Ng strongly advised against diving into AI projects without foundational knowledge, calling it 'bad advice' for those not ...

Content chunking is a technique for breaking down information into smaller, focused sections that make content more scannable, comprehensible, and actionable for both human readers and AI systems. And ...

A valuable pedagogical process is the concept and application of explicit teaching, chunking, and sequence learning. According to Edwards-Groves (2012), explicit teaching can be thought of as the ...

In the paper “Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception”, I did not observe any mention of data reduction after ...

In this research, Soni and Frank investigate the network mechanisms underlying capacity limitations in working memory from a new perspective, with a focus on Visual Working Memory (VWM). The authors ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

In recent years, the field of Natural Language Processing (NLP) has seen significant advancements, particularly in Retrieval-Augmented Generation (RAG) systems. RAG combines the strengths of ...

Retrieval-augmented generation (RAG) has emerged as a prominent application in the field of natural language processing. This innovative approach involves breaking down large documents into smaller, ...