How Claude Code Is Reshaping Software—and Anthropic

WIRED spoke with Boris Cherny, head of Claude Code, about how the viral coding tool is changing the way Anthropic works.
GitHub

CGBridge: Bridging Code Graphs and Large Language Models for Better Structure-Aware Code Understanding

CGBridge is a novel framework designed to enhance the code understanding capabilities of Large Language Models (LLMs) by integrating rich structural information from code graphs. Our approach follows ...
GitHub

DEEM: Diffusion models serve as the eyes of large language models for image perception

DEEM is an exploration of using diffusion models as the eyes of multi-modal large language models, with the goal of eliminating potential biases in different visual encoders from a vision-centric ...
IEEE

Vision-Language Consistency Guided Multi-Modal Prompt Learning for Blind AI Generated Image Quality Assessment

Abstract: Recently, textual prompt tuning has shown inspirational performance in adapting Contrastive Language-Image Pre-training (CLIP) models to natural image quality assessment. However, such ...
Frontiers

Diagnostic performance of large language models on the NEJM image challenge: a comparative study with human evaluators and the impact of prompt engineering

1 Department of Radiation Oncology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China 2 Tsinghua Medicine, School of Medicine, ...
IEEE

SARCLIP: The First Vision–Language Foundation Model for SAR Image

Abstract: Foundation models have achieved remarkable breakthroughs across various domains, with the widely use of masked image modeling (MIM) and self-supervised learning (SSL). However, these models ...