Center for AI Safety (CAIS) — publication: Representation Engineering: A Top-Down Approach to AI Transparency — proposes methods to read and control LLM internal representations for safety
1 → confirmed
Our claim
entire record- Subject
- Center for AI Safety (CAIS)
- Value
- Representation Engineering: A Top-Down Approach to AI Transparency — proposes methods to read and control LLM internal representations for safety
- As Of
- October 2023
- Notes
- By Zou, Phan, Chen, Campbell, Guo, Ren, Pan, Yin, Mazeika, Dombrowski, Goel, Li, Byun, Wang, Mallen, Basart, Koyejo, Song, Li, Hendrycks
Source evidence
1 src · 1 checkNoteThe source directly confirms all elements of the claim: (1) The publication is 'Representation Engineering: A Top-Down Approach to AI Transparency'; (2) It is authored by researchers affiliated with Center for AI Safety (Andy Zou, Long Phan, Sarah Chen, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Zifan Wang, Steven Basart, Dan Hendrycks are all listed with CAIS affiliation); (3) The paper proposes methods to 'read and control' LLM internal representations (explicitly discussed in Sections 3.1 and 3.2 on 'Representation Reading' and 'Representation Control'); (4) These methods are framed for safety purposes (abstract mentions 'safety-relevant problems'); (5) The arxiv date 2310.01405 corresponds to October 2023 (matching the 'as of 2023-10' temporal qualifier). All author names in the claim match those listed in the source.