2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2025
RETROcode: Leveraging a Code Database for Improved Natural Language to Code Generation
Nathanaël Beau, Benoît Crabbé
As text and code resources have expanded, large-scale pre-trained models have shown promising capabilities in code generation tasks, typically employing supervised fine-tuning with…
cs.CL2025
Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning
Jean Vassoyan, Nathanaël Beau, Roman Plaud
The ability to achieve long-term goals is a key challenge in the current development of large language models (LLMs). To address this, pre-trained LLMs can be fine-tuned with reinf…
cs.CL2022★ 2 cited
The impact of lexical and grammatical processing on generating code from natural language
Nathanaël Beau, Benoît Crabbé
Considering the seq2seq architecture of TranX for natural language to code translation, we identify four key components of importance: grammatical constraints, lexical preprocessin…