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

Liyan Xu

ACL 2026×2AAAI 2026ICML 2026检索与知识推理评测与基准可解释性效率与系统
新星分贡献者
74
一作贡献30
核心/参与17
方向广度16
合作网络12
1 一作 · 4 篇 · ACL 2026 / AAAI 2026 / ICML 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
一作ICML 2026Poster· Deep Learning / Large Language Models

How Far Ahead Do LLMs Plan? Uncovering the Latent Horizon in Chain-of-Thought Reasoning

Liyan Xu · Mo Yu · Fandong Meng · Jie Zhou

作者位次 #5/9ACL 2026Poster· Natural Language Processing

Situated Embedding Models for Context-Aware Dense Retrieval

Junjie Wu · Jiangnan Li · Yuqing Li · Lemao Liu · Liyan Xu · Jiwei Li · Dit-Yan Yeung · Jie Zhou · Mo Yu

摘要

Retrieval-augmented generation (RAG) over long documents typically involves splitting the text into smaller chunks, which serve as the basic units for retrieval. However, due to dependencies across the original document, contextual information is often essential for accurately interpreting each c...

评测与基准检索与知识可解释性OpenReview 项目页
作者位次 #2/9ACL 2026Findings· Findings of ACL

R e F ree KV : Towards Threshold-Free KV Cache Compression

Xuanfan Ni · Liyan Xu · Chenyang Lyu · Longyue Wang · Mo Yu · Lemao Liu · Fandong Meng · Jie Zhou · Piji Li

摘要

To reduce memory consumption during LLM inference, a handful of methods have been proposed for KV cache pruning.While these techniques can accomplish lossless memory reduction on many datasets, they often hinge on an under-emphasized condition: an input/domain-specific threshold for KV cache budg...

效率与系统数据与预训练检索与知识OpenReview 项目页

常见合作者