Weak-to-strong generalization
We present a new research direction for superalignment, together with promising initial results: can we leverage the generalization properties of deep learning to control strong models with weak supervisors?
Similar Posts
Assessing Natural Language Generation (NLG) in the Age of Large Language Models: A Comprehensive Survey and Taxonomy
The Natural Language Generation (NLG) field stands at the intersection of linguistics and artificial intelligence. It focuses on the creation of human-like text by machines. Recent advancements in Large Language Models (LLMs) have revolutionized NLG, significantly enhancing the ability of systems to generate coherent and contextually relevant text. This evolving field necessitates robust evaluation methodologies…
Seeking Speed without Loss in Large Language Models? Meet EAGLE: A Machine Learning Framework Setting New Standards for Lossless Acceleration
For LLMs, auto-regressive decoding is now considered the gold standard. Because LLMs generate output tokens individually, the procedure is time-consuming and expensive. Methods based on speculative sampling provide an answer to this problem. In the first, called the “draft” phase, LLMs are hypothesized at little cost; in the second, called the “verification” phase, all of…
Fudan University Researchers Introduce SpeechGPT-Gen: A 8B-Parameter Speech Large Language Model (SLLM) Efficient in Semantic and Perceptual Information Modeling
One of the most exciting advancements in AI and machine learning has been speech generation using Large Language Models (LLMs). While effective in various applications, the traditional methods face a significant challenge: the integration of semantic and perceptual information, often resulting in inefficiencies and redundancies. This is where SpeechGPT-Gen, a groundbreaking method introduced by researchers…
Alibaba Researchers Introduce Mobile-Agent: An Autonomous Multi-Modal Mobile Device Agent
Mobile device agents utilizing Multimodal Large Language Models (MLLM) have gained popularity due to the rapid advancements in MLLMs, showcasing notable visual comprehension capabilities. This progress has made MLLM-based agents viable for diverse applications. The emergence of mobile device agents represents a novel application, requiring these agents to operate devices based on screen content and…
Researchers from McGill University Present the Pythia 70M Model for Distilling Transformers into Long Convolution Models
The emergence of Large Language Models (LLMs) has transformed the landscape of natural language processing (NLP). The introduction of the transformer architecture marked a pivotal moment, ushering in a new era in NLP. While a universal definition for LLMs is lacking, they are generally understood as versatile machine learning models adept at simultaneously handling various…
AI News Weekly – Issue #429: Google DeepMind’s new AI models – Mar 14th 2025
ByWeb Dev
Powered by jotform.ai Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Google DeepMind’s new AI models Google DeepMind is launching two new AI models designed to help robots “perform a wider range of real-world tasks than ever before.” The first, called…
