8 citations · 18 across the 14 of their papers we have counts for
16 papers
PACT: Proactive Asking for Continual Task Assistance in Human-Robot Collaboration
Chengbo He, Sheng Li, Chenyang Ma +6
Robotic assistants in long-term human-robot collaboration need to assist users under partial observations while leveraging cross-day interaction history. However, human traits and…
Video-Only ToM: Enhancing Theory of Mind in Multimodal Large Language Models
Siqi Liu, Xinyang Li, Bochao Zou +3
As large language models (LLMs) continue to advance, there is increasing interest in their ability to infer human mental states and demonstrate a human-like Theory of Mind (ToM). M…
DecepGPT: Schema-Driven Deception Detection with Multicultural Datasets and Robust Multimodal Learning
Jiajian Huang, Dongliang Zhu, Zitong YU +4
Multimodal deception detection aims to identify deceptive behavior by analyzing audiovisual cues for forensics and security. In these high-stakes settings, investigators need verif…
Boosting Micro-Expression Analysis via Prior-Guided Video-Level Regression
Zizheng Guo, Bochao Zou, Yinuo Jia +2
Micro-expressions (MEs) are involuntary, low-intensity, and short-duration facial expressions that often reveal an individual's genuine thoughts and emotions. Most existing ME anal…
ME-TST+: Micro-expression Analysis via Temporal State Transition with ROI Relationship Awareness
Zizheng Guo, Bochao Zou, Junbao Zhuo +1
Micro-expressions (MEs) are regarded as important indicators of an individual's intrinsic emotions, preferences, and tendencies. ME analysis requires spotting of ME intervals withi…
From Black Boxes to Transparent Minds: Evaluating and Enhancing the Theory of Mind in Multimodal Large Language Models
Xinyang Li, Siqi Liu, Bochao Zou +2
As large language models evolve, there is growing anticipation that they will emulate human-like Theory of Mind (ToM) to assist with routine tasks. However, existing methods for ev…
AGC-Drive: A Large-Scale Dataset for Real-World Aerial-Ground Collaboration in Driving Scenarios
Yunhao Hou, Bochao Zou, Min Zhang +7
By sharing information across multiple agents, collaborative perception helps autonomous vehicles mitigate occlusions and improve overall perception accuracy. While most previous w…
DeCoDe: Defer-and-Complement Decision-Making via Decoupled Concept Bottleneck Models
Chengbo He, Bochao Zou, Junliang Xing +3
In human-AI collaboration, a central challenge is deciding whether the AI should handle a task, be deferred to a human expert, or be addressed through collaborative effort. Existin…
Enhancing LLM Reasoning with Multi-Path Collaborative Reactive and Reflection agents
Chengbo He, Bochao Zou, Xin Li +3
Agents have demonstrated their potential in scientific reasoning tasks through large language models. However, they often face challenges such as insufficient accuracy and degenera…
RNet: Adversarial Attack Resilient Network for Robust Infrared and Visible Image Fusion
Jiawei Li, Hongwei Yu, Jiansheng Chen +5
Infrared and visible image fusion (IVIF) is a crucial technique for enhancing visual performance by integrating unique information from different modalities into one fused image. E…
Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transition
Bochao Zou, Zizheng Guo, Wenfeng Qin +3
Micro-expressions are involuntary facial movements that cannot be consciously controlled, conveying subtle cues with substantial real-world applications. The analysis of micro-expr…
Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training
Kun Song, Zhiquan Tan, Bochao Zou +3
In this paper, we introduce matrix entropy as an analytical tool for studying supervised learning, investigating the information content of data representations and classification…
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song, Zhiquan Tan, Bochao Zou +2
In this paper, we use matrix information theory as an analytical tool to analyze the dynamics of the information interplay between data representations and classification head vect…
RhythmMamba: Fast, Lightweight, and Accurate Remote Physiological Measurement
Bochao Zou, Zizheng Guo, Xiaocheng Hu +1
Remote photoplethysmography (rPPG) is a method for non-contact measurement of physiological signals from facial videos, holding great potential in various applications such as heal…
RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention
Bochao Zou, Zizheng Guo, Jiansheng Chen +3
Remote photoplethysmography (rPPG) is a non-contact method for detecting physiological signals based on facial videos, holding high potential in various applications. Due to the pe…
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
Kun Song, Huimin Ma, Bochao Zou +2
Due to the limited availability of data, existing few-shot learning methods trained from scratch fail to achieve satisfactory performance. In contrast, large-scale pre-trained mode…