3 citations · 6 across the 18 of their papers we have counts for
10 papers · 1 filter
Multi-Objective Reinforcement Learning for Large Language Model Optimization: Visionary Perspective
Lingxiao Kong, Cong Yang, Oya Deniz Beyan +1
Multi-Objective Reinforcement Learning (MORL) presents significant challenges and opportunities for optimizing multiple objectives in Large Language Models (LLMs). We introduce a M…
MoiréNet: A Compact Dual-Domain Network for Image Demoiréing
Shuwei Guo, Simin Luan, Yan Ke +3
Moiré patterns arise from spectral aliasing between display pixel lattices and camera sensor grids, manifesting as anisotropic, multi-scale artifacts that pose significant challeng…
Towards Systematic Specification and Verification of Fairness Requirements: A Position Paper
Qusai Ramadan, Jukka Ruohonen, Abhishek Tiwari +2
Decisions suggested by improperly designed software systems might be prone to discriminate against people based on protected characteristics, such as gender and ethnicity. Previous…
A Unified Framework for Cultural Heritage Data Historicity and Migration: The ARGUS Approach
Lingxiao Kong, Apostolos Sarris, Miltiadis Polidorou +6
Cultural heritage preservation faces significant challenges in managing diverse, multi-source, and multi-scale data for effective monitoring and conservation. This paper documents…
InstaDA: Augmenting Instance Segmentation Data with Dual-Agent System
Xianbao Hou, Yonghao He, Zeyd Boukhers +4
Acquiring high-quality instance segmentation data is challenging due to the labor-intensive nature of the annotation process and significant class imbalances within datasets. Recen…
Unleashing Semantic and Geometric Priors for 3D Scene Completion
Shiyuan Chen, Wei Sui, Bohao Zhang +3
Camera-based 3D semantic scene completion (SSC) provides dense geometric and semantic perception for autonomous driving and robotic navigation. However, existing methods rely on a…
Exploring the Limits of Model Compression in LLMs: A Knowledge Distillation Study on QA Tasks
Joyeeta Datta, Niclas Doll, Qusai Ramadan +1
Large Language Models (LLMs) have demonstrated outstanding performance across a range of NLP tasks, however, their computational demands hinder their deployment in real-world, reso…
EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning
Lingxiao Kong, Cong Yang, Susanne Neufang +2
Recent advances in reinforcement learning (RL) for large language model (LLM) fine-tuning show promise in addressing multi-objective tasks but still face significant challenges, in…
ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction. A Case Study on Clinical Reports
Aynur Guluzade, Naguib Heiba, Zeyd Boukhers +4
Europe's healthcare systems require enhanced interoperability and digitalization, driving a demand for innovative solutions to process legacy clinical data. This paper presents the…
Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents
Zeyd Boukhers, Cong Yang
The availability of metadata for scientific documents is pivotal in propelling scientific knowledge forward and for adhering to the FAIR principles (i.e. Findability, Accessibility…