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7428e6db752171d6b832c53b2ed297ab-Paper-Conference.pdf

Neural Information Processing Systems

First, we formalize the problem definition.Weintroducetheconceptof"Idon'tknow (idk) responses" and in this context, honesty necessitates that an aligned LLM provides idk responses for unknown questions and correct responses for known questions.


ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

Neural Information Processing Systems

ToolkenGPT offers the flexibility to plug in an arbitrary number of tools by expanding the set of toolkens on the fly. In addition, it improves tool use by allowing extensive demonstration data for learning the toolken embeddings.





Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation

Neural Information Processing Systems

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion and video editing. A specialized area within generative modeling is layout-to-image (L2I) generation, where predefined layouts of objects guide the generative process. In this study, we introduce a novel regional cross-attention module tailored to enrich layout-to-image generation. This module notably improves the representation of layout regions, particularly in scenarios where existing methods struggle with highly complex and detailed textual descriptions. Moreover, while current open-vocabulary L2I methods are trained in an open-set setting, their evaluations often occur in closed-set environments. To bridge this gap, we propose two metrics to assess L2I performance in open-vocabulary scenarios.


Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio

Neural Information Processing Systems

The system consumes, as input, audio signals from headset microphones and body pose, and produces, as output, a 3D sound field surrounding the transmitter's