marktechpost3d
How Large Language Models (LLMs) can Perform Multiple, Computationally Distinct In-Context Learning (ICL) Tasks Simultaneously
Large Language Models (LLMs) have demonstrated remarkable proficiency in In-Context Learning (ICL), which is a technique that teaches them to complete tasks using just a few examples included in the ...
marktechpost3d
CodeJudge: An Machine Learning Framework that Leverages LLMs to Evaluate Code Generation Without the Need for Test Cases
Artificial Intelligence is evolving significantly, and Large Language Models have shown a remarkable capacity to comprehend human-text inputs. Going beyond simple text to analyzing and generating code ...
marktechpost5d
Thinking LLMs: How Thought Preference Optimization Transforms Language Models to Perform Better Across Logic, Marketing, and Creative Tasks
Large language models (LLMs) have evolved to become powerful tools capable of understanding and responding to user instructions. Based on the transformer architecture, these models predict the next ...
marktechpost4d
Nvidia AI Quietly Launches Nemotron 70B: Crushing OpenAI’s GPT-4 on Various Benchmarks
Current generative AI models face challenges related to robustness, accuracy, efficiency, cost, and handling nuanced human-like responses. There is a need for more scalable and efficient solutions ...
marktechpost3d
IoT-LLM: An AI Framework that Integrates IoT Sensor Data with LLMs to Enhance their Perception and Reasoning Abilities in the Physical World
Widely growing sectors, like Healthcare, logistics, and smart cities, are interconnected on devices that require task reasoning capabilities in the Internet of Things (IoT) systems. This requirement ...
marktechpost4d
Google AI Research Examines Random Circuit Sampling (RCS) for Evaluating Quantum Computer Performance in the Presence of Noise
Quantum computers are a revolutionary technology that harnesses the principles of quantum mechanics to perform calculations that would be infeasible for classical computers. Evaluating the performance ...
marktechpost4d
AutoDAN-Turbo: A Black-Box Jailbreak Method for LLMs with a Lifelong Agent
Large language models (LLMs) have gained widespread adoption due to their advanced text understanding and generation capabilities. However, ensuring their responsible behavior through safety alignment ...
marktechpost3d
Google AI Researchers Propose ‘MODEL SWARMS’: A Collaborative Search Algorithm to Flexibly Adapt Diverse LLM Experts to Wide-Ranging Purposes
There is a need for flexible and efficient adaptation of large language models (LLMs) to various tasks. Existing approaches, such as mixture-of-experts (MoE) and model arithmetic, struggle with ...
marktechpost5d
Embodied Agent Interface: An AI Framework for Benchmarking Large Language Models (LLMs) for Embodied Decision Making
Large Language Models (LLMs) need to be evaluated within the framework of embodied decision-making, i.e., the capacity to carry out activities in either digital or physical environments. Even with all ...
marktechpost4d
Mistral AI Introduces Les Ministraux: Ministral 3B and Ministral 8B- Revolutionizing On-Device AI
High-performance AI models that can run at the edge and on personal devices are needed to overcome the limitations of existing large-scale models. These models require significant computational ...
marktechpost3d
From ONNX to Static Embeddings: What Makes Sentence Transformers v3.2.0 a Game-Changer?
There is a growing demand for embedding models that balance accuracy, efficiency, and versatility. Existing models often struggle to achieve this balance, especially in scenarios ranging from ...
marktechpost7d
Salesforce AI Research Proposes Dataset-Driven Verifier to Improve LLM Reasoning Consistency
Large language models (LLMs) often fail to consistently and accurately perform multi-step reasoning, especially in complex tasks like mathematical problem-solving and code generation. Despite recent ...