A5100306915- Air Quality and Health Impacts
- Atmospheric chemistry and aerosols
- Advanced Photocatalysis Techniques
- Marine and coastal ecosystems
- Emotion and Mood Recognition
- Renal and Vascular Pathologies
- Interconnection Networks and Systems
- Air Quality Monitoring and Forecasting
- Catalytic Processes in Materials Science
- Microencapsulation and Drying Processes
- Sentiment Analysis and Opinion Mining
- Proteins in Food Systems
- biodegradable polymer synthesis and properties
- Sulfur-Based Synthesis Techniques
- Polyoxometalates: Synthesis and Applications
- Distributed and Parallel Computing Systems
- Advanced Computing and Algorithms
- Music Technology and Sound Studies
- CO2 Reduction Techniques and Catalysts
- Advanced Data Processing Techniques
- Neural Networks and Applications
- Neuroscience and Music Perception
- Embedded Systems Design Techniques
Beijing Normal University
2025
State Ethnic Affairs Commission
2025
Alibaba Group (United States)
2025
Shandong Jianzhu University
2024
Fudan University
2024
The inhibitory control dysfunction associated with the cognitive symptoms resulting from repetitive subconcussion (SC) is frequent. Implementing temporally resolved and likely related to dynamic interactions in functional brain networks. However, investigations of activity these networks using electroencephalography (EEG) are often limited specific frequency bands without entirely utilizing spatiotemporal rhythmic information. Therefore, we proposed an innovative framework for constructing a...
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, academic community has intensified its investigations into LLMs with capacities exceeding 50 billion parameters. This technical report builds on our prior work Tele-FLM (also known as FLM-2), publicly available 52-billion-parameter model. We delve two primary areas: we first discuss observation Supervised Fine-tuning (SFT)...
Multimodal emotion recognition (MER) refers to the and understanding of emotional states from multiple types data (e.g., audio, video, etc.). MER in applications such as human-computer interaction, virtual assistants, social media, an accurate user emotions can lead smarter more personalized services. For example, assistants better understand needs users provide responses that are line with expectations. However, existing multimodal research based on LSTM method has poor modeling ability for...
The emergence of Large Language Models (LLMs) has necessitated the adoption parallel training techniques, involving deployment thousands GPUs to train a single model. Unfortunately, we have found that efficiency current is often suboptimal, largely due following two main issues. Firstly, hardware failures are inevitable, leading interruptions in tasks. inability quickly identify faulty components results substantial waste GPU resources. Secondly, since must wait for parameter synchronization...