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

Zeyi Wen

ICLR 2026×3ACL 2026×2AAAI 2026效率与系统可解释性强化学习与后训练长上下文与架构推理
新星分资深
35
一作贡献0
核心/参与29
方向广度16
合作网络3
0 一作 · 6 篇 · ICLR 2026 / ACL 2026 / AAAI 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

6
作者位次 #2/2ICLR 2026Poster· Deep Learning / Attention Mechanisms

Channel-Aware Mixed-Precision Quantization for Efficient Long-Context Inference

Chengxi Liao · Zeyi Wen

效率与系统可解释性长上下文与架构OpenReview
作者位次 #5/5ACL 2026Poster· Natural Language Processing

Efficient Hyperparameter Optimization for LLM Reinforcement Learning

Minping Chen · Bowen Xiao · Du Liang · Chuxuan Zeng · Zeyi Wen

摘要

Hyperparameters are critical to LLM reinforcement learning (RL), but existing hyperparameter optimization (HPO) methods remain inefficient in this area, due to the massive model scale and resource-intensive training cycles. In this paper, we propose Joint Fidelity Hyperparameter Optimization (JF-...

强化学习与后训练可解释性效率与系统OpenReview 项目页
作者位次 #7/7ACL 2026Poster· ACL Industry Track

Enhancing Online Recruitment with Category-Aware M o E and LLM -based Data Augmentation

Minping Chen · Bing Xu · Zulong Chen · Chuanfei Xu · Ying Zhou · Zui Tao · Zeyi Wen

摘要

Person-Job Fit (PJF) is a critical component for online recruitment. Existing approaches face several challenges, particularly in handling low-quality job descriptions and similar candidate-job pairs, which impair model performance. To address these challenges, this paper proposes a large languag...

推理效率与系统评测与基准OpenReview 项目页
作者位次 #2/4AAAI 2026Poster· Artificial Intelligence

A Better Start: Sensitivity-Aware Warm-Up for Robust and Efficient Fine-Tuning

Yile Chen · Zeyi Wen · Jian Chen · Jin Huang

强化学习与后训练效率与系统OpenReview

常见合作者