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

Nathanaël Carraz Rakotonirina

ACL 2026推理强化学习与后训练效率与系统
新星分新星
51
一作贡献30
核心/参与0
方向广度6
合作网络3
1 一作 · 1 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

1
一作ACL 2026Findings· Findings of ACL

Correct, Concise and Complete: Multi-stage Training For Adaptive Reasoning

Nathanaël Carraz Rakotonirina · Ren Pang · Neha Anna John · Michael Bohlke-Schneider · Momchil Hardalov

摘要

The reasoning capabilities of large language models (LLMs) have improved substantially through increased test-time computation, typically in the form of intermediate tokens known as chain-of-thought (CoT). However, CoT often becomes unnecessarily long, increasing computation costs without improvi...

推理强化学习与后训练效率与系统OpenReview 项目页

常见合作者