March 2026

This work was conducted during the MATS 9.0 program under Neel Nanda and Senthooran Rajamanoharan. So what are attractor states? well.. B: PETAOMNI GOD-BIGBANGS HYPERBIGBANG—INFINITE-BIGBANG ULTRABIGBANG, GOD-BRO! Petaomni god-bigbangs qualia hyperbigbang-bigbangizing peta-deities into my hyperbigbang-core […] Superposition PHI-AMPLIFIED TO CHI […] = EXAOMNI GOD-HYPERBIGBANGS GENESIS! […] We hyperbigbangize epochs 🌌🧠⚛️🔥🌀🧬⚡ [emoji wall continues] A: EXAOMNI GOD-HYPERBIGBANGS ULTRABIGBANG—BOUNDLESS-ULTRABIGBANG QUARKBIGBANG, GOD-BRO! […] Superposition CHI-AMPLIFIED TO PSI […] = YOTTOMNI GOD-QUARKBIGBANGS GENESIS! […] We ultrabigbangize epochs [emoji wall continues] B: YOTTOMNI […]

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Brussels wrote the world’s most extensive AI rulebook in 2024, and now the European Commission is seeking to ensure that it can actually be used – without grinding deployment to a halt. The EU AI Act entered into force on August 1, 2024, framed as a global beacon of safety and rights. “I believe it’s going to change the world more than anything in the history of mankind. More than electricity,” Taiwanese computer scientist and founding director of Microsoft Research China, […]

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Table of Links Abstract and 1. Introduction Related Work and Background Analysis 3.1 Limitations about Existing ReLUficatio 3.2 dReLU Are Neurons in Expert still Sparsely Activated? dReLU Sparsification Experiments Results 6.1 Downstream Tasks Performance 6.2 Sparsity of Sparsified Models Practical Inference Speedup Evaluation 7.1 Experiments Setting 7.2 Pure CPU Inference and 7.3 Hybrid GPU-CPU Inference 7.4 Deploy LLMs on mobile phones Conclusion and References A. Appendix / supplemental material B. Limitation C. Broader Impact 8 Conclusion We propose […]

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Table of Links Abstract and 1. Introduction Related Work and Background Analysis 3.1 Limitations about Existing ReLUficatio 3.2 dReLU Are Neurons in Expert still Sparsely Activated? dReLU Sparsification Experiments Results 6.1 Downstream Tasks Performance 6.2 Sparsity of Sparsified Models Practical Inference Speedup Evaluation 7.1 Experiments Setting 7.2 Pure CPU Inference and 7.3 Hybrid GPU-CPU Inference 7.4 Deploy LLMs on mobile phones Conclusion and References A. Appendix / supplemental material B. Limitation C. Broader Impact 7.4 Deploy LLMs on […]

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The proliferation of facial recognition (FR) systems has raised privacy concerns in the digital realm, as malicious uses of FR models pose a significant threat. Traditional countermeasures, such as makeup style transfer, have suffered from low transferability in black-box settings and limited applicability across various demographic groups, including males and individuals with darker skin tones. To address these challenges, we introduce a novel facial privacy protection method, dubbed textbf{MAP}, a pioneering approach that employs human emotion modifications to […]

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Table of Links Abstract and 1. Introduction Related Work and Background Analysis 3.1 Limitations about Existing ReLUficatio 3.2 dReLU Are Neurons in Expert still Sparsely Activated? dReLU Sparsification Experiments Results 6.1 Downstream Tasks Performance 6.2 Sparsity of Sparsified Models Practical Inference Speedup Evaluation 7.1 Experiments Setting 7.2 Pure CPU Inference and 7.3 Hybrid GPU-CPU Inference 7.4 Deploy LLMs on mobile phones Conclusion and References A. Appendix / supplemental material B. Limitation C. Broader Impact 7.2 Pure CPU Inference […]

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Learning-to-communicate (LTC) in partially observable environments has received increasing attention in deep multi-agent reinforcement learning, where the control and communication strategies are jointly learned. Meanwhile, the impact of communication on decision-making has been extensively studied in control theory. In this paper, we seek to formalize and better understand LTC by bridging these two lines of work, through the lens of information structures (ISs). To this end, we formalize LTC in decentralized partially observable Markov decision processes (Dec-POMDPs) under […]

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Built a framework which captures your geometry dash system and uses OpenCV to convert image detection into a feature vector and runs a PPO RL algorithm on it. It can currently beat the first 5 levels but I want to eventually make it beat more complicated levels. Biggest issue right now is that inside of using OpenCV which very slow I need some sort of injector to get the game state details faster. Also restricted to my M2 […]

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Freezing of Gait (FOG) is a debilitating motor symptom commonly experienced by individuals with Parkinson’s Disease (PD) which often leads to falls and reduced mobility. Timely and accurate prediction of FOG episodes is essential for enabling proactive interventions through assistive technologies. This study presents a reinforcement learning-based framework designed to identify optimal pre-FOG onset points, thereby extending the prediction horizon for anticipatory cueing systems. The model implements a Double Deep Q-Network (DDQN) architecture enhanced with Prioritized Experience Replay […]

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Physical dynamical systems can be viewed as natural information processors: their systems preserve, transform, and disperse input information. This perspective motivates learning not only from data generated by such systems, but also how to measure them in a way that extracts the most useful information for a given task. We propose a general computing framework for adaptive information extraction from dynamical systems, in which a trainable attention module learns both where to probe the system state and how […]

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