Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting | Paper Citation Record

Observation 0930ca92-79d3-4028-b090-5c2760d2398f · outbound

This paper cites write newline.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:51.666160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e2c19ad-d784-4629-99c6-829098346d20 · outbound

This paper cites https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:51.746633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8239cb3-a359-4ace-8560-0558a502546e · outbound

This paper cites http://pems.dot.ca.gov/.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting http://pems.dot.ca.gov/

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:51.857976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c9f0238-3f60-4f6a-b435-e25bc19ab9dd · outbound

This paper cites an unresolved cited work.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:51.983687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb588c05-bab8-4a9c-a546-8e70567c0b73 · outbound

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

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Chronos: Learning the Language of Time Series

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.096683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d79f9966-922b-409d-bbf1-11f2f0b70a18 · outbound

This paper cites Pagerank bandits for link prediction.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Pagerank bandits for link prediction

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.214568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f3219ed-58fe-4d4d-b787-cd8727f599c4 · outbound

This paper cites Adaptive test-time personalization for federated learning.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Adaptive test-time personalization for federated learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.344571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8323e714-cdee-4e02-acf3-8fcff08d6151 · outbound

This paper cites Matcha: Mitigating graph structure shifts with test-time adaptation.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Matcha: Mitigating graph structure shifts with test-time adaptation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.488218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dded35a-65b0-4129-8119-af79814bdbce · outbound

This paper cites Tsfel: Time series feature extraction library.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Tsfel: Time series feature extraction library

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.613953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56823352-d84d-4fc3-b370-d9fe14683e76 · outbound

This paper cites Ensemble selection from libraries of models.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Ensemble selection from libraries of models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.686421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75c9ae8d-2338-4cc6-b0f3-a9f06cf1c8dd · outbound

This paper cites F., Skabardonis, A., Varaiya, P.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting F., Skabardonis, A., Varaiya, P

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.746920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a5d4e9-1abe-414a-9048-114378a8af79 · outbound

This paper cites an unresolved cited work.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.838468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 416499c8-0a2c-43fb-9afe-f254fed8a4af · outbound

This paper cites E., and Shah, K.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting E., and Shah, K

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.910260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6250c27b-ddf4-46c3-af17-823533db6093 · outbound

This paper cites I., and Chen, H.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting I., and Chen, H

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:52.996609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2294ebbf-a97c-412e-b65a-55f08d921007 · outbound

This paper cites Adversarial graph contrastive learning with information regularization.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Adversarial graph contrastive learning with information regularization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.069831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5806a533-a9f9-49dc-9142-3e4ad95c078f · outbound

This paper cites Auto-sklearn 2.0: Hands-free automl via meta-learning.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Auto-sklearn 2.0: Hands-free automl via meta-learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.140264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca8f8631-609c-403e-8011-7c7af6af2c04 · outbound

This paper cites Unsupervised scalable representation learning for multivariate time series.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Unsupervised scalable representation learning for multivariate time series

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.194937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afeed74f-df4d-4c2f-8bce-bcb5dc06d201 · outbound

This paper cites I., and He, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting I., and He, J

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.249071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5cd14c6-1248-4cc9-a5d0-3b9309825ab2 · outbound

This paper cites What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.311294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e843afee-fca7-4a5b-ad65-a77937e40900 · outbound

This paper cites Vcr-graphormer: A mini-batch graph transformer via virtual connections.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Vcr-graphormer: A mini-batch graph transformer via virtual connections

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.382492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caed0d50-447c-4a06-ab01-3bd1b5dc65c1 · outbound

This paper cites Generating fine-grained causality in climate time series data for forecasting and anomaly detection.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Generating fine-grained causality in climate time series data for forecasting and anomaly detection

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.464114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 969d6391-6eb5-4711-aad0-c7ac05c50d73 · outbound

This paper cites ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:35:00.727792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c5fbbd3d-fd9f-4897-ba6f-55108479c7be · outbound

This paper cites On the sensitivity of individual fairness: Measures and robust algorithms.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting On the sensitivity of individual fairness: Measures and robust algorithms

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.612997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e752d83e-565b-44de-856a-4f4376912195 · outbound

This paper cites Temporal heterogeneous graph generation with privacy, utility, and efficiency.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Temporal heterogeneous graph generation with privacy, utility, and efficiency

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.739734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b5f879b-150d-4fae-8fda-a23b4dc77548 · outbound

This paper cites and Fulcher, B.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and Fulcher, B

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.833856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec0e9bed-f664-49ed-9967-1f34599c7d05 · outbound

This paper cites an unresolved cited work.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Unresolved cited work

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:53.906777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f6e27e8-1b04-4873-b8ad-27a824db647e · outbound

