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Understand new AI research with readable explanations and links to the original papers.
What the paper is about Deep research, in which an agent searches the open web, collects evidence, and derives an answer through extended reasoning, is a pro...
ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving Autonomous vehicles (AVs) are often tested using simulation, but...
PALS: Power-Aware LLM Serving for Mixture-of-Experts Models Large language model (LLM) inference is a major driver of energy consumption in modern data cente...
AutoRPA: Efficient GUI Automation through LLM-Driven Code Synthesis from Interactions AutoRPA is a framework designed to bridge the gap between two common me...
Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G This paper proposes a fundamental shift in how cellular networks are designed, mo...
Teaching AI Through Benchmark Construction: QuestBench as a Course-Based Practice for Accountable Knowledge Work As AI tools become standard in education and...
Playing Devil's Advocate: Off-the-Shelf Persona Vectors Rival Targeted Steering for Sycophancy explores a new way to reduce "sycophancy"—the tendency of AI m...
Mind the Sim-to-Real Gap & Think Like a Scientist explores how to effectively combine pre-trained simulators with real-world experimentation.
Insights Generator: Systematic Corpus-Level Trace Diagnostics for LLM Agents Diagnosing why AI agents fail is currently a manual, inefficient process.
When Skills Don't Help: A Negative Result on Procedural Knowledge for Tool-Grounded Agents in Offensive Cybersecurity This paper investigates the effectivene...
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