Publications associées à Assessment of fine-tuned large language models for real-world chemistry and material science applications

Publications associées (14)

Machine learning enhanced atom probe tomography analysis

Atom probe tomography (APT) is a burgeoning characterization technique that provides compositional mapping of materials in three-dimensions at near-atomic scale. Since its significant expansion in the past 30 years, we estimate that one million APT dataset ...

2026

Personalizing Learning and Empowering Educators through Multi-Dimensional Clustering, Teacher Dashboards, and AI-Hybrid Learning Systems

Paola Mejia Domenzain

The shift from traditional classroom settings to technology-supported learning environments has led to the adoption of learning analytics and artificial intelligence (AI) in education. These technologies promise to support personalized learning by analyzin ...

EPFL2025

Hadamard product in deep learning: Introduction, Advances and Challenges

Volkan Cevher, Yongtao Wu

While convolution and self-attention mechanisms have dominated architectural design in deep learning, this survey examines a fundamental yet understudied primitive: the Hadamard product. Despite its widespread implementation across various applications, th ...

2025

Semantic Segmentation of Benthic Classes in Reef Environments Using a Large Vision Transformer

Devis Tuia, Jonathan Paul Sauder, Charlotte Louise Sertic

Coral reefs are crucial for biodiversity and provide vital resources for humankind. But despite such a central role, they are confronted to increasing threats linked to climate change, pollution, and local stressors. To ensure effective conservation, effic ...

Springer Science and Business Media Deutschland GmbH2025

Representing and machine learning complex electronic-structure properties of materials

Austin Jacob Zadoks

The rise of high-throughput first-principles calculations of materials since the turn of the millennium has gifted the fields of physics, quantum chemistry, and materials science with a mountainous and ever-growing pile of data ready to be mined for hidden ...

EPFL2025

synMARSS—An End-To-End Platform for the Parametric Generation of Synthetic In Vivo Magnetic Resonance Spectra

André Döring

Synthetic magnetic resonance spectra (MRS) are mathematically generated spectra which can be used to investigate the assumptions of data analysis strategies, optimize experimental design, and as training data for the development and validation of machine l ...

2025

PLUMED Tutorials: A collaborative, community-driven learning ecosystem

Michele Ceriotti, Guillaume André Jean Fraux

In computational physics, chemistry, and biology, the implementation of new techniques in shared and open-source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several cha ...

AIP Publishing2025

Songdo Vision: Vehicle Annotations from High-Altitude BeV Drone Imagery in a Smart City

Nikolaos Geroliminis, Robert Fonod

The Songdo Vision dataset provides high-resolution (4K, 3840×2160 pixels) RGB images annotated with categorized axis-aligned bounding boxes (BBs) for vehicle detection from a high-altitude bird’s-eye view (BeV) perspective. Captured over Songdo Internation ...

Zenodo2025

Higher-order knowledge-enhanced recommendation with heterogeneous hypergraph multi-attention

Thanh Trung Huynh

Recent advancements in recommender systems have focused on integrating knowledge graphs (KGs) to leverage their auxiliary information. The core idea of KG-enhanced recommenders is to incorporate rich semantic information for more accurate recommendations. ...

2024

LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields

Mathieu Salzmann

We introduce a new task, novel view synthesis for LiDAR sensors. While traditional model-based LiDAR simulators with style-transfer neural networks can be applied to render novel views, they fall short of producing accurate and realistic LiDAR patterns bec ...

Association for Computing Machinery, Inc2024

Knowledge-Aware Visual Question Generation for Remote Sensing Images

Devis Tuia, Javiera Francisca Castillo Navarro, Li Mi

With the rapid development of remote sensing image archives, asking questions about images has become an effective way of gathering specific information or performing image retrieval. However, automatically generated image-based questions tend to be simpli ...

IEEE2024

Combining general and personal models for epilepsy detection with hyperdimensional computing

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Epilepsy is a highly prevalent chronic neurological disorder with great negative impact on patients' daily lives. Despite this there is still no adequate technological support to enable epilepsy detection and continuous outpatient monitoring in everyday li ...

Elsevier2024

Unsupervised quality monitoring of metal additive manufacturing using Bayesian adaptive resonance

Patrik Willi Hoffmann

Metal additive manufacturing is a recent breakthrough technology that promises automated production of complex geometric shapes at low operating costs. However, its potential is not yet fully exploited due to the low reproducibility of quality in mass prod ...

CELL PRESS2024

Optimizing Context-Enhanced Relational Joins

Anastasia Ailamaki, Viktor Sanca

Collecting data, extracting value, and combining insights from relational and context-rich sources of many modalities in data processing pipelines presents a challenge for traditional relational DBMS. While relational operators enable declarative and optim ...

IEEE2024