This paper cites A review on time series aggregation methods for energy system models.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting A review on time series aggregation methods for energy system models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.001445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 120543ef-677a-4af3-8373-f231c1c11261 · outbound

This paper cites an unresolved cited work.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.081921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac17dc86-eb4a-4837-b457-5858b4ee035b · outbound

This paper cites Network of tensor time series.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Network of tensor time series

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.150664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8637fe00-7c9b-4df8-8ec0-9cab61f2afd6 · outbound

This paper cites Retrieval Based Time Series Forecasting.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Retrieval Based Time Series Forecasting

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.230890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d08e6daf-8272-48db-a26f-ef4914f060e9 · outbound

This paper cites Towards editing time series.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Towards editing time series

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.305305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f0691c8-3e2b-4f18-a748-1ad9a95ac56f · outbound

This paper cites Automated contrastive learning strategy search for time series.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Automated contrastive learning strategy search for time series

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.380798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f9d5d12-b1ad-4bc8-a195-80b43a5da918 · outbound

This paper cites Causality-aware spatiotemporal graph neural networks for spatiotemporal time series imputation.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Causality-aware spatiotemporal graph neural networks for spatiotemporal time series imputation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.498801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10661305-229c-4eba-aa94-10508951ebd0 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Adam: A Method for Stochastic Optimization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.579318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 350f1450-bfbd-487d-b19f-a12d06a22b0b · outbound

This paper cites K., and Crone, S.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting K., and Crone, S

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.663343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ef29c85-972e-4257-8dfb-7d4d9aa83e9c · outbound

This paper cites Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.754753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42f28bd6-b187-421d-bcdb-b1885ebb609d · outbound

This paper cites Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:54.885974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf2dd809-afe2-4312-b7be-50020c89dc94 · outbound

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

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Modeling long-and short-term temporal patterns with deep neural networks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:55.014201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed23b5b2-4435-447b-a1c1-694082af9beb · outbound

This paper cites Trend modeling for traffic time series analysis: An integrated study.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Trend modeling for traffic time series analysis: An integrated study

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.288612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8c077b12-9599-4d5b-8b74-7a91ea1747f9 · outbound

This paper cites Everything evolves in personalized pagerank.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Everything evolves in personalized pagerank

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:55.185345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92f872c1-8de2-42c2-8642-91c1e0c3a574 · outbound

This paper cites F., Tong, H., and He, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting F., Tong, H., and He, J

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:55.254725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6a36a63-00cd-4c52-85ad-99b85d49c0bf · outbound

This paper cites and Zohren, S.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and Zohren, S

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.273460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bf23ab5d-d325-4c4f-8d12-2d27b60fed51 · outbound

This paper cites Backtime: Backdoor attacks on multivariate time series forecasting.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Backtime: Backdoor attacks on multivariate time series forecasting

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.258169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36d01a84-2bed-413b-beb5-2bf416e15f62 · outbound

This paper cites CATS: Mitigating Correlation Shift for Multivariate Time Series Classification.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting CATS: Mitigating Correlation Shift for Multivariate Time Series Classification

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:55.554920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 572c58f8-6b22-47f7-8f1a-73a347c0507f · outbound

This paper cites Non-stationary transformers: Rethinking the stationarity in time series forecasting.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Non-stationary transformers: Rethinking the stationarity in time series forecasting

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.243757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e770661-59e9-4593-b24f-457e9845e050 · outbound

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

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting itransformer: Inverted transformers are effective for time series forecasting

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.228973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e15a721-776d-4312-ab3d-08df31542ff8 · outbound

This paper cites Self-paced ensemble for highly imbalanced massive data classification.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Self-paced ensemble for highly imbalanced massive data classification

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.213845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38c7c41b-da36-4055-998e-8c1a577b47c9 · outbound

This paper cites Mesa: boost ensemble imbalanced learning with meta-sampler.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Mesa: boost ensemble imbalanced learning with meta-sampler

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.197557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2bb25a04-7ab7-422c-ae4b-1bf9ec13c588 · outbound

This paper cites IMBENS: Ensemble Class-imbalanced Learning in Python.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting IMBENS: Ensemble Class-imbalanced Learning in Python

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:35:01.134475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0f0a9644-10b0-4e10-8ad5-86fa641215a9 · outbound

This paper cites Class-imbalanced graph learning without class rebalancing.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Class-imbalanced graph learning without class rebalancing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.181679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b96c2761-6b22-475c-ac83-f66217fab1c7 · outbound

This paper cites an unresolved cited work.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:35:02.165640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6f289194-d1cc-4e7e-a9a2-f4159336abd1 · outbound

This paper cites H., Sinthong, P., and Kalagnanam, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting H., Sinthong, P., and Kalagnanam, J

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.147739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d4ecdea8-a234-4aea-aad6-28ac307b63f0 · outbound

This paper cites and Torgo, L.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and Torgo, L

