cambodia
Thailand accuses Cambodia of breaking newly signed ceasefire deal
Thailand's army has accused Cambodia of breaching a newly-signed ceasefire deal reached after weeks of deadly clashes that forced nearly one million people from their homes. In a statement, the Thai army said than more than 250 unmanned aerial vehicles (UAVs) were detected flying from the Cambodian side on Sunday night. The ceasefire took effect at noon local time (05:00 GMT) on Saturday. Both sides agreed to freeze the front lines where they are now, ban reinforcements and allow civilians living in border areas to return as soon as possible. It had been seen as a breakthrough, which came after days of talks between both countries, with diplomatic encouragement from China and the US.
- North America > United States (0.50)
- Asia > Cambodia (0.45)
- Asia > Thailand (0.38)
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- Government > Regional Government (0.49)
- Leisure & Entertainment > Sports (0.44)
- Law > Criminal Law (0.31)
Jeffrey Epstein's Yahoo Inbox Revealed
Plus: ICE deploys secretive phone surveillance tech, officials warn of Chinese surveillance tools in US highway infrastructure, and more. Right-wing internet personality and Turning Point USA cofounder Charlie Kirk was shot and killed on Wednesday during a speaking engagement at Utah Valley University in Orem, Utah. After a chaotic 24-hour manhunt, the FBI named 22-year-old Utah resident Tyler Robinson as a suspect in the murder. As polarization and political violence continues to increase in the US, a new platform from the Public Service Alliance is offering tools like data-removal services and threat monitoring to public servants who increasingly need to defend themselves and their data. Meanwhile, new research this week warned that the number of US investors putting money into invasive commercial spyware rose significantly in 2024.
- North America > United States > Utah > Utah County > Orem (0.24)
- Asia > Russia (0.15)
- Asia > North Korea (0.14)
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GeoReg: Weight-Constrained Few-Shot Regression for Socio-Economic Estimation using LLM
Ahn, Kyeongjin, Han, Sungwon, Lee, Seungeon, Ahn, Donghyun, Kim, Hyoshin, Kim, Jungwon, Kim, Jihee, Park, Sangyoon, Cha, Meeyoung
Socio-economic indicators like regional GDP, population, and education levels, are crucial to shaping policy decisions and fostering sustainable development. This research introduces GeoReg a regression model that integrates diverse data sources, including satellite imagery and web-based geospatial information, to estimate these indicators even for data-scarce regions such as developing countries. Our approach leverages the prior knowledge of large language model (LLM) to address the scarcity of labeled data, with the LLM functioning as a data engineer by extracting informative features to enable effective estimation in few-shot settings. Specifically, our model obtains contextual relationships between data features and the target indicator, categorizing their correlations as positive, negative, mixed, or irrelevant. These features are then fed into the linear estimator with tailored weight constraints for each category. To capture nonlinear patterns, the model also identifies meaningful feature interactions and integrates them, along with nonlinear transformations. Experiments across three countries at different stages of development demonstrate that our model outperforms baselines in estimating socio-economic indicators, even for low-income countries with limited data availability.
Hierarchical Memory Organization for Wikipedia Generation
Yu, Eugene J., Zhu, Dawei, Song, Yifan, Wong, Xiangyu, Zhang, Jiebin, Shi, Wenxuan, Li, Xiaoguang, Liu, Qun, Li, Sujian
Generating Wikipedia articles autonomously is a challenging task requiring the integration of accurate, comprehensive, and well-structured information from diverse sources. This paper introduces the Memory Organization-based Generation (MOG) framework, a novel approach to address these challenges by leveraging a hierarchical memory architecture. MOG extracts fine-grained memory units from web documents, recursively organizes them into a Wikipedia-style hierarchical structure, and uses this structure to guide the generation process. This ensures alignment between memory and the article outline, improving both informativeness and verifiability while minimizing hallucinations. Additionally, a citation module is implemented to enhance traceability by linking every generated sentence to specific memory units. Evaluations on our newly created WikiStart dataset demonstrate that MOG outperforms baseline methods in producing informative and reliable articles, making it particularly robust in real-world scenarios.
- Asia > Philippines (0.15)
- Asia > Malaysia (0.14)
- Asia > Singapore (0.06)
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- Leisure & Entertainment > Sports > Olympic Games (0.68)
- Consumer Products & Services > Travel (0.68)
- Information Technology > Communications > Social Media (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Large Language Model (0.70)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.46)
- Information Technology > Artificial Intelligence > Natural Language > Text Processing (0.46)
Japan and Cambodia to help countries with landmine removals
The Japanese government will announce a package of comprehensive measures to help other countries remove landmines, an informed source said Friday. Foreign Minister Yoko Kamikawa will make the announcement Saturday during her trip to Cambodia, according to the source. The aim is to utilize the know-how of Japan and the Southeast Asian country in removing mines and help other nations struggling with the issue, including Ukraine. The package will include education to avoid the risk of mines, provision of mine detectors, support for victims and the development of an artificial intelligence-powered system to identify possible mine locations. In Cambodia, a civil war continued for more than 20 years from 1970, with 4 million to 6 million mines believed to have been buried.
