Large language models are typically refined after pretraining using either supervised fine-tuning (SFT) or reinforcement fine-tuning (RFT), each with distinct […]
Category: AI Paper Summary
Google AI Proposes Novel Machine Learning Algorithms for Differentially Private Partition Selection
Differential privacy (DP) stands as the gold standard for protecting user information in large-scale machine learning and data analytics. A […]
Zhipu AI Unveils ComputerRL: An AI Framework Scaling End-to-End Reinforcement Learning for Computer Use Agents
In the rapidly evolving landscape of AI-driven automation, Zhipu AI has introduced ComputerRL, a groundbreaking framework designed to empower agents […]
NVIDIA AI Releases Nemotron Nano 2 AI Models: A Production-Ready Enterprise AI Model Family and 6x Faster than Similar Sized Model
NVIDIA has unveiled the Nemotron Nano 2 family, introducing a line of hybrid Mamba-Transformer large language models (LLMs) that not […]
Memp: A Task-Agnostic Framework that Elevates Procedural Memory to a Core Optimization Target in LLM-based Agent
LLM agents have become powerful enough to handle complex tasks, ranging from web research and report generation to data analysis […]
R-Zero: A Fully Autonomous AI Framework that Generates Its Own Training Data from Scratch
Large Language Models (LLMs) have revolutionized fields from natural language understanding to reasoning and code generation. However, pushing their reasoning […]
This AI Paper Introduces ReaGAN: A Graph Agentic Network That Empowers Nodes with Autonomous Planning and Global Semantic Retrieval
How can we make every node in a graph its own intelligent agent—capable of personalized reasoning, adaptive retrieval, and autonomous […]
Nebius AI Advances Open-Weight LLMs Through Reinforcement Learning for Capable SWE Agents
The landscape of software engineering automation is evolving rapidly, driven by advances in Large Language Models (LLMs). However, most approaches […]
Meet LEANN: The Tiniest Vector Database that Democratizes Personal AI with Storage-Efficient Approximate Nearest Neighbor (ANN) Search Index
Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest […]
Graph-R1: An Agentic GraphRAG Framework for Structured, Multi-Turn Reasoning with Reinforcement Learning
Introduction Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains […]