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最新模型

ShadowPEFT Lands in Hugging Face PEFT Main, Replacing Distributed LoRA Weight Deltas with Cross-Layer State

ShadowPEFT models task adaptation as a small trainable model running alongside a frozen backbone and is now integrated with PEFT’s standard configuration, saving, and loading interfaces. Early experiments outperform LoRA and DoRA at comparable parameter counts, but additional memory usage, dual KV caches, and the lack of a stable release remain deployment trade-offs.

AI 安全

SAILS Shows Backdoor Success Depends on the Poisoned Sample Set, While Random Sampling May Underestimate Worst-Case Risk

With the model, clean data, and number of poisoned samples held constant, a new study changed only the composition of the poisoned sample set and saw attack success rates on Llama 3 8B range from 3% to 80%. SAILS trains a set-scoring model using a small number of costly fine-tuning evaluations, then selects high-risk sets from millions of candidate combinations.

最新模型

T-LoopFormer Lets Each Token Choose Its Own Recurrence Depth and Splits the KV Cache by Loop

The new architecture repeatedly applies a three-layer shared block, allowing a router to decide per token whether to exit early or continue latent reasoning. In experiments with roughly 1 billion parameters, the paper reports better latency and accuracy than a fixed-depth looped Transformer, though the approach has yet to be validated on frontier models or mainstream inference engines.

AI 安全

OpenMAIC 1.0.2 Fixes DNS Rebinding and Cloud Metadata SSRF, Blocks Classroom Overwrites

OpenMAIC’s media proxy previously resolved DNS again after validating a domain, allowing an external hostname to point to an internal network at connection time; another path permitted access to an Alibaba Cloud metadata address. Version 1.0.2 now connects using a pinned resolution result and generates classroom IDs server-side, but the changes may affect deployments that access local models over CGNAT ranges used by Tailscale and similar services.

AI 安全

MCP Tool Annotations Remain Too Limited to Support Transaction Safety, Study Catalogs Eight Types of Agentic External-Side-Effect Anomalies

A new study categorizes eight types of external-state anomalies caused by agent retries, parallel execution, and compensation, showing that a successful response from an individual tool does not guarantee consistency across the overall workflow. A survey of 98,291 MCP tools found that annotation fields are common but cannot express outcome confirmation, staged commits, compensation, or cross-call dependencies.

最新模型

Atria Dawn Preview Releases 744B MoE Weights, Trained for Long-Horizon Research Agents in Verifiable Environments

The Shanghai AI Laboratory has released Atria Dawn Preview, along with FP8 weights and inference recipes, positioning it as a full-loop agent capable of searching, coding, and running experiments. The organization claims the best reported results on five of 16 benchmarks, though model scale, test-time compute, and its in-house evaluation setup still limit comparability.