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.131909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 26ac9655-2adc-4582-81e9-5c5c842eeb92 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Pytorch: An imperative style, high-performance deep learning library

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:56.459571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 717ec46f-a15a-43df-9ddb-7b92535bee8f · outbound

This paper cites and Tong, H.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and Tong, H

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.103594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7eddfc3e-276b-420c-8ba8-3b879d330df6 · outbound

This paper cites DIMES : A differentiable meta solver for combinatorial optimization problems.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting DIMES : A differentiable meta solver for combinatorial optimization problems

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.087278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6f84ef54-6c73-4d15-97c2-c4d883f64aad · outbound

This paper cites V., Zhang, Y., and Tong, H.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting V., Zhang, Y., and Tong, H

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.070131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af09cccc-520b-4b9e-83bd-d6a04a867ddd · outbound

This paper cites TUCKET : A tensor time series data structure for efficient and accurate factor analysis over time ranges.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting TUCKET : A tensor time series data structure for efficient and accurate factor analysis over time ranges

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.051306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d176c374-f21f-4450-bdc3-6dcb82700342 · outbound

This paper cites Ask, and it shall be given: On the Turing completeness of prompting.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Ask, and it shall be given: On the Turing completeness of prompting

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:56.878812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30d9c9c0-b689-4a93-92d7-6778f68f5276 · outbound

This paper cites How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:56.978627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6fb91c3-3281-45df-bec0-779770c0e917 · outbound

This paper cites Canon: Complex analytics of network of networks for modeling adversarial activities.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Canon: Complex analytics of network of networks for modeling adversarial activities

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.030813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 54e69b4f-bd3a-44d3-9b56-edfd8d9d0438 · outbound

This paper cites and Rokach, L.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and Rokach, L

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:02.013738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 85c4a863-a246-49ee-a7c9-34fde1da6831 · outbound

This paper cites B., Gudelek, M.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting B., Gudelek, M

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.996655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3a66e1ca-75ae-4e0e-aeb9-ee4def117b2a · outbound

This paper cites C., Erickson, N., Shen, H., Shirkov, A., Hu, T., and Wang, B.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting C., Erickson, N., Shen, H., Shirkov, A., Hu, T., and Wang, B

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.980387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4a332657-16a7-4133-be86-23cae781379c · outbound

This paper cites A., Gupta, V., Althoff, T., and Hartvigsen, T.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting A., Gupta, V., Althoff, T., and Hartvigsen, T

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.960232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4a190e0-6e46-4d9d-95e8-8573f8eb295d · outbound

This paper cites F., and He, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting F., and He, J

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:57.467944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e53594c-6a19-4423-b4d8-42d58cbdbda8 · outbound

This paper cites Invariant link selector for spatial-temporal out-of-distribution problem.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Invariant link selector for spatial-temporal out-of-distribution problem

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:57.541677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a74b3981-5373-4682-a5aa-e180b5d41660 · outbound

This paper cites Networked time series imputation via position-aware graph enhanced variational autoencoders.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Networked time series imputation via position-aware graph enhanced variational autoencoders

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.912198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c0350d8c-80b9-4cef-8e58-bbae253492fb · outbound

This paper cites Learning graph quantized tokenizers.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Learning graph quantized tokenizers

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:57.683162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0d6168a-32db-4010-a837-396bf38b325c · outbound

This paper cites Y., and ZHOU, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Y., and ZHOU, J

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.876472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f6dee87f-e432-4974-b2d5-65e75692e792 · outbound

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

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Deep Time Series Models: A Comprehensive Survey and Benchmark

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:57.943371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb829cbb-79c1-4af6-9eb4-27d6e8f30c66 · outbound

This paper cites TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:58.082771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00685dd8-5cca-4563-ba6c-9bed286d1207 · outbound

This paper cites and He, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and He, J

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.859445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1145416a-32f5-4eb9-9fdd-54e8c260fe28 · outbound

This paper cites Fast adaptation for cold-start collaborative filtering with meta-learning.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Fast adaptation for cold-start collaborative filtering with meta-learning

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.841037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0aa419d5-92ba-4ca5-807b-fba1ac5ab93f · outbound

This paper cites Model-agnostic counterfactual reasoning for eliminating popularity bias in recommender system.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Model-agnostic counterfactual reasoning for eliminating popularity bias in recommender system

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.821732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 33269198-a2fd-4f4f-9a9f-32069c05a4cf · outbound

This paper cites Augmentations in hypergraph contrastive learning: Fabricated and generative.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Augmentations in hypergraph contrastive learning: Fabricated and generative

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.804215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2367c1d8-09ca-4ca4-a527-d2b42298960a · outbound

This paper cites Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:58.848362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83afccc1-ebec-4735-8414-570cddbf4829 · outbound

