Author

Shu-Yao Xiao

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Preprint Sep 2026

Employing the Structural Power to Achieve Supply-Demand Balanced Payment Channel Networks

Blockchain technology faces scalability challenges because transactions must be validated and recorded across the network. Payment channel networks (PCNs) improve efficiency by moving transactions off-chain and recording only critical interactions on the mainnet. However, PCNs require pre-deposited channel balances (su...

Shu-Yao Xiao, Sheng-Ling Wang, Hong-Wei Shi et al. · 0 citations

#artificial intelligence Preprint Sep 2026

When Harnesses Lose the Signal: Causal Evaluation of Recovery in LLM Agents

Large language model agents rely on external harnesses to pass information between the model and its environment and to recover from execution errors. Yet recovery is usually judged only by average task success. This hides an important tension. The same operation can rescue a failing trajectory or disrupt one that woul...

Shu-Yao Xiao, Sheng-Ling Wang, Xuan Chen et al. · 0 citations

Preprint Aug 2026

SubZero+: Memory-Efficient Adaptive Zeroth-Order LLM Fine-Tuning in Random Subspaces

Zeroth-order (ZO) optimization with SGD in random subspaces enables memory-efficient fine-tuning of large language models without backpropagation. However, high gradient estimation noise fundamentally undermines adaptive optimizers like Adam. We propose SubZero+, which achieves practical adaptive ZO optimization throug...

Zi-Ming Yu, Shu-Yao Xiao, Xingyu Zhao et al. · 0 citations

#artificial intelligence Review Sep 2026

Search Shapes Conclusions: Auditing Evidence Selection Bias in Deep Research Agents

Deep Research agents synthesize evidence into cited reports, yet a well-cited report can still reach a misleading conclusion. Citation correctness checks whether cited sources support individual claims. It does not show whether adaptive search exposed a representative view of all documents made available for evaluation...

Shu-Yao Xiao, Sheng-Ling Wang, Xuan Chen et al. · 0 citations

Preprint Sep 2026

Who Drives the Probability Game of VLMs? A Temporal Causal Drive Evaluation Framework

Results show that causal-drive trajectories provide complementary source-level diagnostics for multimodal generation and show a consistent transition from stronger early question and visual guidance toward increasing reliance on generated prefixes.

Shu-Yao Xiao, Sheng-Ling Wang, Hao-Yu Niu et al. · 0 citations

#natural language process... Preprint Aug 2026

When Errors Become Memories: Causal Pathway Tracing in Multi-Turn Memory-Augmented LLMs

A structural causal model (SCM)-based framework for cross-turn error propagation in memory-augmented LLMs is proposed, and experiments show that error influence generally decays with interaction distance, while the memory-update pathway contributes more persistent effects than question feedback.

Shu-Yao Xiao, Sheng-Ling Wang, Xuan Chen et al. · 0 citations

#machine learning Preprint Aug 2026

SubZero+: Efficient Zeroth-Order LLM Fine-Tuning via Large Learning Rates

Experiments show that SubZero+, an improved SubZero framework that improves stability in three complementary ways, consistently outperforms prior ZO baselines, enlarges the stable learning-rate range, and narrows the gap to first-order methods with minimal extra memory overhead.

Ziming Yu, Shu-Yao Xiao, Xingyu Zhao et al. · 0 citations