GPUs, training clusters, MLOps, and deployment
Perplexity just ran a structural analysis on the criticism campaign against my work. What it found: synchronized language across posts, n...
Crescendo (Russinovich et al., USENIX Security 2025) is a multi-turn jailbreak that starts with innocent questions and gradually steers a...
I built Arc Sentry, a pre-generation guardrail for open source LLMs that blocks prompt injection before the model generates a response. I...
Nvidia's recent partnership with Meta marks a significant shift in AI computing, focusing on efficient chip usage for both training and i...
Darren Mowry, Google Cloud’s VP for startups, discusses the challenges and strategies for AI startups in a competitive landscape, emphasi...
Google Cloud's VP discusses the challenges startups face in scaling, including funding pressures and infrastructure choices, in a recent ...
Gradio's new gr.HTML feature allows users to create interactive web apps using a single Python file, enabling seamless integration of fro...
Amazon has discontinued its Blue Jay robotics project after less than six months, citing the intention to repurpose its core technology f...
The article discusses rumors about Qwen3.5 integrating Mixture of Experts (MoE) with Hybrid Attention to enhance inference efficiency in ...
IBM and UC Berkeley explore the failures of enterprise agents in IT automation, utilizing IT-Bench and MAST to diagnose issues and improv...
The article presents a controversial viewpoint that AI's takeover of knowledge work jobs is essential for redirecting human efforts towar...
The article discusses the potential performance advantages of ZeRO-1 over ZeRO-2 in parallel training, highlighting insights from empiric...
The article discusses the considerations for choosing between agentic and workflow-based solutions in machine learning applications, emph...
Google's AI Cloud business shows significant profitability, with a 48% revenue growth and a 154% increase in operating profit, driven by ...
This article discusses a multi-agent pipeline using LLMs that demonstrated emergent self-correction behavior, improving task coverage thr...
![[2601.01581] CONSENT: A Negotiation Framework for Leveraging User Flexibility in Vehicle-to-Building Charging under Uncertainty](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents CONSENT, a negotiation framework designed to optimize vehicle-to-building (V2B) charging by balancing the needs of bui...
The paper presents MARS-Sep, a novel reinforcement learning framework for sound separation that enhances semantic consistency by aligning...
This study explores a new Self-correction Loop with Structured Output (SLSO) framework to enhance the accuracy of AI-generated findings f...
LogiPart introduces a scalable framework for data exploration using local large language models, enhancing the efficiency of taxonomic di...
The paper presents a novel framework for premise verification in large language models (LLMs) to reduce hallucinations by using retrieval...
The paper introduces the Intermittent Semi-Working Mask (ISM), a novel masking paradigm for Large Language Models (LLMs) that enhances mu...
The paper discusses the critical energy concerns associated with High-Performance Computing (HPC) systems and applications, emphasizing t...
This paper examines the shortcomings of speech recognition models in accurately transcribing high-stakes utterances, particularly U.S. st...
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