This focuses on computational approaches to understanding, processing, and generating human languages.
The paper proposes OmniPred, a framework for training language models as universal regressors over evaluation data from various real-world experiments. This approach, which uses data from Google Vizier, demonstrates that…
Continue readingPreference learning aims to align the generations of large language models (LLMs) with human preferences. Most previous work focuses on in-distribution preference learning, but this research addresses out-of-distribution (OOD) preference…
Continue readingThe study presents Daisy-TTS, a text-to-speech system that simulates a broad spectrum of emotions. It uses a prosody encoder to learn emotionally-separable prosody embedding, which acts as a proxy for…
Continue readingThis research explores the use of Haru, a tabletop social robot, for fostering positive behavior change through the Tiny Habits method. The study focuses on developing an autonomous dialogue system…
Continue readingThis paper discusses the use of Large Language Models (LLMs) to enhance the conversational abilities of social robots. The authors propose a fully automated conversation system that uses LLMs to…
Continue readingThe study investigates the performance of GPT-4 in healthcare applications. A unique prompting technique was used to evaluate the model’s confidence score before and after posing questions from the United…
Continue readingThe article presents a state-of-the-art analysis of Generative AI’s role in the construction industry. It identifies productivity challenges in design, planning, procurement, inspection, and maintenance processes. Generative AI, which can…
Continue readingThe article explores the use of Large Language Models (LLMs) for tool planning in black box settings. It introduces an approach named TOPGUN, leveraging program synthesis for black box tool…
Continue readingThe article introduces GeoEval, a comprehensive collection of geometry math problems designed to evaluate the proficiency of Large Language Models (LLMs) and Multi-Modal Models (MMs) in problem-solving. The benchmark includes…
Continue readingThe article discusses a method to reduce diagnostic errors by using Latent Dirichlet Allocation (LLMs) to identify pieces of evidence in Electronic Health Records (EHR) that show increased or decreased…
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