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LLMs adapted for time-series forecasting using parameter-efficient methods · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers are exploring parameter-efficient methods to adapt large language models (LLMs) for time-series forecasting tasks. One study projects time-series data directly into the embedding space of a GPT-2 model, achieving competitive accuracy while updating less than 1% of parameters. Another paper introduces a "competence gate" that selectively integrates LLM forecasts by estimating their marginal value over existing predictions, improving accuracy on average but deferring to strong market forecasts. AI

IMPACT New techniques could improve the accuracy and efficiency of AI-driven forecasting across various domains.

RANK_REASON Two research papers exploring novel methods for applying language models to time-series forecasting.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLMs adapted for time-series forecasting using parameter-efficient methods · 2 sources tracked

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Two research papers exploring novel methods for applying language models to time-series forecasting.
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2 independent sources
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paper, model release
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High
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16 days old
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Tamanna Kumavat, Georg Brunner, Kyriakos Flouris ·

    Parameter-Efficient Adaptation of Pretrained Language Models for Time-Series Forecasting

    arXiv:2609.15344v1 Announce Type: new Abstract: We study the adaptation of pretrained language models to univariate time-series forecasting through a parameter-efficient transfer learning framework, with the goal of understanding which design choices drive effective cross-modal t…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Competence-Gated Pooling of Language Models and Priors for Event Forecasting

    A competence gate selectively integrates language model forecasts by estimating domain-level marginal value over external predictions, improving hybrid forecasting accuracy.

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