marktechpost5d
Contrastive Twist Learning and Bidirectional SMC Bounds: A New Paradigm for Language Model Control
Large language models (LLMs) have made significant success in various language tasks, but steering their outputs to meet specific properties remains a challenge. Researchers are attempting to solve ...
marktechpost5d
Optimizing AI Safety and Deployment: A Game-Theoretic Approach to Protocol Evaluation in Untrusted AI Systems
AI Control assesses the safety of deployment protocols for untrusted AIs through red-teaming exercises involving a protocol designer and an adversary. AI systems, like chatbots with access to tools ...
marktechpost4d
Verifying RDF Triples Using LLMs with Traceable Arguments: A Method for Large-Scale Knowledge Graph Validation
In recent research, a state-of-the-art technique has been introduced for utilizing Large Language Models (LLMs) to verify RDF (Resource Description Framework) triples, emphasizing the significance of ...
marktechpost6d
NiNo: A Novel Machine Learning Approach to Accelerate Neural Network Training through Neuron Interaction and Nowcasting
In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and ...
marktechpost4d
This AI Paper from Centre for the Governance of AI Proposes a Grading Rubric for AI Safety Frameworks
AI safety frameworks have emerged as crucial risk management policies for AI companies developing frontier AI systems. These frameworks aim to address catastrophic risks associated with AI, including ...
marktechpost5d
MPPI-Generic: A New C++/CUDA library for GPU-Accelerated Stochastic Optimization
Stochastic optimization problems involve making decisions in environments with uncertainty. This uncertainty can arise from various sources, such as sensor noise, system disturbances, or unpredictable ...
marktechpost6d
FuXi-2.0: Advancement in Machine Learning ML-based Weather Forecasting for Practical Applications
ML models are increasingly used in weather forecasting, offering accurate predictions and reduced computational costs compared to traditional numerical weather prediction (NWP) models. However, ...
marktechpost6d
Understanding the Inevitable Nature of Hallucinations in Large Language Models: A Call for Realistic Expectations and Management Strategies
Prior research on Large Language Models (LLMs) demonstrated significant advancements in fluency and accuracy across various tasks, influencing sectors like healthcare and education. This progress ...
marktechpost6d
Deep Learning Approach for Lithium-Ion Battery Life Prediction via Dual-Stream Vision Transformer
Predicting battery lifespan is difficult due to the nonlinear nature of capacity degradation and the uncertainty of operating conditions. As battery lifespan prediction is vital for the reliability ...
marktechpost4d
Jina-Embeddings-v3 Released: A Multilingual Multi-Task Text Embedding Model Designed for a Variety of NLP Applications
Text embedding models have become foundational in natural language processing (NLP). These models convert text into high-dimensional vectors that capture semantic relationships, enabling tasks like ...
marktechpost6d
Allen Institute for AI Researchers Propose SUPER: A Benchmark for Evaluating the Ability of LLMs to Set Up and Execute Research Experiments
Artificial Intelligence (AI) and Machine Learning (ML) have been transformative in numerous fields, but a significant challenge remains in the reproducibility of experiments. Researchers frequently ...
marktechpost5d
Qwen 2.5 Models Released: Featuring Qwen2.5, Qwen2.5-Coder, and Qwen2.5-Math with 72B Parameters and 128K Context Support
The Qwen team from Alibaba has recently made waves in the AI/ML community by releasing their latest series of large language models (LLMs), Qwen2.5. These models have taken the AI landscape by storm, ...