The return of BTS is a big deal. In case you were in any doubt, just look at the frenzy surrounding the South Koreans' comeback. On Saturday, the band will kick off a sold-out, 82-date world tour with a free concert in Seoul, which is expected to be attended by more than 250,000 in-person fans and will be live-streamed on Netflix to more than 190 countries. When the tour wraps up in 2027, BTS are expected to have generated more than $1billion in revenue. Some more outlandish estimates suggest they will eclipse the $2billion haul of Taylor Swift's Eras tour.

We propose to view the outcomes of the agents' dynamics as inducing a "meta-game" between the users.

Return ˆ α We show the following generalization of Proposition 2.1. Moreover, Alg. 4 has sample complexity The sample complexity is clear so we focus on the first statement. Theorem 4.5 in [MU17]) on these events as i varies and noting that Hence recalling (A.2) above, we conclude that The other direction is similar. Using (A.2) in the same way as above, we find First we analyze the expected sample complexity. Finally Alg. 4 has sample complexity We do this using Bayes' rule.

We study pure exploration with infinitely many bandit arms generated i.i.d.

Filming federal agents in public is legal, but avoiding a dangerous--even deadly--confrontation isn't guaranteed. Here's how to record ICE and CBP agents as safely as possible and have an impact. In January 2026, two Americans were killed in the act of watching Immigration and Customs Enforcement operations in Minneapolis. Renee Nicole Good was acting as a legal observer while her wife recorded the federal immigration agents they encountered. Alex Pretti was holding a phone in his hand, filming the agents who would soon take his life.

Only around 175 broadsides copies of the document are believed to exist. Breakthroughs, discoveries, and DIY tips sent six days a week. The Declaration of Independence is up for sale, but it will cost more than most of us can afford. Despite this, the edition offered by Goldin Auction originally printed and distributed so that colonists could read the Second Continental Congress' argument for separating from Great Britain in July 1776. The document is part of a collection of over 400 historic items scheduled for auction in May, and is set to coincide with the 250th anniversary of American independence .

The new designs honor the Constitution, Civil War, and more. Breakthroughs, discoveries, and DIY tips sent every weekday. While we've said goodbye to both the year 2025 and the penny, five new United States quarters will be finding their way into your pocket soon enough. The designs of each new quarter will honor the country's 250th anniversary (aka its semiquincentennial). According to a press release from the U.S. Mint, the coins "commemorate 250 years of American Liberty by reflecting our country's founding principles and honoring our Nation's history."

We introduce the MultiLang Code Parser Dataset (MLCPD), a large-scale, language-agnostic dataset unifying syntactic and structural representations of code across ten major programming languages. MLCPD contains over seven million parsed source files normalized under our proposed universal Abstract Syntax Tree (AST) schema, enabling consistent cross-language reasoning, structural learning, and multilingual software analysis. Unlike existing corpora that focus purely on token-level code or isolated parsers, MLCPD provides both hierarchical tree representations and rich metadata for every file, ensuring lossless syntactic coverage and structural uniformity. Each entry includes a normalized schema, language-level metadata, and abstracted node semantics stored in Parquet format for scalable retrieval. Empirical analyses reveal strong cross-language structural regularities-demonstrating that syntactic graphs from languages as diverse as Python, Java, and Go can be aligned under a shared schema. We release the dataset publicly on Hugging Face and the accompanying codebase on GitHub, which includes complete pipelines for dataset reproduction, grammar compilation, and a visualization tool for exploring the unified AST across languages. Together, these resources establish MLCPD as an open, reproducible foundation for future research in cross-language representation learning and program analysis.

Knowledge editing and machine unlearning are two popular approaches for large language models (LLMs) to stay up-to-date. However, the knowledge updating mechanism of LLMs remains largely unexplored due to insufficient, isolated, and small-scale evaluation. For instance, are LLMs similar to humans in modifying certain knowledge? What differs editing and unlearning as training data increases? This paper proposes KnowledgeSmith, a unified framework to systematically understand the updating mechanism of LLMs. We first cast editing and unlearning as instances of one constrained optimization problem. Then, we propose an automatic dataset generator that provides structured interventions across multiple graph levels and data scales, enabling controlled studies of how different modification strategies propagate through model knowledge. Extensive experiments demonstrate nuanced insights over knowledge propagation, plasticity scaling, consistency, and robustness. For instance, our results show that LLMs do not exhibit similar updating as humans for different levels of knowledge, and there exists consistency-capacity trade-off. We hope our findings can offer suggestions to the design of more reliable and scalable strategies. Code: https://github.com/AIFrontierLab/KnowledgeSmith.git

Return ˆ α We show the following generalization of Proposition 2.1. Moreover, Alg. 4 has sample complexity The sample complexity is clear so we focus on the first statement. Theorem 4.5 in [MU17]) on these events as i varies and noting that Hence recalling (A.2) above, we conclude that The other direction is similar. Using (A.2) in the same way as above, we find First we analyze the expected sample complexity. Finally Alg. 4 has sample complexity We do this using Bayes' rule.