3 citations · 3 across the 11 of their papers we have counts for
13 papers
BayesJudge: Uncertainty-Aware Bayesian Meta-Evaluation of Human and LLM Judgments
Jiahao Zhang, Pengbin Feng, Chunlei Meng +2
AI evaluation pipelines often produce conflicting judgments rather than clean labels. In pairwise LLM evaluation, this conflict is especially visible: disagreement can arise from a…
EvoGen-Harness: Learning Where and How to Evolve Image-Generation Harnesses
Jiabin Luo, Yinan Liu, Chunlei Meng +1
Modern text-to-image (T2I) systems can be improved without modifying generator parameters by adapting the external system around frozen generators. However, existing approaches typ…
Adaptive Hierarchical Representation Alliance for Multimodal Learning
Chunlei Meng, Pengbin Feng, Jacqueline J. Pang +5
Multimodal models often align language, vision, and audio in a single final-layer latent space, implicitly assuming that task-relevant evidence emerges at the same semantic depth a…
Rethinking Modality Reliability in Multimodal Sentiment Analysis with Incomplete Observations
Chunlei Meng, Jacqueline J. Pang, Pengbin Feng +3
Multimodal Sentiment Analysis (MSA) integrates text, audio, and vision to infer human affect, yet real-world multimodal observations are often incomplete. Existing methods for inco…
Learning Spatiotemporal Decision Priors for Efficient Path Planning under Partial Observability
Yi Liu, Hongda Zhang, Leyao Zou +7
Path planning under partial observability remains challenging because an agent must make long-horizon navigation decisions from only locally bounded observations. Nevertheless, his…
Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration
Chunlei Meng, Pengbin Feng, Rong Fu +7
Centralized multimodal learning commonly compresses language, acoustic, and visual signals into a single fused representation for prediction. While effective, this paradigm suffers…
Mitigating Shared-Private Branch Imbalance via Dual-Branch Rebalancing for Multimodal Sentiment Analysis
Chunlei Meng, Jiabin Luo, Pengbin Feng +4
Multimodal Sentiment Analysis (MSA) requires integrating language, acoustic, and visual signals without sacrificing modality-specific sentiment evidence. Existing methods mainly im…
CLCR: Cross-Level Semantic Collaborative Representation for Multimodal Learning
Chunlei Meng, Guanhong Huang, Rong Fu +3
Multimodal learning aims to capture both shared and private information from multiple modalities. However, existing methods that project all modalities into a single latent space f…
Tri-Subspaces Disentanglement for Multimodal Sentiment Analysis
Chunlei Meng, Jiabin Luo, Zhenglin Yan +4
Multimodal Sentiment Analysis (MSA) integrates language, visual, and acoustic modalities to infer human sentiment. Most existing methods either focus on globally shared representat…
Temporal-Spatial Decouple before Act: Disentangled Representation Learning for Multimodal Sentiment Analysis
Chunlei Meng, Ziyang Zhou, Lucas He +3
Multimodal Sentiment Analysis integrates Linguistic, Visual, and Acoustic. Mainstream approaches based on modality-invariant and modality-specific factorization or on complex fusio…
Pheromone-Focused Ant Colony Optimization algorithm for path planning
Yi Liu, Hongda Zhang, Zhongxue Gan +4
Ant Colony Optimization (ACO) is a prominent swarm intelligence algorithm extensively applied to path planning. However, traditional ACO methods often exhibit shortcomings, such as…
ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation
Bowen Liu, Chunlei Meng, Wei Lin +4
Accurate vascular segmentation is essential for coronary visualization and the diagnosis of coronary heart disease. This task involves the extraction of sparse tree-like vascular b…
CTA-Net: A CNN-Transformer Aggregation Network for Improving Multi-Scale Feature Extraction
Chunlei Meng, Jiacheng Yang, Wei Lin +4
Convolutional neural networks (CNNs) and vision transformers (ViTs) have become essential in computer vision for local and global feature extraction. However, aggregating these arc…