Government
Off-policy estimation with adaptively collected data: the power of online learning
Off-policy estimation: Oftentimes, one needs to estimate the linear functional based on observational data collected from a behavior policy.
DiffuPac: Contextual Mimicry in Adversarial Packets Generation via Diffusion Model
Deep Learning (DL) have significantly enhanced Network Intrusion Detection Systems (NIDS), improving the effectiveness of cybersecurity operations.
Burnt Hair and Soft Power: A Night Out With Evie Magazine
Evie is a longtime favorite of far-right. At its very first live event, the strength of the publication's politics was in the pretense that it doesn't have any. Just after 8:00 pm on Sunday night, Evie Magazine's first live event was finally getting started. The women's magazine, which was founded in 2019 and once described itself as a " conservative Cosmo," welcomed eager fans to celebrate the publication, generally, and its new issue, specifically, during New York Fashion Week at the Standard Hotel's Boom in Chelsea. Guests lined up outside, hugging fur coats around formal dresses, as hosts scanned a list for their names. One blonde woman begged for access to the VIP section; an event planner ran downstairs to tell her coworkers that someone's hair had caught on fire.
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness
Randomized smoothing is a popular certified defense against adversarial attacks.
Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach Weiyu Ma
With the continued advancement of Large Language Models (LLMs) Agents in reasoning, planning, and decision-making, benchmarks have become crucial in evaluating these skills. However, there is a notable gap in benchmarks for real-time strategic decision-making. StarCraft II (SC2), with its complex and dynamic nature, serves as an ideal setting for such evaluations. To this end, we have developed TextStarCraft II, a specialized environment for assessing LLMs in real-time strategic scenarios within SC2. Addressing the limitations of traditional Chain of Thought (CoT) methods, we introduce the Chain of Summarization (CoS) method, enhancing LLMs' capabilities in rapid and effective decision-making. Our key experiments included: 1. LLM Evaluation: Tested 10 LLMs in TextStarCraft II, most of them defeating L V5 build-in AI, showcasing effective strategy skills.
Big Tech Says Generative AI Will Save the Planet. It Doesn't Offer Much Proof
Big Tech Says Generative AI Will Save the Planet. A new report finds that of 154 specific claims about how AI will benefit the climate, just a quarter cited academic research. A third included no evidence at all. A few years ago, Ketan Joshi read a statistic about artificial intelligence and climate change that caught his eye. In late 2023, Google began claiming that AI could help cut global greenhouse gas emissions by between 5 and 10 percent by 2030.
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks
Input reduction reduces the length of the input context before feeding to downstream LLMs.
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
The CCP method finds the class-wise quantiles of non-conformity scores on calibration data.