[Submitted on 14 May 2026 (v1), last revised 20 May 2026 (this version, v2)] · arXiv.org
Large language models (LLMs) achieve strong performance across a wide range of tasks, but remain frozen after pretraining until subsequent updates. Many real-world applications require timely, domain-specific information, motivating the need for efficient mechanisms to incorporate new knowledge. In this paper, we introduce MeMo (Memory as a Model), a modular framework that encodes new knowledge into a dedicated memory model while keeping the LLM parameters unchanged. Compared to existing methods
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Lakehouse native graph engine with git-style workflows - ModernRelay/omnigraph
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Contribute to Kappaemme-git/local-client-prospector-skill development by creating an account on GitHub.
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The Programming Language for Agents. Contribute to vercel-labs/zerolang development by creating an account on GitHub.
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The headless browser for AI agents and web scraping - h4ckf0r0day/obscura
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Browser automation, web crawling, and iOS + Android device control for AI agents. Zig-native, token-efficient CDP snapshots, HAR recording, native adb wire-protocol client, and a standalone fetcher...
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We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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usgraphics · GitHub
Invoice LaTeX template. Contribute to usgraphics/usgc-invoice development by creating an account on GitHub.
ton-blockchain.github.io
Acton is an all-in-one CLI built around Tolk — from project creation to tests, debugging, dApp integration, deployment, and verification.
Hermes Agent
Hermes Agent — a standalone terminal app and a native application for macOS, Windows, and Linux. Install it and start a conversation with the agent that grows with you.
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[Submitted on 8 May 2026] · arXiv.org
Recent byte-level language models (LMs) match the performance of token-level models without relying on subword vocabularies, yet their utility is limited by slow, byte-by-byte autoregressive generation. We address this bottleneck in the Byte Latent Transformer (BLT) through new training and generation techniques. First, we introduce BLT Diffusion (BLT-D), a new model and our fastest BLT variant, trained with an auxiliary block-wise diffusion objective alongside the standard next-byte prediction
Contributors to Wikimedia projects · Wikimedia Foundation, Inc.
In mathematics and computer algebra, automatic differentiation (auto-differentiation, autodiff, or AD), also called algorithmic differentiation, computational differentiation, and differentiation arithmetic[1][2][3][4] is a set of techniques to evaluate the partial derivative of a function specified by a computer program. Automatic differentiation enables the simultaneous computation of the numerical values of arbitrarily complex functions and their derivatives using only the function itself; no
Steven Veld · AI Futures Project
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softmax.com
An independent research lab building the science of organic alignment through multi-agent reinforcement learning.
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Codex++ tweak system for the Codex desktop app. Contribute to b-nnett/codex-plusplus development by creating an account on GitHub.
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Write HTML. Render video. Built for agents. Contribute to heygen-com/hyperframes development by creating an account on GitHub.
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[Submitted on 3 Feb 2026 (v1), last revised 29 May 2026 (this version, v2)] · arXiv.org
How do neural networks trained over sequences acquire the ability to perform structured operations, such as arithmetic, geometric, and algorithmic computation? To gain insight into this question, we introduce the sequential group composition task. In this task, networks receive a sequence of elements from a finite group encoded in a real vector space and must predict their cumulative product. This task can be order-sensitive and cannot be solved by a linear model. Our analysis isolates the roles
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