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

Fuwen Luo

ACL 2026×2多模态推理强化学习与后训练可解释性
新星分新星
72
一作贡献60
核心/参与0
方向广度8
合作网络3
2 一作 · 2 篇 · ACL 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

2
一作ACL 2026Poster· Natural Language Processing

MUSEG : Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding

Fuwen Luo · Shengfeng Lou · Chi Chen · Ziyue Wang · Chenliang Li · Weizhou Shen · Jiyue Guo · Peng Li · Ming Yan · Ji Zhang · Fei Huang · Yang Liu

摘要

Video temporal understanding is crucial for multimodal large language models (MLLMs) to reason over events in videos. Despite recent advances in general video understanding, current MLLMs still struggle with fine-grained temporal reasoning. While reinforcement learning (RL) has been explored to a...

多模态强化学习与后训练推理OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

Enabling Stroke-Level Structural Analysis of Hieroglyphic Scripts without Language-Specific Priors

Fuwen Luo · Zihao Wan · Ziyue Wang · Yaluo Liu · Pau Tong Lin Xu · Xuanjia Qiao · Xiaolong Wang · Peng Li · Yang Liu

摘要

Hieroglyphs, as logographic writing systems, encode rich semantic and cultural information within their internal structural composition. Yet, current advanced Large Language Models (LLMs) and Multimodal LLMs (MLLMs) usually remain structurally blind to this information. LLMs process characters as...

可解释性多模态推理OpenReview 项目页

常见合作者