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Finetuning LLMs risks verbatim recall of copyrighted books; Liquid AI releases edge-deployable 24B MoE model

A new research paper and accompanying code repository reveal that fine-tuning large language models can inadvertently lead to verbatim recall of copyrighted material. The study, titled "Alignment Whack-a-Mole," demonstrates how models trained on specific texts can reproduce large portions of those texts verbatim. The researchers provide a pipeline for preprocessing books, fine-tuning models using APIs from OpenAI, Google (Gemini), and DeepSeek (Tinker), and evaluating the memorization capabilities. AI

Summary written by gemini-2.5-flash-lite from 3 sources. How we write summaries →

IMPACT Fine-tuning LLMs may inadvertently expose copyrighted material, necessitating careful data curation and evaluation.

RANK_REASON The cluster describes a research paper and associated code release detailing a novel finding about LLM behavior.

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COVERAGE [3]

  1. Mastodon — fosstodon.org TIER_1 · [email protected] ·

    Alignment Whack-a-Mole: Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models https:// arxiv.org/abs/2603.20957 # ai

    Alignment Whack-a-Mole: Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models https:// arxiv.org/abs/2603.20957 # ai

  2. Mastodon — mastodon.social TIER_1 · [email protected] ·

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture https://www.liquid.ai/blog/lfm2-24b-a2b # HackerNews # Tech # AI

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture https://www.liquid.ai/blog/lfm2-24b-a2b # HackerNews # Tech # AI

  3. Mastodon — mastodon.social TIER_1 · [email protected] ·

    Finetuning Activates Verbatim Recall of Copyrighted Books in LLMs https://github.com/cauchy221/Alignment-Whack-a-Mole-Code # HackerNews # Tech # AI

    Finetuning Activates Verbatim Recall of Copyrighted Books in LLMs https://github.com/cauchy221/Alignment-Whack-a-Mole-Code # HackerNews # Tech # AI