Knowledge Distillation of Black-Box Large Language Models (2024) (arxiv.org)

Screenshot of arxiv.org: Knowledge Distillation of Black-Box Large Language Models (2024)

First screen, captured 3 months ago.

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Screenshot of arxiv.org: A sleep-like consolidation mechanism for LLMs

A sleep-like consolidation mechanism for LLMs (arxiv.org)

178 points by juxtapose 5 months ago | 126 comments

Screenshot of arxiv.org: Unsupervised Elicitation of Language Models

Unsupervised Elicitation of Language Models (arxiv.org)

128 points by kordlessagain 1 year ago | 18 comments

Screenshot of arxiv.org: LM2: Large Memory Models

LM2: Large Memory Models (arxiv.org)

105 points by fzliu 1 year ago | 30 comments

Screenshot of arxiv.org: Large Language Models Are Neurosymbolic Reasoners

Large Language Models Are Neurosymbolic Reasoners (arxiv.org)

94 points by optimalsolver 2 years ago | 86 comments

Screenshot of arxiv.org: Embarrassingly simple self-distillation improves code generation

Embarrassingly simple self-distillation improves code generation (arxiv.org)

605 points by Anon84 6 months ago | 182 comments

arXiv paper showing that fine-tuning an LLM on its own sampled code outputs (simple self-distillation) improves code generation, e.g. Qwen3-30B on LiveCodeBench.

self-distillation code-generation llm fine-tuning

Screenshot of arxiv.org: Qwen-AgentWorld: Language World Models for General Agents

Qwen-AgentWorld: Language World Models for General Agents (arxiv.org)

175 points by ilreb 4 months ago | 47 comments

Looks similar

A sleep-like consolidation mechanism for LLMs(arxiv.org)

Unsupervised Elicitation of Language Models(arxiv.org)

LM2: Large Memory Models(arxiv.org)

Large Language Models Are Neurosymbolic Reasoners(arxiv.org)

Embarrassingly simple self-distillation improves code generation(arxiv.org)

Qwen-AgentWorld: Language World Models for General Agents(arxiv.org)