Paper Citation Record · LEDGER

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 3 inbound Pith citation observations for arXiv:2505.10774.

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

pith.paper-citation-record.v1
2505.10774 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:08:10.555424Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:49:34.926858Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

52 of 52 outbound references displayed

verified exact0
verified fuzzy34
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2d680327-4bdb-43c2-9027-be9105028a1d · outbound

This paper cites Tiny Time Mixers (TTMs): Fast pre-trained 9 models for enhanced zero/few-shot forecasting of multivariate time series.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Tiny Time Mixers (TTMs): Fast pre-trained 9 models for enhanced zero/few-shot forecasting of multivariate time series

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.172954Z

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 bd09d8fb-bf35-4568-b686-bf810e0fbfd9 · outbound

This paper cites MOMENT: A family of open time-series foundation models.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting MOMENT: A family of open time-series foundation models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.375496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe8ff4e0-ff79-4575-8ee6-dcf6c5e402c3 · outbound

This paper cites Time series analysis: Forecasting and control.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Time series analysis: Forecasting and control

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.156243Z

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 d6b9c977-b482-445a-9164-df8753ce37d5 · outbound

This paper cites Time series prediction using support vector machines: A survey.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Time series prediction using support vector machines: A survey

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.146350Z

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 d2541693-a80a-40f8-aef9-1f6ffd6ee4c7 · outbound

This paper cites Long short-term memory.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Long short-term memory

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.136701Z

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 b06b1f08-f32a-4b15-92fd-737c96e560b5 · outbound

This paper cites A dual-stage attention-based recurrent neural network for time series prediction.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting A dual-stage attention-based recurrent neural network for time series prediction

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.125682Z

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 be686c7d-037d-42cf-9180-c59839f43bc3 · outbound

This paper cites Modeling long-and short-term temporal patterns with deep neural networks.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Modeling long-and short-term temporal patterns with deep neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.114737Z

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 689bfdae-f7df-45aa-9943-fc05c2e32ee5 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.397319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aca7b0bf-68a8-4ab1-8de8-3d57f174331a · outbound

This paper cites TimesNet: Temporal 2d-variation modeling for general time series analysis.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting TimesNet: Temporal 2d-variation modeling for general time series analysis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.102232Z

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 a97532f5-9984-41dc-9978-4ca9d0489c42 · outbound

This paper cites ModernTCN: A modern pure convolution structure for general time series analysis.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting ModernTCN: A modern pure convolution structure for general time series analysis

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.089978Z

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 41ca271d-caf7-4d65-920d-bb1a24ebe42c · outbound

This paper cites Transformers in time series: A survey.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Transformers in time series: A survey

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.079109Z

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 c78efc86-00eb-4cb6-ac69-9d8b2aa7b84c · outbound

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

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.413229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 334bdb65-baf3-477c-b2c2-ecf3082b9270 · outbound

This paper cites Autoformer: Decomposition trans- formers with auto-correlation for long-term series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Autoformer: Decomposition trans- formers with auto-correlation for long-term series forecasting

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.416517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7b03edf-2165-48bc-b2e1-ecee88b72745 · outbound

This paper cites FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.058021Z

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 59c91b6a-d8b9-41af-bfbd-c225d30caff0 · outbound

This paper cites Non-stationary Transformers: Exploring the stationarity in time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Non-stationary Transformers: Exploring the stationarity in time series forecasting

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.048352Z

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 d7cea039-72f1-4317-9f27-ce308f6acafc · outbound

This paper cites NHITS: Neural hierarchical interpolation for time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting NHITS: Neural hierarchical interpolation for time series forecasting

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.038908Z

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 f8e16b48-7c26-415a-a3fb-72978d0cf7d3 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.431855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 127e35e6-a990-4400-9583-7ef8cf7bcb17 · outbound

This paper cites iTransformer: Inverted transformers are effective for time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting iTransformer: Inverted transformers are effective for time series forecasting

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.029591Z

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 4ba38c5c-eb79-4858-aa33-f4fcd6d8fe89 · outbound

