Autonomous agents, tool use, and agentic systems
Pluribus is a memory service for agents (MCP + HTTP, Postgres-backed) that stores structured memory: constraints, decisions, patterns, an...
https://github.com/h5i-dev/awesome-ai-agent-incidents submitted by /u/Living_Impression_37 [link] [comments]
hey everyone. been lurking here for a while and wanted to share something we been building. the problem: ai coding agents are only as goo...
![[2507.16801] Decoding Translation-Related Functional Sequences in 5'UTRs Using Interpretable Deep Learning Models](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This paper presents UTR-STCNet, a novel deep learning model designed to analyze 5' untranslated regions (5'UTRs) for improved prediction ...
The paper presents a metric called Intelligence per Watt (IPW) to evaluate the efficiency of local AI models compared to centralized clou...
The paper presents Supervised Reinforcement Learning (SRL), a framework that enhances reasoning in Large Language Models (LLMs) by reform...
The paper presents a novel approach to structure learning in vine copulas using random search algorithms, outperforming traditional metho...
This study investigates the impact of AI assistants on software maintainability, revealing no significant differences in code evolution d...
The paper introduces DeepMartingale, a deep-learning framework addressing the dual formulation of optimal stopping problems, enhancing sc...
The paper presents an atlas-free brain network transformer (BNT) that improves brain network analysis by utilizing individualized brain p...
The paper presents a novel approach called Sparse Imagination for enhancing visual world model planning in robotics, improving computatio...
This article presents PathVis, a mixed-reality platform designed to enhance digital pathology workflows by integrating multimodal AI and ...
This article presents PoET-2, a multimodal retrieval-augmented protein foundation model that enhances protein function prediction and var...
This paper analyzes the interpolation error of nonlinear attention mechanisms compared to linear regression, revealing insights into thei...
The paper presents Dual-IPO, a novel framework for optimizing text-to-video generation by iteratively improving both the reward and video...
This paper introduces a framework for open vocabulary object detection that allows vision language models to identify and learn novel obj...
This paper explores the complexity of neural computation in superposition, establishing theoretical bounds for algorithms and revealing l...
This paper presents the Unbiased Sliced Wasserstein RBF kernel, a novel approach for enhancing audio captioning systems by addressing exp...
This paper presents a novel framework for one-shot learning in computer vision, utilizing Abstracted Gaussian Prototypes to enhance image...
This article introduces ReasoningMath-Plus, a benchmark designed to evaluate structural mathematical reasoning in large language models (...
The paper explores the relationship between consciousness and computational processes in machines, arguing that the timing of computation...
This paper explores the relationship between Generative Flow Networks (GFlowNets) and Markov chains, introducing a framework to control e...
This paper presents Discovered Adversarial Imitation Learning (DAIL), a novel approach to improving stability in Adversarial Imitation Le...
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