ICDM 2026 Workshop on LLM for Tensor Analysis & Tensor for LLM Advancement

Overview

The LLMTenA 2026 workshop is motivated by the untapped synergy between tensor methods and large language models. While tensors offer mathematically grounded tools for dimensionality reduction, multi-modal fusion, and interpretability, LLMs provide powerful semantic understanding and generative capabilities.

We invite original submissions on topics including tensor-based LLM compression, LLM-enhanced tensor analysis, multi-modal fusion, interpretability, and applications across diverse domains such as recommendation systems and spatio-temporal data.

Topics of interest

• Tensor-based compression and acceleration of LLMs
• LLM-enhanced tensor decomposition, denoising, and completion
• Multi-modal data fusion using tensors and LLMs
• Interpretability and explainability of LLMs via tensor methods
• Tensor networks for efficient fine-tuning and prompt engineering
• Knowledge graph embedding and reasoning with tensors and LLMs
• Applications in recommendation systems, neuroscience, spatio-temporal data, and multi-agent systems