Tech Xplore

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
GitHub

BELM: High-quality Exact Inversion sampler of Diffusion Models

🔥 We introduce a generic formulation of the exact inversion samplers, BELM. the general k-step BELM: $$\bar{\mathbf{x}}_{i-1} = \sum_{j=1}^{k} a_{i,j}\cdot \bar ...
GitHub

SimVQ: Addressing Representation Collapse in Vector Quantized Models with One Linear Layer

imagenet └── train/ ├── n01440764 ├── n01440764_10026.JPEG ├── n01440764_10027.JPEG ├── ... ├── n01443537 ...
IEEE

LiP-LLM: Integrating Linear Programming and Dependency Graph With Large Language Models for Multi-Robot Task Planning

Abstract: This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform ...
Indiatimes

Oracle founder Larry Ellison explains two types of AI models, uses Elon Musk’s Tesla as example of ‘low-latency’ intelligence

Oracle founder Larry Ellison distinguished between two AI model types: those requiring real-time, low-latency decisions for applications like self-driving cars and robotics, and those where delays are ...
IEEE

Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning

Abstract: As one of the most critical components in modern LP solvers, presolve in linear programming (LP) employs a rich set of presolvers to remove different types of redundancy in input problems by ...
Microsoft

“I Want It That Way”: Enabling Interactive Decision Support Using Large Language Models and Constraint Programming

A critical factor in the success of many decision support systems is the accurate modeling of user preferences. Psychology research has demonstrated that users often develop their preferences during ...