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20222025
most citedDUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization

42 citations · 48 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CL2025

InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion

Yuanyi Wang, Zhaoyi Yan, Yiming Zhang +4

Recent advances in large language models (LLMs) have intensified efforts to fuse heterogeneous open-source models into a unified system that inherits their complementary strengths.…

cs.LG2025

InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models

Yanggan Gu, Yuanyi Wang, Zhaoyi Yan +4

Model fusion combines multiple Large Language Models (LLMs) with different strengths into a more powerful, integrated model through lightweight training methods. Existing works on…

cs.AI2025★ 1 cited

EcoAgent: An Efficient Device-Cloud Collaborative Multi-Agent Framework for Mobile Automation

Biao Yi, Xavier Hu, Yurun Chen +3

To tackle increasingly complex tasks, recent research on mobile agents has shifted towards multi-agent collaboration. Current mobile multi-agent systems are primarily deployed in t…

cs.AI2025

InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners

Yuhang Liu, Pengxiang Li, Congkai Xie +5

Multimodal Large Language Models (MLLMs) have powered Graphical User Interface (GUI) Agents, showing promise in automating tasks on computing devices. Recent works have begun explo…

cs.CL2025

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion

Zhaoyi Yan, Yiming Zhang, Baoyi He +7

We introduce InfiFusion, an efficient training pipeline designed to integrate multiple domain-specialized Large Language Models (LLMs) into a single pivot model, effectively harnes…

cs.AI2025

InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and Reflection

Yuhang Liu, Pengxiang Li, Zishu Wei +7

Graphical User Interface (GUI) Agents, powered by multimodal large language models (MLLMs), have shown great potential for task automation on computing devices such as computers an…