Engineering
Bekko Embedding: how small can a multilingual retrieval model be?
Bekko Embedding is a family of compact multilingual retrieval models built through layer pruning and contrastive learning. Its smaller variant,…
Engineering
LFM2.5-Encoders for Fast Long-Context Inference on CPU
Liquid AI released two encoder models, LFM2.5-Encoder-230M and -350M, built for efficient long-context processing on CPU by converting decoder architectures…
Engineering
Building abundant intelligence
OpenAI described engineering work, partly performed autonomously by its GPT-5.6 “Sol” model, to optimize the production software that serves its…
Engineering
The Fast Gemma Challenge: our verified-SOTA recipe, in full
The VIDRAFT team documented its winning entry to the Fast Gemma Challenge, reaching 510.58 tokens per second at a perplexity…
Engineering
Discovering Cryptographic Weaknesses with Claude
Anthropic researchers ran an internal model (referred to as “Claude Mythos”) for roughly 60 hours of iterative, human-guided prompting to…
Engineering
Leanstral 1.5: Proof Abundance for All
Mistral AI released Leanstral 1.5, a 6-billion-parameter model for formal proof engineering in Lean 4, under an Apache-2.0 license. It…
Engineering
Bringing More Control Over Your Connectors
Mistral AI detailed new administrative and API-level controls for its agent “connectors” (tool/data integrations), aimed at production deployment concerns. The…
Engineering
Brain2Qwerty v2: From Brain Waves to Words
Meta AI described Brain2Qwerty v2, a system that decodes typed text directly from non-invasive magnetoencephalography (MEG) brain recordings using end-to-end…
Engineering
AISPA: User-Centric System Prompt Auditing for Large Language Model Applications
This paper proposes AISPA, a framework for auditing the hidden system prompts that govern commercial LLM products, which are rarely…
Engineering
smevals Introduces a Standard Vocabulary for LLM Evaluation Pipelines
Simon Willison describes smevals, an evaluation framework built with Prime Radiant that separates running tasks against model variants from grading…
Engineering
How Meta’s SAM and DINO Models Give a Pittsburgh Assistive-Robotics Platform Real-Time Awareness
The University of Pittsburgh’s RAMMP project integrates Meta’s open-source DINO and Segment Anything Model (SAM) to let a robotic mobility…
Engineering
Agentic Context Management Treats AI Agent Memory as a Lifecycle Problem, Not Just Storage
A new paper proposes Agentic Context Management (ACM), reframing agent memory as a lifecycle and architecture problem rather than a…