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

Song-Li Wu

AAAI 2026×2ACL 2026×2KDD 2026检索与知识对齐与偏好推理可解释性多模态
新星分新星
92
一作贡献100
核心/参与14
方向广度16
合作网络6
3 一作 · 5 篇 · AAAI 2026 / ACL 2026 / KDD 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

5
一作ACL 2026Poster· Natural Language Processing

From ID to LLM : Rethinking Representation Learning for Recommendation

Song-Li Wu · Zhaocheng Du · Weinan Gan · Jingyi Wang · Xianquan Wang

摘要

Recent studies indicate a fundamental incompatibility between ID representations and language model (LM) representations, as they capture behavioral and semantic spaces respectively. This mismatch leads LM representations to consistently underperform ID representations in recommendation tasks. In...

对齐与偏好推理可解释性OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

C a PE dit: Capability-Preserving Lifelong Knowledge Editing For Language Models

Song-Li Wu · Zhaocheng Du · Xianquan Wang · Jingyi Wang

摘要

Lifelong knowledge editing (LKE) aims to incrementally correct factual inaccuracies in large language models (LLMs), but sequential edits can lead to substantial degradation of capabilities. Existing approaches primarily rely on static parameter regularization, which restricts knowledge integrati...

检索与知识多模态OpenReview 项目页

常见合作者