paper.dinq.meAI 与前沿科学顶会 · 学术新星雷达
登录 DINQ
返回新星榜
ÉC

Éric Villemonte de la Clergerie

ACL 2026×2数据与预训练社会与人本强化学习与后训练评测与基准代码
新星分资深
17
一作贡献0
核心/参与5
方向广度10
合作网络3
0 一作 · 2 篇 · ACL 2026

获取完整研究档案

首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。

联系方式

实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。

2026 顶会论文

2
作者位次 #3/3ACL 2026Findings· Findings of ACL

Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level Annotation

Rian Touchent · Nathan Godey · Éric Villemonte de la Clergerie

摘要

We annotate PubMed Central paragraphs for document type, domain, and educational quality using a two-stage pipeline: Llama-3.1-70B labels 400K paragraphs, then a fine-tuned XLM-RoBERTa propagates annotations to the full corpus. This paragraph-level approach captures content diversity within scien...

数据与预训练社会与人本强化学习与后训练OpenReview 项目页
作者位次 #5/7ACL 2026Findings· Findings of ACL

Gaperon: A Peppered E nglish- F rench Generative Language Model Suite

Nathan Godey · Wissam Antoun · Rian Touchent · Rachel Bawden · Éric Villemonte de la Clergerie · Benoît Sagot · Djamé Seddah

摘要

Standardized benchmarks have become the dominant metric for measuring progress in large language models, yet their validity is increasingly compromised by data contamination and the unclear relationship between benchmark scores and genuine language understanding. We introduce Gaperon, a suite of...

评测与基准数据与预训练代码OpenReview 项目页

常见合作者