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SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting research paper by Google, 2026

Google · Applied AI · Oct 2, 2026 · 0 citations · 35 upvotes · unverified

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What it shows

SEER improves time series forecasting by using a closed-loop system to retrieve and reason about external events that influence data trends.

By Mingtian Tan, Palash Goyal, Mihir Parmar and 6 more · arXiv 2610.04109 · PDF · Code

UnverifiedSummarised by a model from the abstract; not yet checked by hand.

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About this paper
Citations
0, 0 influential · Semantic Scholar
Upvotes
35 · Hugging Face
Lab
Google · on Companies · on Acquisitions · on Paydays · on TechConf · on Releases

Changes

CitationsNov 9, 2026A first count of 0 influential citations.
CitationsNov 9, 2026A first count of 0 citations.
New summaryOct 26, 2026SEER improves time series forecasting by using a closed-loop system to retrieve and reason about external events that influence data trends.
TopicOct 26, 2026Moved from Reasoning to Applied AI.
New paperOct 12, 2026Found by the weekly Hugging Face scan; not yet checked by hand.