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cs.LG2026

KVpop -- Key-Value Cache Compression with Predictive Online Pruning

Lukas Hauzenberger, Niklas Schmidinger, Anamaria-Roberta Hartl +5

Key-value (KV) cache growth is a major bottleneck in autoregressive decoding, as memory and bandwidth scale linearly with context length. Existing KV eviction methods often rely on…

cs.LG2026

TiRex-2: Generalizing TiRex to Multivariate Data and Streaming

Patrick Podest, Marco Pichler, Elias Bürger +7

We introduce TiRex-2, a recurrent xLSTM-based time series foundation model that generalizes the univariate TiRex to multivariate forecasting with both past and future covariates. R…

cs.LG2026

On Subquadratic Architectures: From Applications to Principles

Anamaria-Roberta Hartl, Levente Zólyomi, David Stap +6

Transformers dominate modern sequence modeling, but their quadratic attention incurs substantial computational cost. Subquadratic architectures offer a scalable alternative. Howeve…

cs.LG2026

Symbol-Equivariant Recurrent Reasoning Models

Richard Freinschlag, Timo Bertram, Erich Kobler +2

Reasoning problems such as Sudoku and ARC-AGI remain challenging for neural networks. The structured problem solving architecture family of Recurrent Reasoning Models (RRMs), inclu…

cs.LG2026

Effective Distillation to Hybrid xLSTM Architectures

Lukas Hauzenberger, Niklas Schmidinger, Thomas Schmied +7

There have been numerous attempts to distill quadratic attention-based large language models (LLMs) into sub-quadratic linearized architectures. However, despite extensive research…