3 papers
cs.CL2026
From Layers to Submodules: Rethinking Granularity in Replacement-Based LLM Compression
Elia Cunegatti, Marcus Vukojevic, Erik Nielsen +1
Post-training compression of Large Language Models (LLMs) removes entire architectural components, either deleting them or replacing them with fitted modules. Existing replacement-…
cs.CL2026
Hallucination as an Anomaly: Dynamic Intervention via Probabilistic Circuits
Erik Nielsen, Elia Cunegatti, Marcus Vukojevic +1
One of the most critical challenges in Large Language Models is their tendency to hallucinate, i.e., produce factually incorrect responses. Existing approaches show promising resul…
cs.LG2025
A Benchmark Dataset for Graph Regression with Homogeneous and Multi-Relational Variants
Peter Samoaa, Marcus Vukojevic, Morteza Haghir Chehreghani +1
Graph-level regression underpins many real-world applications, yet public benchmarks remain heavily skewed toward molecular graphs and citation networks. This limited diversity hin…