6 papers
Kairos: A Scalable Serving System for Physical AI
Yinwei Dai, Ganesh Ananthanarayanan, Landon Cox +3
Physical AI is experiencing rapid growth with frontier foundation models increasing its capabilities across general environments. Physical AI tasks are characterized by inference p…
Geometry Guided Self-Consistency for Physical AI
Yinwei Dai, Zhuofu Chen, Lijie Yang +1
State-of-the-art physical AI models generate a chunk of actions per inference through diffusion or flow matching, iteratively refining an initial noise sample into an action trajec…
Slipstream: Trajectory-Grounded Compaction Validation for Long-Horizon Agents
Zhuofu Chen, Rui Pan, Yinwei Dai +1
To cope with the large contexts that long-horizon LLM agents produce, modern frameworks increasingly rely on compaction -- invoking an LLM to rewrite the accumulated trajectory int…
Aragog: Just-in-Time Model Routing for Scalable Serving of Agentic Workflows
Yinwei Dai, Zhuofu Chen, Anand Iyer +1
Agentic workflows have emerged as a powerful paradigm for solving complex, multi-stage tasks, but serving them at scale is computationally expensive given the many LLM inferences t…
SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
Rui Pan, Yinwei Dai, Zhihao Zhang +3
Recent advances in inference-time compute have significantly improved performance on complex tasks by generating long chains of thought (CoTs) using Large Reasoning Models (LRMs).…
Legilimens: Performant Video Analytics on the System-on-Chip Edge
Murali Ramanujam, Yinwei Dai, Kyle Jamieson +1
Continually retraining models has emerged as a primary technique to enable high-accuracy video analytics on edge devices. Yet, existing systems employ such adaptation by relying on…