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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. TOOL · arXiv cs.CL English(EN) ·

    PEFT of SLM for Telecommunications Customer Support: A Comparative Study of LoRA Configurations with Energy Consumption Analysis

    Researchers explored parameter-efficient fine-tuning (PEFT) using LoRA configurations on the Qwen2.5-3B model for telecommunications customer support. They developed a synthetic data generation method and evaluated 16 LoRA configurations, including energy consumption and LLM-as-a-judge assessments. The study found that traditional validation loss metrics did not correlate with qualitative performance, highlighting the need for more comprehensive evaluation methods. AI

    IMPACT Highlights the limitations of standard validation loss for evaluating fine-tuned models, suggesting a need for better qualitative assessment methods in domain-specific AI.

  2. RESEARCH · METR (Model Evaluation & Threat Research) 中文(ZH) · · [101 sources]

    Frontier AI Safety Regulations: A Reference Guide for AI Company Employees

    Researchers are developing new methods to attack and defend AI agents used in software reverse engineering and cybersecurity. One approach uses genetic algorithms to inject malicious prompts into AI agents, causing them to misinterpret code and bypass detection systems. Other studies focus on detecting and obfuscating these prompt injection attacks, as well as defending against multi-step trojan attacks that embed persistent control within agent workflows. Additionally, a framework called CVE-Factory automates the creation of executable vulnerability tasks for training and evaluating code security agents, showing significant improvements in models like Qwen3-32B. AI

    IMPACT New attack vectors and defense mechanisms for AI agents highlight critical security vulnerabilities in AI-powered tools.