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Zhuoyun Du

ACL 2026×2推理效率与系统可解释性智能体与工具强化学习与后训练
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一作贡献30
核心/参与5
方向广度10
合作网络9
1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
一作ACL 2026Poster· Natural Language Processing

Enabling Agents to Communicate Entirely in Latent Space

Zhuoyun Du · Runze Wang · Huiyu Bai · Zouying Cao · Xiaoyong Zhu · Yu Cheng · Zerui Huang (Taobao &amp · Wei Chen · Haochao Ying

摘要

While natural language is the de facto communication medium for LLM-based agents, it presents a fundamental constraint. The process of downsampling rich, internal latent states into discrete tokens inherently limits the depth and nuance of information that can be transmitted, thereby hindering co...

推理效率与系统可解释性OpenReview 项目页
作者位次 #3/7ACL 2026Findings· Findings of ACL

Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization

Shan He · Runze Wang · Zhuoyun Du · Huiyu Bai · Zouying Cao · Yu Cheng · Zerui Huang (Taobao &amp

摘要

Designing and optimizing multi-agent systems (MAS) is a complex, labor-intensive process of “Agent Engineering.” Existing automatic optimization methods, primarily focused on flat prompt tuning, lack the structural awareness to debug the intricate web of interactions in MAS. More critically, thes...

智能体与工具强化学习与后训练评测与基准OpenReview 项目页

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