@stanfordnlp
A single direction in LLM activation space, applied as a steering vector with four different norms, can cause the language model to perform a different behavior at each norm.
This and more in a new blog post, Do Not Rely on the Linear Representation Hypothesis. (link below.)View quoted post on X
DINQ每日人才转会报道!
吴政璇（@ZhengxuanZenWu）从 Google DeepMind 加入 Meta TBD，X 简介已更新为“safety @Meta tbd”。
斯坦福计算机博士，ReFT 共同一作、pyvene 第一作者。从模型内部干预到 Agent 安全评测，他的研究关注如何理解并控制模型行为。View quoted post on X
Huge congrats to @cyruszzhou on winning the outstanding paper award at EMNLP!!View quoted post on X
Accountable AI with Grounded, Faithful, Consistent, Actionable Rationales: A Case Study in Clinical Trial Matching with VERDICT: arxiv.org/abs/2609.03366
Spotlight: Kristina Toutanova, research scientist at Google DeepMind and co-author of BERT 🌟 From a Stanford PhD with Christopher Manning to Microsoft Research to Google, Kristina's language work keeps lifting NLP. Meet Kristina: aipeoplewiki.com/people/kristin… #AI #NLP #BERTView quoted post on X
www.gatesnotes.com Unconfuse Me Ep. 5: Yejin Choi | Bill Gates In the fifth episode of his podcast, Yejin Choi joins Bill to talk about her amazing work on AI training systems and the science of artificial intelligence. in the fifth episode of his podcast, yejin choi joins bill to talk about her amazing work on ai training systems and the science of artificial intelligence. gatesnot.es/3givesd?wt.mc-… via @billgatesView quoted post on X
This is what I listen to/. @BillGates want me to share more!
