3 papers
cs.CL2026
Two-dimensional early exit optimisation of LLM inference
Jan Hůla, David Adamczyk, Tomáš Filip +2
We introduce a two-dimensional (2D) early exit strategy that coordinates layer-wise and sentence-wise exiting for classification tasks in large language models. By processing input…
cs.CL2025
BIPOLAR: Polarization-based granular framework for LLM bias evaluation
Martin PavlÃÄek, Tomáš Filip, Petr SosÃk
Large language models (LLMs) are known to exhibit biases in downstream tasks, especially when dealing with sensitive topics such as political discourse, gender identity, ethnic rel…
cs.CL2024
Fine-tuning multilingual language models in Twitter/X sentiment analysis: a study on Eastern-European V4 languages
Tomáš Filip, Martin PavlÃÄek, Petr SosÃk
The aspect-based sentiment analysis (ABSA) is a standard NLP task with numerous approaches and benchmarks, where large language models (LLM) represent the current state-of-the-art.…