From the 1 of 9 linked papers with an AI index.
1 citations · 1 across the 7 of their papers we have counts for
9 papers
From Tokens to Watt-hours: Analytical Energy Estimation for LLM Inference on Modern GPUs
Tina Vartziotis, Rodopi Kosteli, Elli Vartziotis +5
The paper introduces an analytical, calibrated method to estimate the energy consumption of large language model inference on NVIDIA H100 GPUs without direct power measurements, se…
CSE-UOI at SemEval-2026 Task 6: A Two-Stage Heterogeneous Ensemble with Deliberative Complexity Gating for Political Evasion Detection
Christos Tzouvaras, Konstantinos Skianis, Athanasios Voulodimos
This paper describes our system for SemEval-2026 Task 6, which classifies clarity of responses in political interviews into three categories: Clear Reply, Ambivalent, and Clear Non…
GreekMMLU: A Native-Sourced Multitask Benchmark for Evaluating Language Models in Greek
Yang Zhang, Mersin Konomi, Christos Xypolopoulos +6
Large Language Models (LLMs) are commonly trained on multilingual corpora that include Greek, yet reliable evaluation benchmarks for Greek-particularly those based on authentic, na…
On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets
Giannis Nikolentzos, Konstantinos Skianis
The Lipschitz constant of a neural network is connected to several important properties of the network such as its robustness and generalization. It is thus useful in many settings…
Building Multilingual Datasets for Predicting Mental Health Severity through LLMs: Prospects and Challenges
Konstantinos Skianis, John Pavlopoulos, A. Seza DoÄruöz
Large Language Models (LLMs) are increasingly being integrated into various medical fields, including mental health support systems. However, there is a gap in research regarding t…
Leveraging LLMs for Translating and Classifying Mental Health Data
Konstantinos Skianis, A. Seza DoÄruöz, John Pavlopoulos
Large language models (LLMs) are increasingly used in medical fields. In mental health support, the early identification of linguistic markers associated with mental health conditi…