Xiaoze Liu
Computer Science · Purdue University West Lafayette
Publications
72
Citations
770
Est. group size
—
Recurring co-author estimate
Active years
8
Publishing since 2019
This bibliographic record appears to blend work from multiple researchers sharing the name Xiaoze Liu, spanning multi-agent AI systems, large language models, knowledge graphs, and food chemistry topics such as polyphenol extraction and starch structure. The computer-science-related output focuses on how multiple AI agents or language models can communicate, share experience, and learn from each other, as well as knowledge graphs for combining different types of data (like text and images). Prospective students should note the topic list here is not well resolved (all relevance scores are 0.00), suggesting the profile mixes distinct research identities.
Publication output has grown substantially over the last decade, rising from occasional papers before 2020 to a high and sustained rate of 12-18 per year since 2023.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems
arXiv (Cornell University) · 2026
- The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems
arXiv (Cornell University) · 2026
- Mechanistic elucidation of epigallocatechin gallate binding to various starches: impacts on structural alterations, stability, and digestive properties
Food Chemistry · 2026
- Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models
arXiv (Cornell University) · 2026
- Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models
arXiv (Cornell University) · 2026
- Multi-Rollout On-Policy Distillation via Peer Successes and Failures
arXiv (Cornell University) · 2026
- Multi-Rollout On-Policy Distillation via Peer Successes and Failures
arXiv (Cornell University) · 2026
- Do Proactive Agents Really Need an LLM to Decide When to Wake and What to Anchor?
arXiv (Cornell University) · 2026
- Do Proactive Agents Really Need an LLM to Decide When to Wake and What to Anchor?
arXiv (Cornell University) · 2026
- OpenRFM: Dissecting Relational In-Context Learning
arXiv (Cornell University) · 2026
- DLLG: Dynamic Logit-Level Gating of LLM Experts
arXiv (Cornell University) · 2026
- OpenRFM: Dissecting Relational In-Context Learning
arXiv (Cornell University) · 2026
- DLLG: Dynamic Logit-Level Gating of LLM Experts
arXiv (Cornell University) · 2026
- Deep eutectic solvents-synergistic ultrasonic-assisted extraction of polyphenols from raspberry (Rubus idaeus L.): Optimization, mechanisms, and in vitro and cellular antioxidant activity
Food Chemistry · 2025
- Knowledge Graphs for Multi-modal Learning: Survey and Perspective
Information Fusion · 2025
- arXiv (Cornell University)×25
- Food Chemistry×4
- Trends in Food Science & Technology×3
- Food Chemistry X×2
- LWT×2
- Huan Sun
Computer Science · The Ohio State University
- Yu Gu
Computer Science · The Ohio State University
- Zhongwei Wan
Computer Science · The Ohio State University
- Vardaan Pahuja
Computer Science · The Ohio State University
- Xiang Deng
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile