Self-Taught Optimizer (Stop): Recursively Self-Improving Code Generation (arxiv.org)

Screenshot of arxiv.org: Self-Taught Optimizer (Stop): Recursively Self-Improving Code Generation

First screen, captured 3 years ago.

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Screenshot of arxiv.org: Ladder: Self-improving LLMs through recursive problem decomposition

Ladder: Self-improving LLMs through recursive problem decomposition (arxiv.org)

339 points by fofoz 1 year ago | 103 comments

arXiv paper introducing LADDER, a framework where LLMs self-improve by recursively generating simpler problem variants, plus TTRL test-time reinforcement learning.

llm reinforcement-learning self-improvement test-time-compute

Screenshot of arxiv.org: Cautious Optimizers: Improving Training with One Line of Code

Cautious Optimizers: Improving Training with One Line of Code (arxiv.org)

46 points by tosh 1 year ago | 2 comments

Screenshot of arxiv.org: Sophia: Scalable Stochastic 2nd-Order Optimizer for Language Model Pre-Training

Sophia: Scalable Stochastic 2nd-Order Optimizer for Language Model Pre-Training (arxiv.org)

49 points by tosh 2 years ago | 2 comments

Screenshot of arxiv.org: Large Language Models for Compiler Optimization

Large Language Models for Compiler Optimization (arxiv.org)

199 points by og_kalu 3 years ago | 95 comments

Screenshot of arxiv.org: Teaching Large Language Models to Self-Debug

Teaching Large Language Models to Self-Debug (arxiv.org)

79 points by saurabh20n 3 years ago | 44 comments

Screenshot of arxiv.org: Language models as compilers: Simulating pseudocode execution

Language models as compilers: Simulating pseudocode execution (arxiv.org)

159 points by milliondreams 2 years ago | 49 comments

Looks similar

Ladder: Self-improving LLMs through recursive problem decomposition(arxiv.org)

Cautious Optimizers: Improving Training with One Line of Code(arxiv.org)

Sophia: Scalable Stochastic 2nd-Order Optimizer for Language Model Pre-Training(arxiv.org)

Large Language Models for Compiler Optimization(arxiv.org)

Teaching Large Language Models to Self-Debug(arxiv.org)

Language models as compilers: Simulating pseudocode execution(arxiv.org)