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

Jiaxin Ding

ACL 2026×2ICML 2026评测与基准多模态智能体与工具代码效率与系统
新星分贡献者
55
一作贡献0
核心/参与22
方向广度13
合作网络9
0 一作 · 3 篇 · ACL 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

3
作者位次 #5/7ACL 2026Poster· Natural Language Processing

V is PCO : Visual Token Pruning Configuration Optimization via Budget-Aware P areto-Frontier Learning for Vision-Language Models

Huawei Ji · Yuanhao Sun · Yuan Jin · Cheng Deng · Jiaxin Ding · Luoyi Fu · Xinbing Wang

摘要

Visual token pruning methods effectively mitigate the quadratic computational growth caused by processing high-resolution images and video frames in vision-language models (VLMs). However, existing approaches rely on predefined pruning configurations without determining whether they achieve compu...

多模态效率与系统评测与基准OpenReview 项目页
作者位次 #2/12ACL 2026Findings· Findings of ACL

GR 1: Reinforcement-Enhanced LLM for Geoscience Reasoning

Yule Xie · Jiaxin Ding · Cheng Deng · Shiqing Gao · Junran Zhang · Sibo Zhang · Zeyuan Wang · Ke Wu · Xin Ding · Luoyi Fu · Meng Jin · Xinbing Wang

摘要

Reinforcement learning (RL) has recently shown remarkable ability to enhance reasoning in large language models (LLMs), yet its potential in scientific domains beyond mathematics remains largely unexplored. Geoscience questions couple broad factual knowledge with multi-step inference and often re...

强化学习与后训练多模态推理OpenReview 项目页

常见合作者