Large Language Models (LLMs) have significantly advanced natural language processing (NLP), excelling at text generation, translation, and summarization tasks. However, their ability to engage in ...

A new AI-driven approach to tokamak plasma control offers an improved route to commercial fusion technology. Next Step Fusion ...

Hortus AI calls for constituents to reassert and defend public values before they are automated away by ever larger models.

This research endeavors to advance peak load forecasting strategies and demand response optimization at the microgrid level, thereby enhancing grid reliability through the application of Deep ...

By reinforcement fine-tuning these rewards, CollabLLM goes beyond responding to user requests, and actively uncovers user intent and offers insightful suggestions-a key step towards more ...

Abstract: Vertical federated learning (VFL) is an emerging paradigm well-suitable ... We design two types of spy attacks tailored for scenarios where the attacker either takes an active or passive ...

“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...

Reinforcement learning is a subset of machine learning where agents learn to make decisions by interacting with their environment and receiving rewards or penalties based on their actions. Unlike ...

DeepSeek challenged this assumption by skipping SFT entirely, opting instead to rely on reinforcement learning (RL) to train the model. This bold move forced DeepSeek-R1 to develop independent ...

Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the ...