Tag: fine-tuning techniques
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OpenAI : Toward understanding and preventing misalignment generalization
Source URL: https://openai.com/index/emergent-misalignment Source: OpenAI Title: Toward understanding and preventing misalignment generalization Feedly Summary: We study how training on incorrect responses can cause broader misalignment in language models and identify an internal feature driving this behavior—one that can be reversed with minimal fine-tuning. AI Summary and Description: Yes Summary: The text discusses the potential negative…
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Slashdot: Alibaba’s ZeroSearch Teaches AI To Search Without Search Engines, Cuts Training Costs By 88%
Source URL: https://slashdot.org/story/25/05/09/0113217/alibabas-zerosearch-teaches-ai-to-search-without-search-engines-cuts-training-costs-by-88?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Alibaba’s ZeroSearch Teaches AI To Search Without Search Engines, Cuts Training Costs By 88% Feedly Summary: AI Summary and Description: Yes Summary: Alibaba Group’s “ZeroSearch” technique showcases an innovative approach that enables large language models (LLMs) to develop search capabilities without relying on external search engines, demonstrating significant cost…
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Enterprise AI Trends: Finetuning LLMs for Enterprises: Interview with Travis Addair, CTO of Predibase
Source URL: https://nextword.substack.com/p/finetuning-llms-for-enterprises-interview Source: Enterprise AI Trends Title: Finetuning LLMs for Enterprises: Interview with Travis Addair, CTO of Predibase Feedly Summary: Plus, how RFT (reinforcement finetuning) will really change the game for finetuning AI models AI Summary and Description: Yes Summary: The provided text details an in-depth discussion about advancements in fine-tuning large language models…
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Hacker News: LoRA vs. Full Fine-Tuning: An Illusion of Equivalence
Source URL: https://arxiv.org/abs/2410.21228 Source: Hacker News Title: LoRA vs. Full Fine-Tuning: An Illusion of Equivalence Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper presents a comparative study of Low-Rank Adaptation (LoRA) and full fine-tuning for large language models (LLMs). It reveals significant differences in how each method alters pre-trained models, particularly focusing…
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Hacker News: Ask HN: Recommendation for LLM-based "documentation interaction"
Source URL: https://news.ycombinator.com/item?id=41847966 Source: Hacker News Title: Ask HN: Recommendation for LLM-based "documentation interaction" Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a plan for fine-tuning a large language model (LLM) to enhance the accessibility and efficiency of documentation for a particular framework. This initiative aims to improve user experience by…
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Hacker News: LLMs know more than what they say
Source URL: https://arjunbansal.substack.com/p/llms-know-more-than-what-they-say Source: Hacker News Title: LLMs know more than what they say Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses advancements in evaluation techniques for generative AI applications, particularly focusing on reducing hallucination occurrences and improving evaluation accuracy through a method called Latent Space Readout (LSR). This approach demonstrates…