arXiv:2602.07158v1 Announce Type: new Abstract: Passive dynamic walkers are widely adopted as a mathematical model to represent biped walking. The stable locomotion of these models is limited to tilted surfaces, requiring gravitational energy. Various techniques, such as actuation through the ankle and hip joints, have been proposed to extend the applicability of these models to level ground and rough terrain with improved locomotion efficiency. However, most of these techniques rely on impulsive energy injection schemes and torsional springs, […]

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Table of Links Abstract and 1. Introduction Related Works 2.1 Traditional Index Selection Approaches 2.2 RL-based Index Selection Approaches Index Selection Problem Methodology 4.1 Formulation of the DRL Problem 4.2 Instance-Aware Deep Reinforcement Learning for Efficient Index Selection System Framework of IA2 5.1 Preprocessing Phase 5.2 RL Training and Application Phase Experiments 6.1 Experimental Setting 6.2 Experimental Results 6.3 End-to-End Performance Comparison 6.4 Key Insights Conclusion and Future Work, and References 5.1 Preprocessing Phase The preprocessing phase is […]

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arXiv:2602.07992v1 Announce Type: cross Abstract: The emergence of compositional reasoning in large language models through reinforcement learning with verifiable rewards (RLVR) has been a key driver of recent empirical successes. Despite this progress, it remains unclear which compositional problems are learnable in this setting using outcome-level feedback alone. In this work, we theoretically study the learnability of compositional problems in autoregressive models under RLVR training. We identify a quantity that we call the task-advantage ratio, a joint property […]

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https://github.com/wiltchamberian/Zeta I wrote a library to implement Alpha-zero ‘s algorithm with convolutional neural network. In image recognition it could beat pytorch in 3 times faster with similar accuracy, but it can’t play chess on boards larger than 3*3. I suspect there are some bugs there but couldnt find any. If anyone has interests, pls have a look. submitted by /u/Such-Refrigerator951 [link] [comments]

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Tool: Merge State Visualizer Bram Cohen wrote about his coherent vision for the future of version control using CRDTs, illustrated by 470 lines of Python. I fed that Python (minus comments) into Claude and asked for an explanation, then had it use Pyodide to build me an interactive UI for seeing how the algorithms work. Tags: vcs, pyodide, bram-cohen, crdt

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arXiv:2601.12227v1 Announce Type: new Abstract: Foundation models trained on electronic health records show strong performance on many clinical prediction tasks but are limited by sparse and irregular documentation. Wearable devices provide dense continuous physiological signals but lack semantic grounding. Existing methods usually model these data sources separately or combine them through late fusion. We propose a multimodal foundation model that jointly represents electronic health records and wearable data as a continuous time latent process. The model uses modality […]

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A few weeks ago I posted here asking for advice about a Dueling DDQN chess agent that completely collapsed after I pretrained it with supervised learning. Several people pointed out that the issue might be the transition from supervised learning to value-based RL, and that actor-critic methods might be a better fit. They were right. I had been treating the Q-values as logits. Using cross-entropy loss during supervised learning meant that the “correct” Q-value (the expert move) was […]

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arXiv:2603.02345v1 Announce Type: new Abstract: Infrastructure as code (IaC) tools automate cloud provisioning but verifying that deployed systems remain consistent with the IaC specifications remains challenging. Such configuration drift occurs because of bugs in the IaC specification, manual changes, or system updates. Large language model (LLM)-based agentic AI systems can automate the analysis of large volumes of telemetry data, making them suitable for the detection of configuration drift. However, existing agentic systems implicitly assume that the tools they […]

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I am currently working on an RL game where an agent has to complete several (intermediate) jobs. The environment, jobs and agent features are very rich. For almost every single action I provide a progressive reward if it shows favorable behavior (e.g. a certain sequence of jobs, timing etc.) or a negative reward to penalize undesired behavior (e.g. delays). However, I have no feel for what the right size or number is for the rewards. And I also […]

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arXiv:2604.07494v1 Announce Type: new Abstract: Context: AI coding agents route every task to a single frontier large language model (LLM), paying premium inference cost even when many tasks are routine. Objectives: We propose Triage, a framework that uses code health metrics — indicators of software maintainability — as a routing signal to assign each task to the cheapest model tier whose output passes the same verification gate as the expensive model. Methods: Triage defines three capability tiers (light, […]

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