Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:44:59.060989Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 21 inbound Pith citation observations for arXiv:2502.04395.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:44:59.060989Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:44:14.849109Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T19:56:10.514464Z
39 of 39 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation e0ecf545-b868-4b79-9780-377aa9e32287 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting G., Oreshkin, B
Reference 1
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Observation 51f9a2dd-98f9-406f-92f7-b21d24da0a36 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters
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Observation 628d0b91-8fb1-4091-8816-ac628b3f2767 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
Reference 3
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Observation 86227714-6517-4054-8b72-49bd984e1303 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting E., and Shah, K
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Observation 60127c4d-fcef-4d3b-860e-f77599b2e806 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Unresolved cited work
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Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting M., Alam, M
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Observation 051a0775-6dc6-4846-8d64-ed2a88ac7de8 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Scaling up visual and vision-language representation learning with noisy text supervision
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Observation d2c07c01-be99-447a-9d98-c5252552a991 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Y., Shi, X., Chen, P.-Y., Liang, Y., Li, Y.-F., Pan, S., and Wen, Q
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Observation 47cf497f-1f99-4196-8b03-88b782eff185 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting and Suykens, J
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Observation d1440971-b9a1-4fb2-bdca-730686bbf4a4 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Vilt: Vision-and-language transformer without convolution or region supervision
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Observation f40a41ed-950f-45cc-ac97-1bdfd1bb0c71 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Reformer: The efficient transformer
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Observation 7ba6f2c3-f0c1-487b-b621-1ed4a2c9f184 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Modeling long-and short-term temporal patterns with deep neural networks
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Observation 11db342f-dd61-44cf-8424-4ad65036037f · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
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Observation b58139a2-c71e-4ab6-8ccf-5d5773e54e4f · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting
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Observation be07c52b-c008-4b7b-9789-4d6c0906a478 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Forecasting with time series imaging
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Observation 51a62824-5bd8-408f-ae26-934e6c16fd18 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Foundation models for time series analysis: A tutorial and survey
Reference 16
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Observation ce4dbff1-bb93-4925-b076-f8d6affa9a3f · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Visual Instruction Tuning
Reference 17
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Observation c142d466-9c90-4669-a088-8ed10c086a3f · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
Reference 18
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Observation cacdc08d-8832-4660-927d-aa26b9d4d4dd · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting X., and Dustdar, S
Reference 19
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Observation 98ad3f7c-f590-4c2f-9018-a59493c84cdd · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Unitime: A language-empowered unified model for cross-domain time series forecasting
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Observation 8a4aa038-870c-4d99-b20d-843779722fa0 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Non-stationary transformers: Exploring the stationarity in time series forecasting
Reference 21
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Observation 1147191a-7e61-418a-a95c-acd3f8d39a32 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting The m4 competition: Results, findings, conclusion and way forward
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Observation 308a01bf-d0ff-415b-bb57-462d29843360 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting R., Jain, L., et al
Reference 23
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Observation c64612be-9229-4ca8-ab7f-deb44165c75e · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting H., Sinthong, P., and Kalagnanam, J
Reference 24
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Observation 8420ca8d-f633-4a52-907f-49191b8a33a8 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting N., Carpov, D., Chapados, N., and Bengio, Y
Reference 25
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Observation 5893ad1f-1709-43b5-a042-907063b28b44 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al
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Observation db2a9419-c105-41c1-87d5-dd688bf92887 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Visual time series forecasting: an image-driven approach
Reference 27
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Observation b5577c54-048b-4fb4-bc69-1067e6785a13 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
Reference 28
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Observation d73e9a26-5ff5-414f-9ccb-152f8763ee3b · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
Reference 29
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Observation 3b4af2a4-e92b-467c-b584-915296d2d4e3 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
Reference 30
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Observation 64ffb91c-5dbb-4920-b876-715d4e1767df · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Timesnet: Temporal 2d-variation modeling for general time series analysis
Reference 31
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Observation c884b903-4048-4873-a953-9cbbba06a9fe · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Timesnet: Temporal 2d-variation modeling for general time series analysis
Reference 32
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Observation 7b98579c-7849-403c-a485-7ed05a86e7a3 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Are transformers effective for time series forecasting? In Proceedings of the AAAI conference on artificial intelligence, volume 37, pp.\ 11121--11128, 2023
Reference 33
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Observation 7547b97e-4391-428d-abf0-d288dc5cf82f · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
Reference 34
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Observation ab0c8d1c-d6e6-4f21-af9e-ea96edc056bc · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting and Huang, M
Reference 35
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Observation 058ff896-444b-4a61-9cb3-25ac83a5fd35 · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting
Reference 36
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Observation 1cf8a2a9-1851-487a-9a96-465ce0c98d7a · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting
Reference 37
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Observation 68b89883-75b6-4a0e-8b02-53982db37e7b · outbound
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting One fits all: Power general time series analysis by pretrained lm
Reference 38
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Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting write newline
Reference 39
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From Images to Signals: Are Large Vision Models Useful for Time Series Analysis? Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation ad1b41af-61d1-4385-8a96-a8b5c65eb412 · inbound
From Time Series Analysis to Question Answering: A Survey in the LLM Era Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation ac147497-18ee-4ddc-9581-83e7aa0bd14e · inbound
Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation 4551f998-3eef-4208-ac2a-c1fa5d897850 · inbound
Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Reference 233
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Observation 0d9b4a7a-f47a-4fa7-bb86-feef2bb99b15 · inbound
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Observation 64262374-5624-4138-ab36-ae256c787937 · inbound
Watermarking Large Language Model-based Time Series Forecasting Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Reference 2025
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Observation 708f493d-fa75-4949-879b-c5ed5b98eb1a · inbound
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Observation f9924f67-23dd-40f4-9cfe-8fa41850b3dc · inbound
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Observation ee286e24-a9fc-43e8-9fb3-fed7e492552f · inbound
TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gathering Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation 241f4525-e6bf-4da0-a90c-52dd35754ea0 · inbound
Overcoming the Modality Gap in Context-Aided Forecasting Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Overcoming the Modality Gap in Context-Aided Forecasting Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation 8e1f06a5-3fd4-473b-af86-27ea7c9bdbf6 · inbound
Discrete Prototypical Memories for Federated Time Series Foundation Models Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation 343966be-8b87-495c-a4ff-426d8989ccfe · inbound
Empowering VLMs for Few-Shot Multimodal Time Series Classification via Tailored Agentic Reasoning Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Reference 64
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Observation 2ef25e4e-0cfb-486b-badc-a05ba4486863 · inbound
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Observation 1d140e72-5d1a-4e0f-bd63-a8064a95bd69 · inbound
MULTISEISMO: A Multimodal Seismic Dataset and Model for Cross-Modal Seismic Understanding Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation b1ef0f6f-54ab-47c2-b895-b650df1c44c2 · inbound
VESTA: Visual Exploration with Statistical Tool Agents Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
Reference 59
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Observation 0ada7a79-3d65-4229-98a3-f5b4ce2f0518 · inbound
TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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Observation f00a7f7a-cd43-4b67-9ff7-14a765116739 · inbound
TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
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