This paper cites Are transformers effective for time series forecasting? In Proceedings of the AAAI Conference on Artificial Intelligence , volume 37, pages 11121–11128, 2023.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Are transformers effective for time series forecasting? In Proceedings of the AAAI Conference on Artificial Intelligence , volume 37, pages 11121–11128, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.019756Z

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 7ff9db93-3d98-4ae8-b4a5-a338316c3b83 · outbound

This paper cites N-beats: Neural basis expansion analysis for interpretable time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting N-beats: Neural basis expansion analysis for interpretable time series forecasting

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.443455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fad852ee-4867-438f-8cd7-3182e1828bdf · outbound

This paper cites Large language models are zero-shot time series forecasters.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Large language models are zero-shot time series forecasters

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:11.003476Z

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 cfea0c0b-41ca-4a2b-a3e3-0a715dc0a459 · outbound

This paper cites One Fits All: Power general time series analysis by pretrained lm.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting One Fits All: Power general time series analysis by pretrained lm

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.993647Z

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 637c79be-42f9-4022-bfe7-743e00cbbdfd · outbound

This paper cites PromptCast: A new prompt-based learning paradigm for time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting PromptCast: A new prompt-based learning paradigm for time series forecasting

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.984621Z

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 b128d373-b2c9-4441-b10b-f94032633076 · outbound

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

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting TEMPO: Prompt-based generative pre-trained transformer for time series forecasting

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.975000Z

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 82db23e3-18df-483b-acb8-28964cc7ddf3 · outbound

This paper cites Time-LLM: Time series forecasting by reprogramming large language models.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Time-LLM: Time series forecasting by reprogramming large language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.965456Z

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 16d68416-7949-48bf-bae5-7404e80748da · outbound

This paper cites UniTime: A language-empowered unified model for cross-domain time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting UniTime: A language-empowered unified model for cross-domain time series forecasting

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.956246Z

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 a5a7ff04-0894-4a03-b93f-7c816764eabd · outbound

This paper cites TEST: Text prototype aligned embedding to activate llm’s ability for time series.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting TEST: Text prototype aligned embedding to activate llm’s ability for time series

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.946071Z

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 eef025e2-e67c-4927-872c-d33edb0be305 · outbound

This paper cites S2IP-LLM: Semantic space informed prompt learning with llm for time series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting S2IP-LLM: Semantic space informed prompt learning with llm for time series forecasting

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.936240Z

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 ff8cf738-949b-4cde-8402-7c44b1e71b21 · outbound

This paper cites AutoTimes: Au- toregressive time series forecasters via large language models.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting AutoTimes: Au- toregressive time series forecasters via large language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.926590Z

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 4f6c9f0a-5f8e-47e9-8e08-137101def410 · outbound

This paper cites CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.478636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f56aafc-a51d-4943-b6c1-98fe5c4ef736 · outbound

This paper cites TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.482662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9688aa0-2385-4755-8bae-efd1aca6e95d · outbound

This paper cites Context-Alignment: Activating and enhancing llm capabilities in time series.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Context-Alignment: Activating and enhancing llm capabilities in time series

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.486133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9264d6d-a3be-4e1f-95b7-94cd94b85319 · outbound

This paper cites FNSPID: A comprehensive financial news dataset in time series.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting FNSPID: A comprehensive financial news dataset in time series

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.916725Z

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 1794e2a6-f9c6-49b8-bd6e-c8ba3f140163 · outbound

This paper cites Stock movement prediction from tweets and historical prices.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Stock movement prediction from tweets and historical prices

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.907071Z

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 5c881abe-36e2-469c-9687-29d3ef3dd275 · outbound

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

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting From News to Forecast: Integrating event analysis in llm-based time series forecasting with reflection

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.896131Z

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 fd6b7322-88a9-49e7-9ddb-086aa5af8599 · outbound

This paper cites Time-MMD: Multi-domain multimodal dataset for time series analysis.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Time-MMD: Multi-domain multimodal dataset for time series analysis

