For each image's list of candidate objects, we heuristically downsample to a set of "most interesting" regions by: 1) selecting the at-most k " 4 largest/most central people; 2) keeping the most central/large objects; 3) over-sampling rarer objects according to prior frequency of detection in the LVIS vocabulary; 4) limiting the number of objects of a single type per-image; and 5) downsampling overlapping region proposals to encourage broader coverage of the pixel area of the image.

OpenAI's Sam Altman apologizes for not reporting ChatGPT account of Tumbler Ridge suspect to police Altman penned a letter addressed to the community of Tumbler Ridge, two months following the mass shooting incident. Two months following the deadly shooting in Tumbler Ridge, British Columbia, OpenAI's Sam Altman has formally apologized for not informing police of the alarming ChatGPT conversations seen with the suspect's account. Before the incident, OpenAI banned the account belonging to the alleged shooter, Jesse Van Rootselaar, for violating its usage policy due to potential for real-world violence. I am deeply sorry that we did not alert law enforcement to the account that was banned in June, Altman wrote in the letter. While I know words can never be enough, I believe an apology is necessary to recognize the harm and irreversible loss your community has suffered.

Standardized and quantified evaluation of machine behaviors is a crux of understanding LLMs. In this study, we draw inspiration from psychometric studies by leveraging human personality theory as a tool for studying machine behaviors. Originating as a philosophical quest for human behaviors, the study of personality delves into how individuals differ in thinking, feeling, and behaving. Toward building and understanding human-like social machines, we are motivated to ask: Can we assess machine behaviors by leveraging human psychometric tests in a principled and quantitative manner? If so, can we induce a specific personality in LLMs? To answer these questions, we introduce the Machine Personality Inventory (MPI) tool for studying machine behaviors; MPI follows standardized personality tests, built upon the Big Five Personality Factors (Big Five) theory and personality assessment inventories.

We introduce new methods for 1) accelerating and 2) stabilizing training for large language-vision models.