activity
20242026
most citedMulti-Modal Video Feature Extraction for Popularity Prediction

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

PRISM: Pareto-Efficient Retrieval over Intent-Aware Structured Memory for Long-Horizon Agents

Jingyi Peng, Zhongwei Wan, Weiting Liu +1

Long-horizon language agents accumulate conversation history far faster than any fixed context window can hold, making memory management critical to both answer accuracy and servin…

cs.CV2026

FORGE: Fine-grained Multimodal Evaluation for Manufacturing Scenarios

Xiangru Jian, Hao Xu, Wei Pang +13

The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution, yet current evaluations fai…

cs.CV2025

Tighnari: Multi-modal Plant Species Prediction Based on Hierarchical Cross-Attention Using Graph-Based and Vision Backbone-Extracted Features

Haixu Liu, Penghao Jiang, Zerui Tao +2

Predicting plant species composition in specific spatiotemporal contexts plays an important role in biodiversity management and conservation, as well as in improving species identi…

cs.CV2025★ 2 cited

Multi-Modal Video Feature Extraction for Popularity Prediction

Haixu Liu, Wenning Wang, Haoxiang Zheng +4

This work aims to predict the popularity of short videos using the videos themselves and their related features. Popularity is measured by four key engagement metrics: view count,…

cs.CV2025

nnY-Net: Swin-NeXt with Cross-Attention for 3D Medical Images Segmentation

Haixu Liu, Zerui Tao, Wenzhen Dong +1

This paper provides a novel 3D medical image segmentation model structure called nnY-Net. This name comes from the fact that our model adds a cross-attention module at the bottom o…

cs.LG2024

Unveiling and Controlling Anomalous Attention Distribution in Transformers

Ruiqing Yan, Xingbo Du, Haoyu Deng +7

With the advent of large models based on the Transformer architecture, researchers have observed an anomalous phenomenon in the Attention mechanism--there is a very high attention…