training strategies
The various methodologies and approaches employed during the training phase of AI models, including techniques such as batch training, online learning, and curriculum learning aimed at improving model efficacy.
- Cognitive Mirrors: Exploring the Diverse Functional Roles of Attention Heads in LLM Reasoning
- ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
- ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
- Improve Temporal Reasoning in Multimodal Large Language Models via Video Contrastive Decoding
- Improving Time Series Forecasting via Instance-aware Post-hoc Revision
- OmniBench: Towards The Future of Universal Omni-Language Models
- On the Stability and Generalization of Meta-Learning: the Impact of Inner-Levels
- Towards General Modality Translation with Contrastive and Predictive Latent Diffusion Bridge