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Llama-3-based OpenBioLLM-Llama3-70B and 8B: Outperforming GPT-4, Gemini, Meditron-70B, Med-PaLM-1 and Med-PaLM-2 in Medical-Domain
With the significant development in the rapidly developing field of Artificial Intelligence driven healthcare, a team of researchers has introduced OpenBioLLM-Llama3-70B & 8B models. These state-of-the-art Large Language Models (LLMs) have the potential to...
OpenVoice V2: Evolving Multilingual Voice Cloning with Enhanced Style Control and Cross-Lingual Capabilities
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...
Physics-Based Deep Learning: Insights into Physics-Informed Neural Networks (PINNs)
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...
Researchers at UC San Diego Propose DrS: A Novel Machine Learning Approach for Learning Reusable Dense Rewards for Multi-Stage Tasks in a Data-Driven Manner
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...
SEED-Bench-2-Plus: An Extensive Benchmark Specifically Designed for Evaluating Multimodal Large Language Models (MLLMs) in Text-Rich Scenarios
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...
SynthEval: A Novel Open-Source Machine Learning Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data
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...