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.884284Z

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 18a23964-275b-4e23-9960-f69422f7870f · outbound

This paper cites TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.502845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50519d01-1b96-43b5-8f0c-5e3d88f9a37a · outbound

This paper cites Explainable multi-modal time series prediction with llm-in-the-loop.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Explainable multi-modal time series prediction with llm-in-the-loop

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.506347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db25436e-959f-41e0-8203-616254643fb4 · outbound

This paper cites The m4 competition: 100,000 time series and 61 forecasting methods.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting The m4 competition: 100,000 time series and 61 forecasting methods

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.872579Z

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 1f7cde09-6dab-477e-86a2-c08dad24f871 · outbound

This paper cites Are forecasting competitions data representative of the reality? International Journal of Forecasting, 36(1):37–53, 2020.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Are forecasting competitions data representative of the reality? International Journal of Forecasting, 36(1):37–53, 2020

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.861721Z

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 831250cc-eefe-458b-bf64-3bd11d62e4d7 · outbound

This paper cites Traffic flow prediction with big data: A deep learning approach.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Traffic flow prediction with big data: A deep learning approach

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.852338Z

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 d272ff57-26be-49f1-8a50-6bb8f93d3d6b · outbound

This paper cites Gpt4mts: Prompt-based large language model for multimodal time-series forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Gpt4mts: Prompt-based large language model for multimodal time-series forecasting

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.520287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 156298a2-2656-4d01-862d-1c184a5ea3bb · outbound

This paper cites Combining time-series and textual data for taxi demand prediction in event areas: A deep learning approach.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Combining time-series and textual data for taxi demand prediction in event areas: A deep learning approach

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.837130Z

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 6248fe43-3290-4584-b359-52701de813cb · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting On the Opportunities and Risks of Foundation Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.527368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fc20edd-d855-45e2-8514-d5fd9ea15e9d · outbound

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

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting A decoder-only foundation model for time-series forecasting

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.826247Z

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 d3e6769d-271e-45ac-8bc4-c4e2ffb5b214 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting LLaMA: Open and Efficient Foundation Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.534510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c6491bc-2f6c-46c7-a323-75258836c4c1 · outbound

This paper cites Qwen2.5 Technical Report.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Qwen2.5 Technical Report

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.537750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e550eed-f67f-4e5b-96fb-07aa153d6a12 · outbound

This paper cites Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.541015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d70d96e2-29ca-449b-821b-96933ef97ddf · outbound

This paper cites Language models are unsupervised multitask learners.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Language models are unsupervised multitask learners

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.814973Z

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 9b1e991c-a587-48c0-be11-6868268ee7c7 · outbound

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

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Learning transferable visual models from natural language supervision

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.548101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd98d1e1-bc50-45ed-8c42-53260b8da981 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T21:08:10.551619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54616f51-e980-4348-9f53-4f56216a27a3 · outbound

This paper cites Are language models actually useful for time series forecasting? Advances in Neural Information Processing Systems, 37:60162–60191, 2024.

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting Are language models actually useful for time series forecasting? Advances in Neural Information Processing Systems, 37:60162–60191, 2024

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:08:10.793275Z

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.

Pith citing papers

Observation 0bb3e977-8de9-445f-a9d8-39cbf41156e6 · 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 Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting

Reference 132

Resolution: unresolved; no resolver link, observed 2026-08-04T16:49:34.926858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63a428a2-e941-45e5-8826-128d31fb81a3 · inbound

GRAFT: Grid-Aware Load Forecasting with Multi-Source Textual Alignment and Fusion cites this paper.

GRAFT: Grid-Aware Load Forecasting with Multi-Source Textual Alignment and Fusion Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:48:34.253218Z

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 7e85b331-508d-4020-93ad-e308dff6df63 · inbound

Rethinking Multimodal Fusion for Time Series: Text Modalities Need Constrained Fusion cites this paper.

Rethinking Multimodal Fusion for Time Series: Text Modalities Need Constrained Fusion Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T17:44:46.616740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.