A nonprofit parents coalition is calling on multiple congressional committees to launch an investigation into Meta for prioritizing engagement metrics that put children's safety at risk. The call is part of a three-pronged attack campaign by the American Parents Coalition (APC), launched Thursday. It includes a letter to lawmakers with calls for investigations, a new parental notification system to help parents stay informed on issues impacting their kids at Meta and beyond, and mobile billboards at Meta D.C. and California headquarters, calling out the company for failure to adequately prioritize protecting children. APC's campaign follows an April Wall Street Journal report that included an investigation looking into how the company's metrics focus has led to potential harms for children. "This is not the first time Meta has been caught making tech available to kids that exposes them to inappropriate content," APC Executive Director Alleigh Marre said. "Parents across America should be extremely wary of their children's online activity, especially when it involves emerging technology like AI digital companions.

We introduce Aligner, a novel Parameter-Efficient Fine-Tuning (PEFT) method for aligning multi-billion-parameter-sized Large Language Models (LLMs). Aligner employs a unique design that constructs a globally shared set of tunable tokens that modify the attention of every layer. Remarkably with this method, even when using one token accounting for a mere 5,000 parameters, Aligner can still perform comparably well to state-of-the-art LLM adaptation methods like LoRA that require millions of parameters. This capacity is substantiated in both instruction following and value alignment tasks. Besides the multiple order-of-magnitude improvement in parameter efficiency, the insight Aligner provides into the internal mechanisms of LLMs is also valuable. The architectural features and efficacy of our method, in addition to our experiments demonstrate that an LLM separates its internal handling of "form" and "knowledge" in a somewhat orthogonal manner. This finding promises to motivate new research into LLM mechanism understanding and value alignment.