activity
20242026
collaborators

5 papers

cs.LG2026

Decoding Naturalistic Emotion Dynamics from the Brain: An LLM-Enhanced Regression Framework

Lemei Zhang, Peng Liu, Hans Dahle Kvadsheim +5

Decoding emotional states from neural signals has been typically framed as a discrete, single-label classification task based on emotionally stable stimuli, a formulation that over…

cs.CL2026

NorwAI's Large Language Models: Technical Report

Jon Atle Gulla, Peng Liu, Lemei Zhang

Norwegian, spoken by approximately five million people, remains underrepresented in many of the most significant breakthroughs in Natural Language Processing (NLP). To address this…

cs.CL2025

The Impact of Copyrighted Material on Large Language Models: A Norwegian Perspective

Javier de la Rosa, Vladislav Mikhailov, Lemei Zhang +16

The use of copyrighted materials in training language models raises critical legal and ethical questions. This paper presents a framework for and the results of empirically assessi…

cs.CL2024

PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models

Lemei Zhang, Peng Liu, Marcus Tiedemann Oekland Henriksboe +3

With the rapid advancement of Natural Language Processing in recent years, numerous studies have shown that generic summaries generated by Large Language Models (LLMs) can sometime…

cs.CL2024

NLEBench+NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian

Peng Liu, Lemei Zhang, Terje Farup +5

Norwegian, spoken by only 5 million population, is under-representative within the most impressive breakthroughs in NLP tasks. To the best of our knowledge, there has not yet been…