arXiv:2603.22340v1 Announce Type: new Abstract: Recent advances in Retrieval-Augmented Generation (RAG) have revolutionized knowledge-intensive tasks, yet traditional RAG methods struggle when the search space is unknown or when documents are semi-structured or structured. We introduce a novel end-to-end Graph RAG framework that leverages both Labeled Property Graph (LPG) and Resource Description Framework (RDF) architectures to overcome these limitations. Our approach enables dynamic document retrieval without the need to pre-specify the number of documents and eliminates inefficient reranking. We […]

Ver mais

arXiv:2602.03980v1 Announce Type: new Abstract: Because language is creative, any reasonable language model must generalize, deciding what to say in novel contexts by using information from similar contexts. But what about contexts that are not novel but merely infrequent? In hierarchical regression, the model’s predictions for behavior in a context are affected by observations from other similar contexts to the extent that 1) the current context is infrequent and 2) different contexts behave similarly. This is called adaptive […]

Ver mais

arXiv:2603.24629v1 Announce Type: new Abstract: Converting process sketches into executable simulation models remains a major bottleneck in process systems engineering, requiring substantial manual effort and simulator-specific expertise. Recent advances in generative AI have improved both engineering-diagram interpretation and LLM-assisted flowsheet generation, but these remain largely disconnected: diagram-understanding methods often stop at extracted graphs, while text-to-simulation workflows assume structured inputs rather than raw visual artifacts. To bridge this gap, we present an end-to-end multi-agent large language model system that […]

Ver mais

I spent 6 years doing this work manually for 100+ brands. Then I built the tool that would have replaced me. 61 seconds vs 5 business days, real output comparison, no sugarcoating. I Know What Agencies Charge For. I Used to Be the One Charging It. For 6 years, I sat in the agency chair. Performance marketing. $10M+ in managed ad spend across Meta, Google, and TikTok. Over 100 DTC brands. I know exactly what the $5,000/month retainer […]

Ver mais

Introduction Disclaimer: This article is a cross post from Pytorch Medium Blog Post. One of the most exciting advancements, that has pushed the frontier of the Artificial Intelligence (AI) in recent years, is Deep Reinforcement Learning (DRL). DRL belongs to the family of machine learning algorithms. It assumes that intelligent machines can learn from their actions similar to the way humans learn from experience. Over the recent years we could witness some impressive real-world applications of DRL. The […]

Ver mais

arXiv:2602.12296v1 Announce Type: new Abstract: This study proposes a novel adaptive traffic signal control method leveraging a Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) to optimize signal timing by integrating variable cell length and multi-channel state representation. A road partition formula consisting of the sum of logarithmic and linear functions was proposed. The state variables are a vector composed of three channels: the number of vehicles, the average speed, and space occupancy. The set of available signal […]

Ver mais

Gozzip turns your social graph into your storage network. Instead of relying on servers that decide what gets stored and served, the protocol creates bilateral storage pacts between peers within your Web of Trust. Data lives on your device and your trusted contacts’ devices, verified by cryptographic challenge-response. The architecture formalizes how human communities have always preserved information: reciprocal obligation along trust edges, bounded by Dunbar layers, propagated through gossip. Built on Nostr primitives, bridges to ActivityPub and […]

Ver mais