All entries

arXiv:2510.03096v2 Announce Type: replace Abstract: We propose an adaptive node feature selection approach for graph neural networks (GNNs) that identifies and removes unnecessary features during trai

arXiv:2605.00171v1 Announce Type: cross Abstract: In this paper, we study norm-based regularization methods for neural networks. We compare existing penalization approaches and introduce two regulariz

arXiv:2605.00696v1 Announce Type: cross Abstract: We study adaptive querying for learning user-dependent quantities of interest, such as responses to held-out items and psychometric indicators, within

arXiv:2605.00374v1 Announce Type: new Abstract: Edge classification, a crucial task for graph applications, remains relatively under-explored compared to link prediction. Current methods often overloo

arXiv:2510.10913v3 Announce Type: replace Abstract: Recent progress in large language models (LLMs) has enabled them to communicate their confidence in natural language, improving transparency and rel

arXiv:2605.00604v1 Announce Type: new Abstract: Sparse MoE routing fails at domain transitions, where the current token belongs to one distribution and the next to another. In a controlled experiment

arXiv:2605.00663v1 Announce Type: cross Abstract: Affordance grounding requires identifying where and how an agent should interact in open-world scenes, where actionable regions are often small, occlu

arXiv:2605.00410v1 Announce Type: new Abstract: A multi-agent pipeline with N agents typically issues N LLM calls per run. Merging agents into fewer calls (compound execution) promises token savings,

arXiv:2603.25719v2 Announce Type: replace-cross Abstract: We present an empirical study of how far general-purpose coding agents -- without hardware-specific training -- can optimize hardware designs

Amazon SageMaker AI now offers an agentic experience that changes this. Developers describe their use case using natural language, and the AI coding agent streamlines the entire journey, from use case

arXiv:2605.00334v1 Announce Type: cross Abstract: Production agentic systems make many model calls per user request, and most of those calls are short, structured, and routine. This raises a practical

arXiv:2605.00383v1 Announce Type: new Abstract: The delivery of traditional substance education has remained problematic due to challenges in scalability, personalization, and the currency of informat

The rapid rise of agentic development has radically transformed the software engineering landscape, compelling enterprises to embrace a multi-model AI ecosystem. The pace of change in software develop

Agents are now the primary consumers of knowledge infrastructure. Tomorrow @jennapederson, Arjun Patel, and @RoieSchwabco are going live here to talk about what that means for your stack, share this w

arXiv:2605.00539v1 Announce Type: new Abstract: Quantization is a key method for reducing the GPU memory requirement of training large language models (LLMs). Yet, current approaches are ineffective f

Cerebras Systems Inc., a maker of supersized artificial intelligence chips, today disclosed the financial terms of its upcoming public offering. The company hopes to raise as much as 3.5 billion by se

Most discussions about artificial intelligence security are focused on what models might do wrong. The more urgent issue is what our detection systems still cannot see — and side-channel attacks are m

AI morality should be grounded in durable principles like being maximally truth seeking, enabling human agency, freedom of thought + humility under uncertainty Instead of inheriting the moral fashion

arXiv:2605.00111v1 Announce Type: new Abstract: Person re-identification (Re-ID) aims to match images of the same individual across non-overlapping camera views and remains challenging due to domain s

This article from Latent Space likely explores the distinction between AI systems designed for general-purpose utility versus those optimized for specific alternative applications or use cases. The pi

arXiv:2605.00020v1 Announce Type: new Abstract: The success of large foundation models is catalyzing a new paradigm for AI-native 6G network design: wireless foundation models for physical layer desig

arXiv:2605.00716v1 Announce Type: new Abstract: Representation learning is central to graph machine learning, powering tasks such as link prediction and node classification. However, most graph embedd

arXiv:2605.00251v1 Announce Type: cross Abstract: Existing voice deepfake detection and localization models rely heavily on representations extracted from speech foundation models (SFMs). However, dow

