Conversational AI

Utilizing Large Language Models (LLM) as chatbots in diverse business scenarios often presents the challenge of maintaining topic continuity. Abrupt shifts in topics can lead to poor user experiences and inefficient utilization of computational resources. In this paper, we present a topic continuity model aimed at assessing whether a response aligns with the initial conversation topic. Our model is built

While we can customize large language models (LLMs) on specific domains by finetuning using the domain specific labeled data, performance of the customized models is highly dependent on the quality of the labeled data. Obtaining high-quality labeled data for custom domains often requires considerable human effort and associated costs. However, in many cases, unlabeled data is readily available at little

Determining the precise location of customers is important for an efficient and reliable delivery experience, both for customers and delivery associates. Address text is a primary source of information provided by customers about their location. In this paper, we study the important and challenging task of matching free-form customer address text to determine if two addresses represent the same physical

Large language models (LLMs) can be prone to hallucinations —generating unreliable outputs that are unfaithful to their inputs, external facts or internally inconsistent. In this work, we address several challenges for post-hoc hallucination detection in production settings. Our pipeline for hallucination detection entails: first, producing a confidence score representing the likelihood that a generated

In recent years, Vision Language Models (VLMs) have achieved significant advancements due to the success of large language models. The common strategy for aligning vision and language models involves a two-step process: an alignment (or pretraining) stage and an instruction tuning stage. During the alignment stage, a projection module is trained to map image embeddings into the language space using a paired