activity
20242026
most citedA Survey of Zero-Knowledge Proof Based Verifiable Machine Learning

7 citations · 7 across the 6 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Workflow-Localized Mechanism Learning: Attribution-Guided Repair and Knowledge Reuse for Structured Agent Skills

Zibin Lin, Shengli Zhang, Taotao Wang +3

Agent Skills package reusable procedural knowledge as external artifacts for frozen language-model agents, yet existing optimizers do not jointly resolve where a failure occurs in…

cs.AI2026

Distributed General-Purpose Agent Networks: Architecture, Key Mechanisms, and Prototypes

Shengli Zhang, Deen Ma, Zibin Lin +1

Large language models have accelerated the transition from passive conversational assistants to autonomous agents that can understand goals, plan actions, invoke tools, and execute…

cs.NI2026

ZK-AMS: Credibly Anonymous Admission for Web 3.0 Platforms via Recursive Proof Aggregation

Zibin Lin, Taotao Wang, Shengli Zhang +3

Web 3.0 platforms need an onboarding mechanism that can admit real users at scale without forcing them to reveal identity documents or pay one on-chain verification cost per user.…

cs.NI2025

Binding Agent ID: Unleashing the Power of AI Agents with accountability and credibility

Zibin Lin, Shengli Zhang, Guofu Liao +2

Autonomous AI agents lack traceable accountability mechanisms, creating a fundamental dilemma where systems must either operate as ``downgraded tools'' or risk real-world abuse. Th…

cs.CL2025

EmbedGrad: Gradient-Based Prompt Optimization in Embedding Space for Large Language Models

Xiaoming Hou, Jiquan Zhang, Zibin Lin +2

Effectively adapting powerful pretrained foundation models to diverse tasks remains a key challenge in AI deployment. Current approaches primarily follow two paradigms:discrete opt…

cs.CR20257 cited

A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning

Zhizhi Peng, Chonghe Zhao, Taotao Wang +7

Machine learning is increasingly deployed through outsourced and cloud-based pipelines, which improve accessibility but also raise concerns about computational integrity, data priv…