Almost every warning that I have issued over the last several years has come true. You better hope to God or Darwin or whoever you believe in that this one is wrong. Accidental nuclear war is a potent

arXiv:2605.00369v1 Announce Type: new Abstract: We study how large language models can be used to evolve inventory policies in online, non-stationary environments. Our work is motivated by recent adva

Deborah Sophia / Reuters: Amazon debuts Supply Chain Services, allowing other companies to use its logistics network to move, store, and deliver raw materials, final products, and more — Amazon.com (A

AMD has announced HDMI 2.1 support for Linux and SteamOS, enabling higher bandwidth for 4K 120Hz gaming and variable refresh rate (VRR) . The initial update includes HDMI Fixed Rate Link but excludes

Wall Street Journal: An analysis of 1.6M Polymarket accounts since November 2022: 0.1% of users take 67% of profits, with the highest-frequency traders seeing the most success — A WSJ analysis shows a

arXiv:2605.00291v1 Announce Type: new Abstract: The application of computer vision is gradually increasing across various domains. They employ deep learning models with a black-box nature. Without the

Most enterprise AI pilots are failing to deliver measurable AI business value, and Appian Corp. is suggesting that the culprit isn’t the technology. The gap between AI experimentation and real enterpr

Announcing Cofounder 2: Run an entire company with agents. It's the infrastructure for the one person billion dollar company - orchestrating agents across engineering, sales, marketing, ops, and desig

I cannot provide a factual summary without access to the actual form content. This appears to be an application form shared by ComfyUI on X (Twitter), likely for a program, position, or opportunity re

I just sent out the April edition of my sponsors-only monthly newsletter. If you are a sponsor (or if you start a sponsorship now) you can access it here. In this month's newsletter: Opus 4.7 and GPT-

arXiv:2605.00270v1 Announce Type: new Abstract: Standard methods for aggregating natural language judgments, such as majority voting, often fail to produce logically consistent results when applied to

Owen Tucker-Smith / Wall Street Journal: As Colorado tech leaders say that burdensome regulations are driving companies away, lawmakers introduce a slimmer version of an AI anti-discrimination bill —

This post discusses Ollama's functionality for resuming work with Anthropic's Claude models, indicating that users can safely restore previous sessions or states using a command-line interface (`ollam

🌐At the @UN, @Yoshua_Bengio briefed @antonioguterres on AI governance, followed by a reception with @CanadaUN & @DavidLametti opened by @EgriseldaL As AI risks grow, global coordination matters. 🔗AI D

arXiv:2605.00667v1 Announce Type: new Abstract: Safety is a primary challenge in real-world reinforcement learning (RL). Formulating safety requirements as state-wise constraints has become a prominen

arXiv:2605.00058v1 Announce Type: cross Abstract: The primary goal of Design Verification (DV) is to ensure that a proposed chip design implementation (either in code, or physical form) exactly matche

llama.cpp enables LLM inference in C/C++ , and release b9014 represents a build revision or commit snapshot from the llama.cpp repository on GitHub. This release would include bug fixes, feature impro

The search results show recent llama.cpp releases but not the specific b9015 release details. Based on the pattern found (b9010 is mentioned as the latest release from the search results), b9015 is li

Release b9016 is a build of llama.cpp, an LLM inference implementation in C/C++ . This build designation represents a specific intermediate version in the project's development cycle, similar to other

B9018 is the latest version of llama.cpp released on May 4, 2026. Llama.cpp is a project for LLM inference in C/C++ , providing efficient large language model execution with broad hardware support inc

b9019 is a release of llama.cpp, a C/C++ implementation for LLM inference. As a release tag from the ggml-org/llama.cpp repository, it represents a specific commit or version of the project that inclu

b9020 is a build release of llama.cpp (a C/C++ implementation of LLM inference) released on May 4, 2026, with precompiled binaries available for multiple platforms including macOS, Android, OpenEuler,

B9022 is a release of llama.cpp created on May 4, 2026, with commit d8794ee signed with GitHub's verified signature. The llama.cpp project is the main playground for developing new features for the gg