3 citations · 3 across the 6 of their papers we have counts for
10 papers
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
V Team, Wenyi Hong, Xiaotao Gu +94
We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
Xuan Tong, Yang Chang, Qing Zhao +9
Anomaly detection is critical in industrial manufacturing for ensuring product quality and improving efficiency in automated processes. The scarcity of anomalous samples limits tra…
All rivers run into the sea: Unified Modality Brain-like Emotional Central Mechanism
Xinji Mai, Junxiong Lin, Haoran Wang +10
In the field of affective computing, fully leveraging information from a variety of sensory modalities is essential for the comprehensive understanding and processing of human emot…
Hi-EF: Benchmarking Emotion Forecasting in Human-interaction
Haoran Wang, Xinji Mai, Zeng Tao +6
Affective Forecasting is an psychology task that involves predicting an individual's future emotional responses, often hampered by reliance on external factors leading to inaccurac…
From Efficient Multimodal Models to World Models: A Survey
Xinji Mai, Zeng Tao, Junxiong Lin +5
Multimodal Large Models (MLMs) are becoming a significant research focus, combining powerful large language models with multimodal learning to perform complex tasks across differen…
Suppressing Uncertainties in Degradation Estimation for Blind Super-Resolution
Junxiong Lin, Zeng Tao, Xuan Tong +10
The problem of blind image super-resolution aims to recover high-resolution (HR) images from low-resolution (LR) images with unknown degradation modes. Most existing methods model…