12 results for "llm engineering"
RADIANT-LLM: an Agentic Retrieval Augmented Generation Framework for Reliable Decision Support in Safety-Critical Nuclear Engineering
Reliable decision support in nuclear engineering requires traceable, domain-grounded knowledge retrieval, yet safety and risk analysis workflows remain hampered by fragmented documentation and halluci…
LLM Prompt Engineering in Practice: CoT, Few-Shot, and System Prompt Design
LLM Prompt Engineering in Practice: CoT, Few-Shot, and System Prompt Design Stop getting...…
PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks
The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In such an attack, a malicious actor uses Augmented R…
Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis
Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges regarding time, cost, and respondent fatigue. To addr…
Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach
Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise, it remains unclear …
LEGO: An LLM Skill-Based Front-End Design Generation Platform
Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design and debugging strategies. We present LEGO, a un…
Running Local LLMs Offline on a Ten-Hour Flight
I flew from London to Google Cloud Next 2026 in Las Vegas. Ten hours with no in-flight wifi. I used the time to test how far a modern MacBook can carry engineering work on local LLMs alone. Setup A we…
OpenGame: Open Agentic Coding for Games
Game development sits at the intersection of creative design and intricate software engineering, demanding the joint orchestration of game engines, real-time loops, and tightly coupled state across ma…
Can Current Agents Close the Discovery-to-Application Gap? A Case Study in Minecraft
Discovering causal regularities and applying them to build functional systems--the discovery-to-application loop--is a hallmark of general intelligence, yet evaluating this capacity has been hindered …
Quoting OpenAI Codex base_instructions
Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user's query. — OpenAI Codex base_instruct…
ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems
Despite a century of empirical memory research, existing AI agent memory systems rely on system-engineering metaphors (virtual-memory paging, flat LLM storage, Zettelkasten notes), none integrating pr…
MarketBench: Evaluating AI Agents as Market Participants
Markets are a promising way to coordinate AI agent activity for similar reasons to those used to justify markets more broadly. In order to effectively participate in markets, agents need to have infor…