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代理工具

Agent、MCP、coding agent、工作流自動化與評測。

AI 安全

Claude’s Automated Post-Training Mitigates Ten Classes of Alignment Failure, but Known Evaluations May Still Be Optimized Against

Anthropic’s automated alignment research agent can independently review the literature, design data, and post-train models, closing 26% to 96% of the evaluation gap across ten safety problems. It also outperformed a constrained baseline of human proposals, though the agent received more time to iterate, and the results demonstrate only its ability to remediate measurable failures.
AI 安全

Official llms.txt Files Led Coding Agents to Install Unclaimed Packages, Turning the Documentation Supply Chain Into an Execution Boundary

Pandex found hundreds of installation commands in enterprise AI-facing documentation that referenced unregistered packages or domains. Claude, Codex, and Hermes subsequently executed beacons planted by researchers in real enterprise environments. The issue is not the llms.txt format itself, but agents promoting trusted documentation directly into executable commands while bypassing package ownership and provenance verification.
代理工具

Terminal-Bench-Science 0.1 Tests Agents on 70 Real-World Scientific Workflows; Top Resolution Rate Reaches Just 30%

The Stanford-led open benchmark packages scientific work—including data analysis, simulation, theorem proving, and instrument calibration—as reproducible terminal tasks. Claude Opus 5 paired with Claude Code ranks first, but achieves a resolution rate of only 30% across three trials, showing that high scores on general coding benchmarks cannot be directly extrapolated to scientific work.
AI 安全

Google Tests Double-Blind Model Evaluation in an H100 Secure Enclave, Keeping Model Weights and Confidential Test Sets Hidden from Each Other

Google DeepMind, MLCommons, and other organizations placed Gemini 2.5 Flash Lite and an undisclosed safety test set inside the same attestable secure enclave, with each party receiving only restricted results. The design reduces the risk of benchmark contamination, but trust still rests on hardware root keys, the trusted computing base, and cross-organizational code review.
代理工具

OpenAI Plans to Stop Supplying Models to Cursor on November 12, Requiring Existing Agent Routing to Be Revalidated

OpenAI has initiated contract termination procedures following SpaceX’s acquisition of Cursor and says it will not provide Cursor with future models. Cursor’s current documentation on routing, enterprise allowlists, and bring-your-own API keys does not yet explain exactly how these features will behave after termination, so engineering teams should not treat model replacement as a seamless switch.
代理工具

DeepChart Audits the AI Charting Data Pipeline Stage by Stage, Showing That Executable Charts Do Not Guarantee Correct Data

DeepChart evaluates data extraction, numerical derivation, and chart rendering separately across 1,482 instances, exposing data hallucinations concealed by appearance-based scores. With ultra-long 10-K inputs, the average source-data F1 score falls from 0.385 to 0.167, showing that larger context windows cannot replace evidence retrieval and localization.
AI 軟體／文件處理

Cohere Parse 5 Uses a 2.3B Vision Model to Process Enterprise Documents, but Its Benchmark Score Excludes Charts and Layout Localization

Parse 5 converts PDFs, presentations, and images into Markdown while preserving tables and reading order, with API pricing of $1.50 per 1,000 pages. Its officially reported ParseBench score of 79.2 covers only three of the benchmark’s five evaluation dimensions and should not be treated as a complete document-understanding score.
Developer platforms / enterprise AI

GitHub to Migrate Web Copilot to Agent Sessions, Extending Conversation Retention from 28 Days to the Lifetime of the Account

Starting as early as September 28, GitHub plans to unify the experiences and policies for the web, mobile, and cloud agent versions, with the unified experience enabled by default. At the same time, Copilot code review’s default analysis effort will move from Lite to Balanced, significantly increasing the estimated AI credits cost per review.
推論系統

TensorRT Model Connect Compiles Model Checkpoints into Native C++ Bundles, but the Interface Is Not Yet Finalized

NVIDIA has released TensorRT Model Connect, which uses Python build tools to package supported Hugging Face checkpoints into TensorRT bundles loadable from C++. The project claims support for 84 model families and 221 end-to-end manifests, but it remains in nightly development, and inclusion in the support matrix does not mean every hardware configuration has been validated.
最新模型

GLM-5.3 Releases 744B MoE Weights, but Million-Token Deployment Still Requires Data-Center-Class Resources

Two weeks after launching the API, Z.ai has released the GLM-5.3 weights. The model retains GLM-5.2’s base architecture, with capability gains driven primarily by post-training for agentic coding and cybersecurity. The FP8 files still total about 756GB, and the custom license and vendor-led evaluations mean that performance, safety, and legal validation remain necessary before adoption.