6 papers
Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters
Lingxiao Kong, Cong Yang, Oya Deniz Beyan +1
Despite significant advances in Reinforcement Learning (RL), model performance remains highly sensitive to algorithm and hyperparameter configurations, while generalization gaps ac…
Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge
Zeyd Boukhers, Oya Beyan, Cong Yang +1
Scientific knowledge on the Web is published as passive assertions and cannot decide when to validate evidence, reconcile contradictions, or update confidence as findings accumulat…
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…
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…
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…
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…