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

Zhaochen Su

AwardACL 2026×2NeurIPS 2026×2智能体与工具多模态评测与基准检索与知识对齐与偏好
新星分新星
77
一作贡献30
核心/参与27
方向广度13
合作网络12
1 一作 · 4 篇 · ACL 2026 / NeurIPS 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

4
作者位次 #6/8ACL 2026OralOutstanding Paper· Natural Language Processing

Evolutionary Guided Decoding: Iterative Value Refinement for LLM s

Zhenhua Liu · Lijun Li · Ruizhe Chen · Yuxian Jiang · Tong Zhu · Zhaochen Su · Wenliang Chen · Jing Shao

摘要

While guided decoding, especially value-guided methods, has emerged as a cost-effective alternative for controlling language model outputs without re-training models, its effectiveness is limited by the accuracy of the value function. We identify that this inaccuracy stems from a core distributio...

对齐与偏好效率与系统代码OpenReview 项目页
作者位次 #3/7ACL 2026Poster· Natural Language Processing

C ost B ench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

Jiayu Liu · Cheng Qian · Zhaochen Su · Qing Zong · Shijue Huang · Bingxiang He · Yi R. Fung

摘要

Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability. This neglects a crucial capability: agents’ ability to devise and adjust cost-optimal plans in response to changing environments. To bridge this ga...

推理智能体与工具评测与基准OpenReview 项目页

常见合作者