Khmer Semantic Search Engine (KSE): Digital Information Access and Document Retrieval
The search engine process is crucial for document content retrieval. For Khmer documents, an effective tool is needed to extract essential keywords and facilitate accurate searches. Despite the daily generation of significant Khmer content, Cambodians struggle to find necessary documents due to the lack of an effective semantic searching tool. Even Google does not deliver high accuracy for Khmer content. Semantic search engines improve search results by employing advanced algorithms to understand various content types. With the rise in Khmer digital content such as reports, articles, and social media feedback enhanced search capabilities are essential. This research proposes the first Khmer Semantic Search Engine (KSE), designed to enhance traditional Khmer search methods. Utilizing semantic matching techniques and formally annotated semantic content, our tool extracts meaningful keywords from user queries, performs precise matching, and provides the best matching offline documents and online URLs. We propose three semantic search frameworks: semantic search based on a keyword dictionary, semantic search based on ontology, and semantic search based on ranking. Additionally, we developed tools for data preparation, including document addition and manual keyword extraction. To evaluate performance, we created a ground truth dataset and addressed issues related to searching and semantic search. Our findings demonstrate that understanding search term semantics can lead to significantly more accurate results.
- Asia > Cambodia > Phnom Penh Province > Phnom Penh (0.05)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Europe > Belgium (0.04)
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Cambodian authorities burn 70M of seized illegal drugs in major crackdown
Police seized ketamine hidden inside life-size Transformer robots in Thailand. A woman who was previously caught trying to ship meth hidden in a food processing machine was trying to send the robots to Taiwan. Cambodian authorities on Friday destroyed more than seven tons of illicit drugs and the ingredients for them, as a drug-fighting official said educating people about their danger is the best way of combating the illegal trade. Some 4.1 tons of the destroyed items were drugs including heroin, marijuana, methamphetamine, ecstasy and ketamine that had been confiscated from traffickers across the country, the National Authority for Combating Drugs said. The remaining 3.2 tons were various chemicals and other ingredients used to produce illegal drugs, it said.
- Asia > Thailand (0.26)
- Asia > Taiwan (0.26)
- Asia > Cambodia > Phnom Penh Province > Phnom Penh (0.10)
- Asia > Southeast Asia (0.08)
Can AI and Machine Learning Help Park Rangers Prevent Poaching?
BRIAN KENNY: Artificial intelligence or AI for short is certainly creating a lot of buzz these days. And although it may seem like this amorphous thing that's somewhere off in our future, it's already very much in our midst. Navigation apps have turned printed maps into relics. Alexa, knows what you need from the grocery store before you do. Google Nest has the house at just the right temperature before you roll out from under the covers. And this is all great, but now you have to wonder if this intro is written by me or chat GPT. Which raises an important question.
- Asia > Vietnam (0.14)
- Asia > Cambodia (0.06)
- North America > United States > Rhode Island (0.04)
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- Government (0.95)
- Law Enforcement & Public Safety (0.68)
Computer Conservation: Lily Xu Uses Artificial Intelligence To Stop Poaching Around the World
Lily Xu knew from a young age how much the environment and conservation mattered to her. By 9 years old, she'd already decided to eat vegetarian because, as she put it, "I didn't want to hurt animals." Xu grew up believing her passions would always be separate from her professional interest in computer science. Then she became a graduate student in Milind Tambe's Teamcore Lab, and everything changed. Xu is now doing award-winning research into using machine learning and artificial intelligence to help conservation and anti-poaching efforts around the world.
- Asia > Cambodia (0.08)
- North America > United States > Rhode Island (0.05)
- North America > United States > Maryland (0.05)
- North America > United States > District of Columbia > Washington (0.05)
Interview with Lily Xu – applying machine learning to the prevention of illegal wildlife poaching
Lily Xu is a PhD student at Harvard University, applying machine learning and game theory to wildlife conservation. She is particularly focused on the prevention of illegal wildlife poaching, and she told us about this interesting, and critically important, area of research. Green security is the challenge of environmental conservation under some unknown threat. The three domains that we focus on are illegal wildlife poaching, illegal logging and illegal fishing. Across all of these settings we have an environmental challenge, which is to preserve our natural ecosystems.
- Asia > Cambodia (0.07)
- North America > United States > Rhode Island (0.04)
- Africa > Uganda (0.04)
- Law > Criminal Law (0.35)
- Education > Educational Setting (0.35)