stp2y

arXiv:2407.19108v1 Announce Type: new Abstract: Implicit neural fields have made remarkable progress in reconstructing 3D surfaces from multiple images; however, they encounter challenges when it comes to separating individual objects within a scene. Previous work has attempted to tackle this problem by introducing a framework to train separate signed distance fields (SDFs) simultaneously for each of N objects and using a regularization term to prevent objects from overlapping. However, all of these methods require segmentation masks to be provided, which are not always readily available. We introduce our method, ObjectCarver, to tackle the problem of object separation from just click…

[Submitted on 28 Jul 2024] View a PDF of the paper titled Impact of Decoding Methods on Human Alignment of Conversational LLMs, by Shaz Furniturewala and 2 other authors View PDF Abstract:To be included into chatbot systems, Large language models (LLMs) must be aligned with human conversational conventions. However, being trained mainly on web-scraped data gives existing LLMs a voice closer to informational text than actual human speech. In this paper, we examine the effect of decoding methods on the alignment between LLM-generated and human conversations, including Beam Search, Top K Sampling, and Nucleus Sampling. We present new measures of…

Seven weeks after taking the wraps off Polaris Catalog at its annual user conference, Snowflake today announced that its metadata catalog for the Apache Iceberg table format is now available on GitHub and as a public preview on its cloud. The data warehousing giant also announced plans to merge Polaris with Project Nessie, a metadata catalog developed by Dremio for Iceberg, thereby helping to nip “catalog sprawl” in the bud. Snowflake’s unveiling of Polaris at its Data Cloud Summit in early June was a watershed moment for the company, as it marked Snowflake’s full embrace of open data formats and…

IntroductionAn organization adopting new technologies or on a modernization journey typically focuses on upcoming tools, their features and potential performance/cost improvements under ideal environments. One often overlooked aspect revolves around how an organization can effectively and efficiently assimilate those technologies. The reality is that technology adoption is influenced by business priorities, integration with other systems and technical debt. These resistances could potentially destabilize the overall project execution and efficiency.The role of a typical Professional Services organization during this technology adoption revolves around minimizing the resistance through technical consultation and change management. At Databricks Professional Services, we believe it is important…