Looped language model training cannot control hidden-state norm growth because RMSNorm normalizes scale away before the loss sees it. A paper posted today on arXiv identifies this readout blind spot, ...

This is an implementation of the equivalence checker presented in "Semantic Program Alignment for Equivlance Checking" by Berkeley Churchill, Oded Padon, Rahul Sharma and Alex Aiken, presented at PLDI ...

How modern fuzz testing has evolved into a core assurance technique for embedded, real-time, and safety-critical software, and why it’s essential where exhaustive testing is infeasible. How fuzzing ...

"It's like Gmail for your coding agents!" A mail-like coordination layer for AI coding agents, exposed as an MCP server with 37 tools and 25 resources, Git-backed archive, SQLite indexing, an ...

As artificial intelligence (AI) models are increasingly capable of producing more life-like content, there has been an understandable hesitancy regarding “deepfakes” and their potential negative ...

Combinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical ...

While there have been some notable successes with program verification systems, a the use of such systems is still perceived as a niche activity for the most critical and specialized projects. 1, 23, ...

1 On our inability to do much. 4 On the reliability of mechanisms. 8 On our mental aids. 15 An example of a correctness proof. 19 On the validity of proofs versus the validity of implementations. 21 ...

Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077 Centre for Biosystems, Neuroscience, and Nanotechnology, City University of Hong Kong, Kowloon, Hong Kong ...

In this work, we introduce signal-to-noise ratio (SNR) based fault detection and identification mechanisms for a networked control system feedback loop, where the network component is represented by ...

Structural bioinformatics suffers from the lack of interfaces connecting biological structures and machine learning methods, making the application of modern neural network architectures impractical.