馃敩 Research Summary by Caner Hazirbas, Research Scientist at Meta and Ph.D. graduate in Computer Vision from the Technical University of Munich. [Original paper by Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark … [Read more...] about The Bias of Harmful Label Associations in Vision-Language Models
Technical Methods
Self-Improving Diffusion Models with Synthetic Data
馃敩 Research Summary by Sina Alemohammad, a PhD candidate at Rice University with a focus on the interaction between generative models and synthetic data. [Original paper by Sina Alemohammad, Ahmed Imtiaz Humayun, … [Read more...] about Self-Improving Diffusion Models with Synthetic Data
Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute Misconceptions
馃敩 Research Summary by聽Arjun Arunasalam, a 4th-year Computer Science Ph.D. student at Purdue University researching security, privacy, and trust on online platforms from a human-centered lens. [Original paper by … [Read more...] about Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute Misconceptions
LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI’s ChatGPT Plugins
馃敩 Research Summary by Umar Iqbal, an Assistant professor at Washington University in St. Louis, researching computer security and privacy. [Original paper by Umar Iqbal (Washington University in St. Louis), … [Read more...] about LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI’s ChatGPT Plugins
From Instructions to Intrinsic Human Values – A Survey of Alignment Goals for Big Models
馃敩 Research Summary by Jing Yao, a researcher at Microsoft Research Asia, working on AI value alignment, interpretability and societal AI. [Original paper by Jing Yao, Xiaoyuan Yi, Xiting Wang, Jindong Wang, and … [Read more...] about From Instructions to Intrinsic Human Values – A Survey of Alignment Goals for Big Models