Optimizing Training Data Allocation Between Supervised and Preference Finetuning in Large Language Models
Source: MarkTechPost Large Language Models (LLMs) face significant challenges in optimizing their post-training methods, particularly in balancing Supervised...
This AI Paper from Weco AI Introduces AIDE: A Tree-Search-Based AI Agent for Automating Machine Learning Engineering
Source: MarkTechPost The development of high-performing machine learning models remains a time-consuming and resource-intensive process. Engineers and researchers...
How AI is Transforming Journalism: The New York Times’ Approach with Echo
Source: Unite.AI Artificial Intelligence (AI) is changing how news is researched, written, and delivered. A 2023 report by...
Google’s AI Co-Scientist vs. OpenAI’s Deep Research vs. Perplexity’s Deep Research: A Comparison of AI Research Agents
Source: Unite.AI Rapid advancements in AI have brought about the emergence of AI research agents—tools designed to assist...
What are AI Agents? Demystifying Autonomous Software with a Human Touch
Source: MarkTechPost In today’s digital landscape, technology continues to advance at a steady pace. One development that has...
Moonshot AI and UCLA Researchers Release Moonlight: A 3B/16B-Parameter Mixture-of-Expert (MoE) Model Trained with 5.7T Tokens Using Muon Optimizer
Source: MarkTechPost Training large language models (LLMs) has become central to advancing artificial intelligence, yet it is not...
Fine-Tuning NVIDIA NV-Embed-v1 on Amazon Polarity Dataset Using LoRA and PEFT: A Memory-Efficient Approach with Transformers and Hugging Face
Source: MarkTechPost In this tutorial, we explore how to fine-tune NVIDIA’s NV-Embed-v1 model on the Amazon Polarity dataset...
Sony Researchers Propose TalkHier: A Novel AI Framework for LLM-MA Systems that Addresses Key Challenges in Communication and Refinement
Source: MarkTechPost LLM-based multi-agent (LLM-MA) systems enable multiple language model agents to collaborate on complex tasks by dividing...
TokenSkip: Optimizing Chain-of-Thought Reasoning in LLMs Through Controllable Token Compression
Source: MarkTechPost Large Language Models (LLMs) face significant challenges in complex reasoning tasks, despite the breakthrough advances achieved...