Instant Voice Cloning (IVC) in Text-to-Speech (TTS) synthesis, also known as Zero-shot TTS, allows TTS models to replicate the voice of any given speaker with just a short audio sample without requiring additional training on that speaker. While existing methods like VALLE and XTTS can replicate tone color, they need more flexibility in controlling style… →
Physics-Informed Neural Networks (PINNs) have become a cornerstone in integrating deep learning with physical laws to solve complex differential equations, marking a significant advance in scientific computing and applied mathematics. These networks offer a novel methodology for encoding differential equations directly into the architecture of neural networks, ensuring that solutions adhere to the fundamental laws… →
The success of many reinforcement learning (RL) techniques relies on dense reward functions, but designing them can be difficult due to expertise requirements and trial and error. Sparse rewards, like binary task completion signals, are easier to obtain but pose challenges for RL algorithms, such as exploration. Consequently, the question emerges: Can dense reward functions… →
Evaluating Multimodal Large Language Models (MLLMs) in text-rich scenarios is crucial, given their increasing versatility. However, current benchmarks mainly assess general visual comprehension, overlooking the nuanced challenges of text-rich content. MLLMs like GPT-4V, Gemini-Pro-Vision, and Claude-3-Opus showcase impressive capabilities but lack comprehensive evaluation in text-rich contexts. Understanding text within images requires interpreting textual and visual… →
Computer vision, machine learning, and data analysis across many fields have all seen a surge in the usage of synthetic data in the past few years. Synthetic means to mimic complicated situations that would be challenging, if not impossible, to record in the actual world. Information about individuals, such as patients, citizens, or customers, along… →