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

Zhitong Wang

ACL 2026×2AAAI 2026效率与系统推理智能体与工具可解释性评测与基准
新星分贡献者
46
一作贡献0
核心/参与15
方向广度13
合作网络6
0 一作 · 3 篇 · 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

3
作者位次 #5/12ACL 2026Poster· Natural Language Processing

I m C oref- C e S : An Improved Lightweight Pipeline for Coreference Resolution with LLM -based Checker-Splitter Refinement

Kangyang Luo · Yuzhuo Bai · Shuzheng Si · Cheng Gao · Zhitong Wang · Yingli Shen · Wenhao Li · Zhu Liu · Yufeng Han · Jiayi Wu · Cunliang Kong · Maosong Sun

摘要

Coreference Resolution (CR) is a critical task in Natural Language Processing (NLP). Current research faces a key dilemma: whether to further explore the potential of supervised neural methods based on small language models, whose detect-then-cluster pipeline still delivers top performance, or em...

推理智能体与工具效率与系统OpenReview 项目页
作者位次 #5/11ACL 2026Findings· Findings of ACL

MEIC - DT : Memory-Efficient Incremental Clustering for Long-Text Coreference Resolution with Dual-Threshold Constraints

Kangyang Luo · Shuzheng Si · Yuzhuo Bai · Cheng Gao · Zhitong Wang · Cheng Huang · Yingli Shen · Yufeng Han · Wenhao Li · Cunliang Kong · Maosong Sun

摘要

In the era of large language models (LLMs), supervised neural methods remain the state-of-the-art (SOTA) for Coreference Resolution. Yet, their full potential is underexplored, particularly in incremental clustering, which faces the critical challenge of balancing efficiency with performance for...

效率与系统可解释性评测与基准OpenReview 项目页

常见合作者