Augmenting large language models with chemistry tools

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Quasi-operando Transmission Electron Microscopy Diagnostics for Electrocatalytic Processes in Liquids

Vasiliki Tileli

It is of great interest to the energy community to understand how the mechano-physico-chemical phenomena that eventually lead to device degradation are related to the startup, operation, and shutdown phases. For electrocatalytic systems operating in liquid ...

Swiss Chemical Soc2024

Nanomole-scale photochemical thiol-ene chemistry for high-throughput late-stage diversification of peptide macrocycles

Alexander Lund Nielsen, Mischa Schüttel

The photochemical thiol-ene reaction is an efficient method for rapid and chemoselective formation of thioether linkages under mild conditions. It has found widespread use in small-molecule synthesis as well as peptide and protein chemistry. While high-thr ...

WILEY2023

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

Yumeng Hou

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

Association for Computing Machinery2023

Improving Generalization of Pretrained Language Models

Rabeeh Karimi Mahabadi

In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

EPFL2023

Unlocking a multimodal archive of Southern Chinese martial arts through embodied cues

Sarah Irene Brutton Kenderdine, Yumeng Hou

Purpose: Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as appa ...

2023

Appropriations and Uses of Travel Time

Ludy Juliana González Villamizar

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

ISTE Wiley2023

Building a Knowledge Graph of Chinese Kung Fu Masters From Heterogeneous Bilingual Data

Lin Yuan, Yumeng Hou, Lin Yuan

Various endeavours into semantic web technologies and ontology engineering have been made within the organisation of cultural data, facilitating public access to digital assets. Although models for conceptualising objects have reached a certain level of ma ...

2023

Prompting Large Language Models to Power Educational Chatbots

Fanny Kim-Lan Lasne, Denis Gillet, Juan Carlos Farah, Sandy Ingram, Basile Maurice Pierre Spaenlehauer

The recent rise in both popularity and performance of large language models has garnered considerable interest regarding their applicability to education. Technologies like ChatGPT, which can engage in human-like dialog, have already disrupted educational ...

Springer2023

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

Atomic scale volume and grain boundary diffusion elucidated by in situ STEM

Johann Michler, Xavier Maeder, Laszlo Pethö

Diffusion is one of the most important phenomena studied in science ranging from physics to biology and, in abstract form, even in social sciences. In the field of materials science, diffusion in crystalline solids is of particular interest as it plays a p ...

Nature Portfolio2023

Data-Driven Discovery of Organic Electronic Materials Enabled by Hybrid Top-Down/Bottom-Up Design

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Sergio Vela Llausi, Jacob Terence Blaskovits

The high-throughput exploration and screening of molecules for organic electronics involves either a 'top-down' curation and mining of existing repositories, or a 'bottom-up' assembly of user-defined fragments based on known synthetic templates. Both are t ...

Wiley-V C H Verlag Gmbh2023

Artificial intelligence for natural product drug discovery

Philippe Schwaller, Albert Hofstetter, Michael Alexander Skinnider, Florian Huber

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to e ...

Nature Portfolio2023