Anthropic says it solved the long-running AI agent problem with a new multi-session Claude SDK

Anthropic believes it has solved this issue for its Claude Agent SDK, developing a two-fold solution that allows an agent to work across different context windows.

Alibaba's AgentEvolver lifts model performance in tool use by ~30% using synthetic, auto-generated tasks

The new framework from Tongyi Lab enables agents to create their own training data by exploring and interacting with new ...
DIGITIMES

Xiaomi unveils open-source AI model unifying robotics and autonomous driving

Embodied, an open-source foundational model that integrates autonomous driving with embodied intelligence. The research team ...
IEEE

Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions

Abstract: Total electron content (TEC) is a key ionospheric parameter, but data gaps, especially over oceans, remain challenging due to sparse receiver coverage. Deep learning offers promising ...
GitHub

Tro-fish/Decoding-Dense-Embeddings

To train the SAE, you need embeddings generated by a DPR model. We use dense embeddings from SimLM for all 8.8M MSMARCO passages and train queries. After training the SAE, you can reconstruct the ...
Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs ...
IEEE

Selective Imitation Enhanced Deep Reinforcement Learning for AAV Navigation and Obstacle Avoidance With Sparse Rewards

Abstract: Deep reinforcement learning (DRL) has emerged as a promising solution for autonomous operations of autonomous aerial vehicles (AAVs) in unknown environments. However, learning to navigate ...