arXiv Machine Learning

FlashRT: Agent Harness for Guiding Agents to Deploy Real-Time Multimodal Applications

arXiv:2607. 18171v1 Announce Type: new Abstract: Real-time multimodal applications, including voice agents and interactive video generation, compose heterogeneous models into pipelines whose efficient deployment requires application-specific decisions about placement, streaming, and intra-model parallelism.

arXiv AI
Jun 12

M*: A Modular, Extensible, Serving System for Multimodal Models

arXiv:2606. 12688v1 Announce Type: cross Abstract: We are entering a new era of composite model architectures that integrate diverse components such as vision encoders, language backbones, diffusion and flow heads, audio codecs, action generators, and world-model predictors.

By Atindra Jha, Naomi Sagan, Keisuke Kamahori, Irmak Sivgin, Rohan Sanda, Steven Gao, Mark Horowitz, Luke Zettlemoyer, Olivia Hsu, Jure Leskovec, Baris Kasikci, Stephanie Wang
arXiv AI
Jun 30

Rehearsed Multi-Agent Live Product Demonstrations with Real-Time Voice Question Answering

arXiv:2606. 30294v1 Announce Type: new Abstract: Live product demonstrations are a recurring, high-cost activity in software organizations: a human presenter must select features, dispatch the corresponding interactions on a running application, narrate them coherently, and answer questions in real time.

By Rahul Khedar, Mayank Malhotra, Avinash Karn, Mouli V, Prakhar Mehrotra
Hugging Face Trending Papers
Jul 20

Harness Engineering for LLM-Driven GPU Kernel Generation

Large language models (LLMs) can assist GPU kernel generation, but their practical effectiveness depends on whether generated code can be reliably constrained, validated, profiled, and selected. This paper presents a harness-centered system for LLM-driven GPU kernel optimization in the MLSys 2026 FlashInfer AI Kernel Generation Contest on NVIDIA Blackwell B200 GPUs.

arXiv Machine Learning
Jul 21

ChipChat: Low-Latency Cascaded Conversational Agent in MLX

arXiv:2509. 00078v2 Announce Type: replace-cross Abstract: The emergence of large language models (LLMs) has transformed spoken dialog systems, yet the optimal architecture for real-time on-device voice agents remains an open question.

By Tatiana Likhomanenko, Richard He Bai, Zijin Gu, Zakaria Aldeneh, Shiladitya Dutta, Luke Carlson, Han Tran, Yizhe Zhang, Ruixiang Zhang, Huangjie Zheng, Navdeep Jaitly