1 citations · 1 across the 2 of their papers we have counts for
5 papers
NovoMolGen: Rethinking Molecular Language Model Pretraining
Kamran Chitsaz, Roshan Balaji, Quentin Fournier +2
Designing de-novo molecules with desired property profiles requires efficient exploration of the vast chemical space ranging from to possible synthesizable cand…
CADmium: Fine-Tuning Code Language Models for Text-Driven Sequential CAD Design
Prashant Govindarajan, Davide Baldelli, Jay Pathak +2
Computer-aided design (CAD) is the digital construction of 2D and 3D objects, and is central to a wide range of engineering and manufacturing applications like automobile and aviat…
Small Encoders Can Rival Large Decoders in Detecting Groundedness
Istabrak Abbes, Gabriele Prato, Quentin Fournier +4
Augmenting large language models (LLMs) with external context significantly improves their performance in natural language processing (NLP) tasks. However, LLMs struggle to answer…
NeoBERT: A Next-Generation BERT
Lola Le Breton, Quentin Fournier, Mariam El Mezouar +2
Recent innovations in architecture, pre-training, and fine-tuning have led to the remarkable in-context learning and reasoning abilities of large auto-regressive language models su…
Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs
Megh Thakkar, Quentin Fournier, Matthew Riemer +4
There is a growing interest in training domain-expert LLMs that excel in specific technical fields compared to their general-purpose instruction-tuned counterparts. However, these…