Researchers propose a new framework for designing reward functions in reinforcement learning called Module Level Reward Evolution Framework (MLREF). T...
Researchers have proposed a new method for data augmentation called Learning-State-Aware Dynamic Generative Data Augmentation (LSADA). LSADA aims to i...
Researchers have developed a new method for launching denial-of-service (DoS) attacks against large reasoning models. The approach, called SMTrap, use...
Researchers have tested five different techniques for improving language model outputs at test time, known as test-time scaling. These methods involve...
Researchers propose a new framework called SkillForge to help large language models resolve specific software issues. Unlike existing approaches that ...
Researchers have developed a graphical notation system for designing interpretable AI architectures. The system, inspired by Penrose tensor notation, ...
Researchers have developed a unified medical model called MedUAG that can understand and generate text from various medical imaging modalities. The mo...
Researchers have developed a new approach to training large language models for single-step retrosynthesis. They introduced Top-K prompting and used a...
Researchers have developed AlphaClifford, a model-based Reinforcement Learning framework for efficiently synthesizing Clifford circuits. These circuit...
Researchers propose a method called rEDMRec that compresses the reasoning process of large language models into a compact, structured memory. This mem...
Researchers have proposed a new framework called DeepWeaver to address the issue of evidence synthesis in open-ended question answering. The current a...
A new AI framework called GrabVG is proposed for visual grounding in Unmanned Aerial Vehicle (UAV) imagery. Visual grounding involves identifying a ta...