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I keep seeing cool methods in which LLM agents "condense" or summarize context across steps. We worked on this in Fall 2020, somehow coining the same term used now "condensed" retrieval. It shows a very early instance of self-training language models for chains of reasoning.
This preceded autoregressive chain of thought, so reasoning here is a long chain of search queries and extracted snippets from a 5M-document corpus. The scores on HoVer are still extremely hard to match to this day via prompting or RL on modern LLMs!
Classy New Zealand news
CPO at https://t.co/BNZzlkTfVp. Founder of https://t.co/hOAmca8qLm and https://t.co/dRwgbZCSOw. Coffee-making, parenting, building, exploring: RU → CN → NZ → CL → UK → NZ → PL → UK?
RT @jxmnop: this post is complete misinformation LLMs are lossy compressors! of *training data*. LLMs losslessly compress *prompts*, int…
Root node of the web of threads: https://t.co/ifH80GcLpo
The Audubon Zoo says three African lion cubs were born Oct. 19 to mother Kali and father Arnold. Officials say the cubs are healthy and active.
Advancing the power of facts, globally 🌎
RT @jxmnop: new blog post "There Are No New Ideas In AI.... Only New Datasets" in which i summarize LLMs in exactly four breakthroughs an…
Root node of the web of threads: https://t.co/ifH80GcLpo
Florida executes record 15th inmate this year for woman's 'savagely brutal' rape and murder
The pulse of the nation in the palm of your hand.