T17:38:43.311229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 84f37046-3b1a-4769-bf1e-415416f55bcc · inbound
Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics cites this paper.
Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics TimeGPT-1
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T17:28:44.086406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8301df50-8136-4f8c-b79c-84a327973aff · inbound
Modular Foundation Models for Time-Series Perception in Digital Twins cites this paper.
Modular Foundation Models for Time-Series Perception in Digital Twins TimeGPT-1
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T01:22:51.284207Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49cb55e1-4e19-437a-98e8-c5e6419e73ca · inbound
Forecasting Realized Volatility with Time Series Foundation Models: A Comparison with Econometric Benchmarks cites this paper.
Forecasting Realized Volatility with Time Series Foundation Models: A Comparison with Econometric Benchmarks TimeGPT-1
Reference 74
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-07T19:34:06.415438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 93e2fa8e-238c-4dbb-923d-91d11d9dd8ac · inbound
From Vector Autoregressions to AI-based Time Series Forecasting: A Review cites this paper.
From Vector Autoregressions to AI-based Time Series Forecasting: A Review TimeGPT-1
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T02:39:07.879221Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a7e65b5-bdb6-4200-9945-122048767bb8 · inbound
A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods cites this paper.
A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods TimeGPT-1
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T22:35:47.227092Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f895679-3aaf-4219-ab19-9378f0abf902 · inbound
Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting cites this paper.
Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting TimeGPT-1
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T17:50:48.858348Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58ac0963-5f92-447f-b3b0-42f96e378818 · inbound
Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting cites this paper.
Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting TimeGPT-1
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T17:48:58.864822Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f568d2c5-df2b-4935-8242-472750f61fce · inbound
Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule cites this paper.
Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule TimeGPT-1
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:17:11.933398Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5921e5e0-ae50-4c9e-b492-c4a4d296430d · inbound
Post-Training in Time Series Foundation Models: A Unifying Framework cites this paper.
Post-Training in Time Series Foundation Models: A Unifying Framework TimeGPT-1
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T11:08:05.342371Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e84f46a4-17e6-4305-aa2a-22924fe17ac6 · inbound
DRP-FLR: Data-Driven Assessment of Demand Response Potential for Flexible Load Regulation in Smart Grids cites this paper.
DRP-FLR: Data-Driven Assessment of Demand Response Potential for Flexible Load Regulation in Smart Grids TimeGPT-1
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T11:51:04.712673Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f89d808e-0416-478d-b99e-6daa157bf9cd · inbound
Contextual Deconvolution for Variance-Stable Demand Sensing: Kernel-Modulated Operators in Promotional Retail cites this paper.
Contextual Deconvolution for Variance-Stable Demand Sensing: Kernel-Modulated Operators in Promotional Retail TimeGPT-1
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T01:54:54.224950Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39a0fd8d-d4f0-4266-89e8-1fa2e6507838 · inbound
RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment cites this paper.
RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment TimeGPT-1
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T12:00:32.380856Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 433ac464-e856-4329-9e4d-5a986bc5e5e9 · inbound
FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting cites this paper.
FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting TimeGPT-1
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:11:57.468156Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.