MAMMAL is a multi-modal, multi-task foundation model that unifies diverse biological data (proteins, small molecules, omics) to accelerate …
Researches
This paper introduces 'method-level change-proneness' as a novel metric to improve black-box test suite minimization, making testing more …
This explainer details the Pegasus spyware attack on European Parliament members, covering technical compromise, mobile security …
Explaining the new SPEC CPU 2026 benchmark suite, its modernization efforts, and its impact on CPU, memory, and compiler development for the …
This paper argues that DNS names, not IP addresses, are now the fundamental identifiers for service identity, reachability, load balancing, …
Labyrinth 1.1 introduces a new sub-protocol to ensure end-to-end encrypted messages survive device loss, switching, and long sign-in gaps, …
TeamTR introduces trust-region fine-tuning to prevent shared-context drift, a critical failure mode in multi-agent LLM systems, …
This explainer clarifies recent LLM benchmark results, addressing claims of 0% scores and detailing actual performance on complex software …
This paper reveals that instruction-tuned LLMs can produce fair outputs while still retaining causally potent and asymmetrically biased …
This paper proposes 'face density' as a novel metric to quantify data complexity, particularly for instance counting tasks in computer …
Mistral AI's Vox-Trainer is a new multimodal model capable of understanding and generating both spoken audio and text, with accessible …
This paper introduces an actor-verifier AI architecture that enhances reliability and interpretability in safety-critical systems by having …