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Tsinghua AI Open-Sources AKV, a Cache Engineering Server for LLM Agents on SGLang

Tsinghua University and CUHK researchers open-sourced AKV, a serving system for KV cache engineering in LLM agents. Instead of summarizing old history, agents drop selected KV cache entries and keep reusing the rest. Across 3 models and 4 agent benchmarks, average cost falls 27.7%. Average task score rises 1.7 points. The code is Apache-2.0 licensed

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Nanbeige Releases Nanbeige4.3-33B, a 33B Open Agentic Coding Model

Nanbeige LLM Lab has released Nanbeige4.3-33B on Hugging Face under the Apache 2.0 license. Nanbeige4.3-33B is a 33B dense language model built for agentic coding and office-style ‘cowork’ tasks. The lab sits inside the recruitment platform BOSS Zhipin. It also published Nanbeige4.3-33B-Base for custom post-training. The model supports a 524,288-token context window. In the lab’s

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Hugging Face Releases Carbon-X, a 14B Open DNA Language Model that Brings DNA and Natural Language Together for the First Time

Hugging Face has released Carbon-X, an open DNA language model with 14.8B parameters. Carbon-X is a decoder-only model from Hugging Face Bio. It reads raw DNA in a chat and answers in English. It predicts whether mutations are benign or pathogenic, flags regulatory regions, classifies organisms and predicts next bases. The weights ship under Apache

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Researchers from Stanford and UC Berkeley Introduce TokenGate: Token-Gated Attention Makes Long-Context Prefill Up to 11.3x Faster

Stanford and UC Berkeley researchers released TokenGate, a module for long-context prefill. TokenGate learned token pruning lets an existing LLM skim its input. Only the tokens that matter get full processing. The research team reports 1.4x to 11.3x faster time-to-first-token (TTFT) with no accuracy loss. Peak prefill memory drops 1.5x to 3.4x. Code and checkpoints

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Anthropic Launches OSS Scanner, a Free AI Vulnerability Scanner

Anthropic has launched OSS Scanner, a free, opt-in vulnerability scanner for critical open-source projects. The Anthropic OSS Scanner runs the company’s strongest models, including Claude Mythos, against enrolled codebases. Reports go straight to maintainers without human review. That trade delivers faster findings, but shifts triage work onto project teams. 11 days after the October 8

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Microsoft Open-Sources Agensh: A Multi-Agent Harness for 1,024 Agents

Microsoft Research has open-sourced Agensh, a decentralized harness for large teams of coding agents. The Agensh multi-agent harness removes the central orchestrator that most agent frameworks depend on. Every worker picks its own sub-task, shares findings and merges code into a common Git repo. On ProgramBench, the team scaled the setup from 1 agent to

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Cognition Open-Sources an Agent Plugin that Helps Secure Systems against Recent Cybersecurity Threats

Cognition has released the Devin Vulnerability Fixes plugin, a free, open-source set of agent skills. It targets three critical remote code execution (RCE) advisories. They cover PHP2Shell, the Node.js October 21, 2026 security release and a CVSS 10.0 self-managed GitLab bug. The skills run in Devin and in any coding agent that reads SKILL.md files.

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Meet Anthropic’s sandbox-runtime: OS-Level Sandboxing for AI Agents, No Containers

In this article, we will discuss newly trending open sourced Anthropic’s sandbox-runtime (srt), the OS-level sandbox behind Claude Code’s sandboxed bash tool. The Anthropic sandbox-runtime limits which files a process can touch and which hosts it can reach. It does this without spinning up a container. It is also not tied to Claude Code. Your

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NVIDIA Releases Nemotron 3.5 Bolt E4B 4GB: An Open Small Language Model for Local Voice Agents, Game Characters and Robots

NVIDIA has just released Nemotron 3.5 Bolt E4B 4GB, an open small language model for fast conversational agents. It targets voice assistants, game NPCs and robot interfaces running locally on RTX, Jetson and Spark hardware. The model is post-trained from Google’s Gemma 4 E4B using reinforcement learning only. For developers, this is agent behavior in

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Kyutai CADRE: Video Autoencoders That Cut World Model Lag Below 230 ms

Kyutai has released CADRE, open causal diffusion representation autoencoders for interactive world models. The Kyutai CADRE video autoencoder targets one problem: action lag. Many world models borrow autoencoders from text-to-video generators. Those autoencoders pack many frames into one latent, so every action waits. Per the research paper, CADRE world models run at 20 fps on

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