1 citations · 1 across the 5 of their papers we have counts for
5 papers
Spoken Conversational Agents with Large Language Models
Chao-Han Huck Yang, Andreas Stolcke, Larry Heck
Spoken conversational agents are converging toward voice-native LLMs. This tutorial distills the path from cascaded ASR/NLU to end-to-end, retrieval-and vision-grounded systems. We…
Weight-of-Thought Reasoning: Exploring Neural Network Weights for Enhanced LLM Reasoning
Saif Punjwani, Larry Heck
Large language models (LLMs) have demonstrated remarkable reasoning capabilities when prompted with strategies such as Chain-of-Thought (CoT). However, these approaches focus on to…
Large Body Language Models
Saif Punjwani, Larry Heck
As virtual agents become increasingly prevalent in human-computer interaction, generating realistic and contextually appropriate gestures in real-time remains a significant challen…
Allo-AVA: A Large-Scale Multimodal Conversational AI Dataset for Allocentric Avatar Gesture Animation
Saif Punjwani, Larry Heck
The scarcity of high-quality, multimodal training data severely hinders the creation of lifelike avatar animations for conversational AI in virtual environments. Existing datasets…
Reinforcement Learning via Auxiliary Task Distillation
Abhinav Narayan Harish, Larry Heck, Josiah P. Hanna +2
We present Reinforcement Learning via Auxiliary Task Distillation (AuxDistill), a new method that enables reinforcement learning (RL) to perform long-horizon robot control problems…