3 accepted papers
Large language models (LLMs) have recently emerged as a promising tool for automating robot design from high-level specifications, yet they remain ineffective for robots operating under complex physical interactions. This limitation stems from the gap between language-based reasoning and the physica…
Large language models (LLMs) increasingly rely on Chain-of-Thought (CoT) prompting to improve problem-solving and provide seemingly transparent explanations. However, growing evidence shows that CoT often fail to faithfully represent the underlying reasoning process, raising concerns about their rel…
Despite recent progress, machine learning (ML) models for open-domain audio generation need to catch up to generative models for image, text, speech, and music. The lack of massive open-domain audio datasets is the main reason for this performance gap; we overcome this challenge through a novel data…