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

Tao Ji

AAAI 2026×2ACL 2026×2ICLR 2026×2多模态强化学习与后训练数据与预训练可解释性智能体与工具
新星分贡献者
65
一作贡献0
核心/参与30
方向广度16
合作网络12
0 一作 · 6 篇 · AAAI 2026 / ACL 2026 / ICLR 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 #14/17ACL 2026Findings· Findings of ACL

Muse: Towards Reproducible Long-Form Song Generation with Fine-Grained Style Control

Changhao Jiang · Jiahao Chen · Zhenghao Xiang · Zhixiong Yang · Hanchen Wang · Jiabao Zhuang · Xinmeng Che · Jiajun Sun · Hui Li · Yifei Cao · Shihan Dou · Ming Zhang · Junjie Ye · Tao Ji · Tao Gui · Qi Zhang · Xuanjing Huang

摘要

Recent commercial systems such as Suno demonstrate strong capabilities in long-form song generation, while academic research remains largely non-reproducible due to the lack of publicly available training data, hindering fair comparison and progress. To this end, we release a fully open-source sy...

数据与预训练多模态评测与基准OpenReview 项目页
作者位次 #11/14ACL 2026Findings· Findings of ACL

From Scores to Preferences: Redefining Evaluation Paradigm for Speech Quality Reward Modeling

Yifei Cao · Changhao Jiang · Jiabao Zhuang · Jiajun Sun · Ming Zhang · Zhiheng Xi · Hui Li · Shihan Dou · Yuran Wang · Yunke Zhang · Tao Ji · Tao Gui · Qi Zhang · Xuanjing Huang

摘要

Speech quality assessment (SQA) is typically formulated as a score regression task based on subjective ratings, such as the Mean Opinion Score (MOS), which inherently suffer from inconsistent standards and limit cross-dataset training and evaluation. To address these limitations, we reformulate S...

对齐与偏好多模态强化学习与后训练OpenReview 项目页

常见合作者