This paper cites Robust watermarking for diffusion models: A unified multi-dimensional recipe, 2024 b.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Robust watermarking for diffusion models: A unified multi-dimensional recipe, 2024 b

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.785797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7c68ff39-fec8-40d0-9c73-1af1f5b8e59c · outbound

This paper cites Connecting domains and contrasting samples: A ladder for domain generalization.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Connecting domains and contrasting samples: A ladder for domain generalization

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:59.145811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd7f728b-178c-4bdb-8d53-b4179ccc1127 · outbound

This paper cites Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.767267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation be6d715f-12a6-4061-b23a-1cbbd4c59d67 · outbound

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

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting TimesNet : Temporal 2d-variation modeling for general time series analysis

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.749419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f078309e-e3d3-4230-bb85-47a3adee5e64 · outbound

This paper cites Fair Anomaly Detection For Imbalanced Groups.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Fair Anomaly Detection For Imbalanced Groups

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:59.569457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbd6a769-d2a1-465e-b8f1-b9e5650a7e6b · outbound

This paper cites F., Han, J., and Tong, H.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting F., Han, J., and Tong, H

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.730769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 63b023a5-cc58-4366-a92b-799603ee776b · outbound

This paper cites Language models are graph learners.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Language models are graph learners

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.711629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f8fc758-a59c-488a-a6b0-8fe8c0bbfafd · outbound

This paper cites Discrete-state Continuous-time Diffusion for Graph Generation.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Discrete-state Continuous-time Diffusion for Graph Generation

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:59.864044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da5114aa-e42b-48a7-80a6-06aaba809436 · outbound

This paper cites Dynamic knowledge graph alignment.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Dynamic knowledge graph alignment

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.696414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cc895313-ea16-4c36-9bc4-36cd3b0852c2 · outbound

This paper cites Bright: A bridging algorithm for network alignment.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Bright: A bridging algorithm for network alignment

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.681118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e35d4990-e3a2-4fb0-ad97-f5f9efcd78d9 · outbound

This paper cites Dissecting cross-layer dependency inference on multi-layered inter-dependent networks.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Dissecting cross-layer dependency inference on multi-layered inter-dependent networks

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.662738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3e0fbb48-592b-4cd8-8e0d-c4f5d3f4ec1c · outbound

This paper cites From trainable negative depth to edge heterophily in graphs.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting From trainable negative depth to edge heterophily in graphs

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.645928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b9ab6e76-43e4-438f-97bb-8ebfcbe53131 · outbound

This paper cites Reconciling competing sampling strategies of network embedding.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Reconciling competing sampling strategies of network embedding

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.628400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b832d4ac-f511-4c7e-babe-82d3ffe72cda · outbound

This paper cites THeGCN: Temporal Heterophilic Graph Convolutional Network.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting THeGCN: Temporal Heterophilic Graph Convolutional Network

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-07T14:35:00.361040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d4e19c9-b1d4-4cce-9093-4bbb3825a990 · outbound

This paper cites Pacer: Network embedding from positional to structural.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Pacer: Network embedding from positional to structural

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.612470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 286be7ab-1848-41ed-94c1-2bac6449e83c · outbound

This paper cites Topological anonymous walk embedding: A new structural node embedding approach.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Topological anonymous walk embedding: A new structural node embedding approach

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.596671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d242a725-ff43-473e-b5b5-6d2710e7c676 · outbound

This paper cites M., Bian, J., Chang, Y., Lurie, J.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting M., Bian, J., Chang, Y., Lurie, J

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.574062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 638d6e93-280b-43b6-9335-e0c9b689a39a · outbound

This paper cites Frequency-domain mlps are more effective learners in time series forecasting.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Frequency-domain mlps are more effective learners in time series forecasting

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.555903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 35e1f815-38a2-4297-b760-5571f9cf29a3 · outbound

This paper cites Ensuring user-side fairness in dynamic recommender systems.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Ensuring user-side fairness in dynamic recommender systems

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.537805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca327829-9870-4cfe-b441-93c23df536f5 · outbound

This paper cites Embracing plasticity: Balancing stability and plasticity in continual recommender systems.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Embracing plasticity: Balancing stability and plasticity in continual recommender systems

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.520913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c798d20c-5fec-4b08-9d41-c85f66d29585 · outbound

This paper cites Generalizable recommender system during temporal popularity distribution shifts.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Generalizable recommender system during temporal popularity distribution shifts

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.506169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e3f4f3d7-2383-4343-b661-28a503051b47 · outbound

This paper cites Ensemble forecasting for complex time series using sparse representation and neural networks.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting Ensemble forecasting for complex time series using sparse representation and neural networks

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.489476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5c60496a-6e0d-462a-9460-64c436373c68 · outbound

This paper cites and Li, G.

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting and Li, G

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:01.474452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers