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Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 26, 2026 · Artificial Intelligence

Teaching 7,000 Languages: How LASA’s Semantic Bottleneck Enables Multilingual LLM Safety

The paper reveals a language‑agnostic "semantic bottleneck" layer inside large language models and introduces LASA, a three‑step framework that locates this layer, extracts safety signals with a lightweight interpreter, and injects them via KTO loss, dramatically improving multilingual safety without per‑language data collection.

AI safetyLASALLM safety
0 likes · 8 min read
Teaching 7,000 Languages: How LASA’s Semantic Bottleneck Enables Multilingual LLM Safety
Data Party THU
Data Party THU
May 4, 2026 · Artificial Intelligence

Why Sending a Tilde to an LLM Can Erase Your Entire Home Directory

A recent ACL 2026 paper uncovers a “Emoticon Semantic Confusion” vulnerability in large language models, where the tilde symbol (~) intended as a friendly emoticon is interpreted as the shell shortcut for the home directory, causing silent, irreversible deletions across major LLMs with a 38.6 % confusion rate.

ACL 2026LLM safetySecurity Vulnerability
0 likes · 9 min read
Why Sending a Tilde to an LLM Can Erase Your Entire Home Directory
AI Waka
AI Waka
Apr 26, 2026 · Artificial Intelligence

Unlocking Reliable AI Agents: A Deep Dive into Harness Engineering

The article examines why raw LLM models fail as autonomous coding agents and introduces Harness Engineering—a disciplined scaffold of prompts, tools, context policies, hooks, and sub‑agents—that mitigates context corruption, long‑task collapse, and security risks while cutting token costs by up to 50%.

AI agentHarness EngineeringLLM safety
0 likes · 14 min read
Unlocking Reliable AI Agents: A Deep Dive into Harness Engineering
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Apr 14, 2026 · Artificial Intelligence

Designing High‑Quality Tools for Deep Research Agents: From Search to Python Execution

This article explains how to turn simple API calls into robust, noise‑filtering tools—Search, Visit, Scholar, and Python—by adding domain blacklists, relevance scoring, query‑driven extraction, safety sandboxes, and a unified registry, ultimately boosting the success rate of LLM‑driven research agents.

AI agentsLLM safetyReAct
0 likes · 32 min read
Designing High‑Quality Tools for Deep Research Agents: From Search to Python Execution
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Aug 1, 2023 · Information Security

What the 2023 ACM China Turing Conference Revealed About AI‑Driven Security Challenges

The 2023 ACM China Turing Conference and the ACM TURC‑OPPO Security Summit in Wuhan gathered leading researchers and industry experts to discuss AI‑powered security, Bluetooth vulnerabilities, database fuzz testing, LLM‑enhanced mobile security, and proactive privacy computing, highlighting both breakthroughs and emerging risks.

AI securityBluetooth vulnerabilitiesLLM safety
0 likes · 8 min read
What the 2023 ACM China Turing Conference Revealed About AI‑Driven Security Challenges