arXiv:2601.17058v1 Announce Type: new Abstract: Data preparation aims to denoise raw datasets, uncover cross-dataset relationships, and extract valuable insights from them, which is essential for a wide range of data-centric applications. Driven by (i) rising demands for application-ready data (e.g., for analytics, visualization, decision-making), (ii) increasingly powerful LLM techniques, and (iii) the emergence of infrastructures that facilitate flexible agent construction (e.g., using Databricks Unity Catalog), LLM-enhanced methods are rapidly becoming a transformative and potentially dominant paradigm for data […]

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arXiv:2602.07453v1 Announce Type: cross Abstract: Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study the feature sensitivity problem, which asks whether an ensemble is sensitive to a specified subset of features — such as protected attributes — whose manipulation can alter model predictions. Existing approaches often yield examples of sensitivity that lie far from the training distribution, limiting their interpretability and practical value. We propose a data-aware […]

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Mastering unsupervised learning opens up many avenues for a data scientist. There is so much scope in the vast expanse of unsupervised learning, yet many beginners in machine learning tend to shy away from it. I’m sure most newcomers will stick to basic clustering algorithms like K-Means clustering and hierarchical clustering. Clustering is an essential technique in machine learning and is used widely across domains and industries (think about Uber’s route optimization, Amazon’s recommendation system, Netflix’s customer segmentation, […]

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arXiv:2602.03851v1 Announce Type: new Abstract: The mastery of Hijaiyah letters is a crucial foundation for reading and comprehending the Quran, yet conventional pedagogical approaches based on repetitive memorization frequently struggle to maintain the engagement of young learners in contemporary educational contexts. This research presents the design and implementation of an innovative gamification-based methodology for Hijaiyah literacy acquisition, systematically developed through the ADDIE framework (Analysis, Design, Development, Implementation, Evaluation) to optimize student motivation, participation, and educational outcomes. The resulting […]

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Decoding from large language models (LLMs) typically relies on fixed sampling hyperparameters (e.g., temperature, top-p), despite substantial variation in task difficulty and uncertainty across prompts and individual decoding steps. We propose to learn adaptive decoding policies that dynamically select sampling strategies at inference time, conditioned on available compute resources. Rather than fine-tuning the language model itself, we introduce lightweight decoding adapters trained with reinforcement learning and verifiable terminal rewards (e.g. correctness on math and coding tasks). At the […]

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When I wrote about how Primecoin uses prime chains for proof of work, I left out a detail. To mine a new Primecoin block, you have to find a prime chain of specified length that starts with a number that is a multiple of the block header hash. According to the Primecoin whitepaper Another important property of proof-of-work for cryptocurrency is non-reusability. … To achieve this, the prime chain is linked to the block header hash by requiring […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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The promise of Artificial Intelligence has long been restricted by a single, critical challenge: connecting powerful Large Language Models (LLMs) to the messy, secure, and constantly evolving world of enterprise data and tools. Traditional methods relying on hardcoded integrations and proprietary plugins have proven to be fragile, difficult to scale, and rife with security risks. These limitations have kept AI systems locked in a “walled garden,” preventing them from becoming the truly context-aware, autonomous digital workers we envision. […]

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I have implemented dreamer but cannot get it to solve the walker2d environment. I copied and pasted much of the code from public repositories, but wrote the loss computation part myself. I’ve spent several days trying to debug the code and would really appreciate your help.. I’ve put a github link to the code. I’m suspecting the indexing might be wrong in the computation of lambda returns, but there could many other mistakes. I usually don’t post anything […]

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