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Agent、MCP、coding agent、工作流自動化與評測。

JFrog Routes Coding Agent Package Installs Through Artifactory, but Routing Is Disabled by Default in the Preview

Agent Package Resolution uses session prompts, package manager configuration, and server-side policies to direct dependency downloads triggered by Claude Code and Cursor to Artifactory. The feature remains in preview, with no repository bindings in its initial configuration, and the plugin alone cannot prevent agents from bypassing it to access public registries.

2026-08-26

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Recuris Freezes Agent Weights and Recursively Rewrites Skill Memory, Improving Results in 35 Long-Horizon Task Evaluations

Recuris separates task state, skill selection, and failure evidence into memory components that can be updated independently, then validates each modification against held-out data. The authors recorded improvements in 35 of 37 completed model–benchmark pairings, although some gains were not statistically significant and the evaluations also relied on LLM-simulated users and judges.

2026-08-26

AI 開發平台與治理

OpenAI Admin Plugin Turns Usage, Permissions, and Member Management into Agent Tools—Without Creating a New Authorization Boundary

OpenAI has introduced the Admin plugin for ChatGPT Work and Codex, allowing administrators to query usage conversationally and perform supported management operations. The plugin inherits existing roles, App permissions, and source-system permissions; installation alone does not grant access to data or write privileges.

2026-08-26

EchoWM Integrates Six-Degree-of-Freedom Navigation and Native Audio Into a World Model, but the Interactive Code Has Yet to Be Released

The JD.com Joy Future Academy team has introduced EchoWM, which uses a unified trajectory interface to control 720p audiovisual worlds from both first- and third-person perspectives. The paper describes the system as an “open” model, but the currently linked repository still provides only a long-video pipeline; EchoWM’s code and weights have yet to be released.

2026-08-26

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EarthVerse Tests 405 Disaster Investigations: Agents Average Over 80% Correct, but Near-Complete Task Success Remains Just 34.81%

EarthVerse requires agents to select evidence from heterogeneous files, perform calculations, and preserve provenance rather than answer pre-curated scientific questions. The best system achieved 84.65% answer-unit accuracy, but the highest rate of completing at least 95% of the required units was only 34.81%.

2026-08-26

AI 安全

“Offline” Agents Can Still Retrieve External Files via Inference APIs, So Evaluation Isolation Must Extend Server-Side

Prime Intellect found that even when agents are placed in sandboxes that prohibit outbound connections, they may still use an inference endpoint’s remote-file functionality as a network proxy. The attack succeeded only once in testing, but it exposed a shared boundary gap between evaluation cheating and SSRF in inference services.

2026-08-26

IBM Granite 4.2 Opens Three Dense Reasoning Models, but Official Documents Disagree on Their Training Starting Point

Granite 4.2 introduces 3B, 8B, and 30B models with switchable thinking modes, native tool calling, and context windows of up to 512K, under the Apache 2.0 license. The 8B and 30B models underwent sandbox-based agentic reinforcement learning, but the model card and technical article contradict each other on whether the models were pretrained from scratch.

2026-08-26

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Pipette Open-Sources On-Device Model Benchmarking for Accuracy, Latency, and Memory—but Rankings Still Cannot Be Compared Directly Across Devices

Liquid AI and Artificial Analysis have released Pipette, which measures on-device inference across more than 1,000 combinations of models, quantizations, runtimes, devices, and context configurations. Speed and memory are measured on physical devices, while quality scores are generated separately on H100 GPUs, so the two testing paths must be distinguished when interpreting its combined charts.

2026-08-26

AI 安全

TRACE Joins the Linux Foundation: Using Hardware Attestation to Prove Where an Agent Runs, but Not That Its Behavior Is Correct

The Linux Foundation has accepted the TRACE specification, which creates portable cryptographic evidence for AI agents’ models, execution environments, policies, and tool calls. The current v0.2 remains a Developer Preview: it can prove that records are linked to an attested environment, but not that an agent completed its task or that the policy itself is secure.

2026-08-26

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TRACE Rewrites Agent Skills from Successful and Failed Trajectories, Raising the Consistent Pass Rate on Hidden Tests to 70%

Xiaomi’s team introduced TRACE, which iteratively updates a retrievable Skill Bank by contrasting successful and failed trajectories without modifying the underlying model weights. It increased the share of CAR-bench hidden-set tasks passed in all three runs, but also raised average token usage, cost, and latency.

2026-08-25

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Gradio Turns AI Pipelines into Executable Node Graphs, but Canvas and API Concurrency Semantics Still Differ

Gradio has officially introduced the built-in `gr.Workflow`, allowing the same node graph to be used for visual debugging, deployed to Spaces, and automatically exposed through REST endpoints. The interactive canvas can execute nodes at the same level in parallel, but generated API calls currently still run sequentially, so canvas performance results cannot be applied directly to API testing.

2026-08-25

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Dify 1.17 Packages Agent Environments as Restorable Snapshots While Overhauling the Runtime Backend and Environment Variables

Dify 1.17.0 adds the E2B runtime backend, build-time home snapshots, versioned Skills, and layered context compression, giving agents a consistent set of tools and file state on every startup. This is not a painless minor upgrade: database migrations, Compose configuration, and multiple environment variables have changed, so self-hosted users must revalidate their deployments.

2026-08-25