Han Zhao

Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering

Junyu Dai, Xinyue Fan, Weiqin Li, et al.

JourneyFormer: Encoding Airbnb Guest Journey with Sequence Modeling

Daochen Zha, Chun How Tan, Xin Liu, et al.

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving

Xinwei Qiang, Yifan Hu, Shixuan Sun, et al.

Act While Thinking: Accelerating LLM Agents via Pattern-Aware Speculative Tool Execution

Yifan Sui, Han Zhao, Rui Ma, et al.

This paper addresses the slowness of AI agents (LLMs that use external tools) by proposing PASTE, a method that predicts and executes likely future tool calls before the LLM finishes thinking. By recognizing that agents tend to follow recurring patterns of tool usage, PASTE can execute tools speculatively while the LLM is still processing, hiding wait times and achieving 48.5% faster task completion.