1 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
WebSTAR: Scalable Data Synthesis for Computer Use Agents with Step-Level Filtering
Yifei He, Pranit Chawla, Yaser Souri +2
Computer use agents (CUAs) can operate real-world digital interfaces but remain difficult to train due to the high cost of graphical user interface (GUI) interaction and the scarci…
MergeBench: A Benchmark for Merging Domain-Specialized LLMs
Yifei He, Siqi Zeng, Yuzheng Hu +3
Model merging provides a scalable alternative to multi-task training by combining specialized finetuned models through parameter arithmetic, enabling efficient deployment without t…
Efficiently Editing Mixture-of-Experts Models with Compressed Experts
Yifei He, Yang Liu, Chen Liang +1
Mixture-of-Experts (MoE) models have become a key approach for scaling large language models efficiently by activating only a subset of experts during training and inference. Typic…
Task Vector Bases: A Unified and Scalable Framework for Compressed Task Arithmetic
Siqi Zeng, Yifei He, Meitong Liu +5
Task arithmetic, representing downstream tasks through linear operations on task vectors, has emerged as a simple yet powerful paradigm for transferring knowledge across diverse se…