collaborators

5 papers

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

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…

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.CL2026

Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377

To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…

cs.LG2026

Adaptive Retrieval helps Reasoning in LLMs -- but mostly if it's not used

Srijan Shakya, Anamaria-Roberta Hartl, Sepp Hochreiter +1

Large Language Models (LLMs) often falter in complex reasoning tasks due to their static, parametric knowledge, leading to hallucinations and poor performance in specialized domain…