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cs.AI2026
Verify, Repair, Repeat, or Stop? Robust Stopping for Noisy Verify-Repair Loops in LLM Agents
Yitao Wu, Si Shen, Rui Yang +2
Verify-repair loops are a standard means for large language model (LLM) agents to correct faulty plans in code generation, mathematical reasoning, and tool use. When both the verif…
cs.AI2026
LLM-Metrics: Measuring Research Impact Through Large Language Model Memory
Si Shen, Wenhua Zhao, Danhao Zhu
Citation counts remain the dominant metric for assessing research impact, yet they suffer from well-documented limitations: temporal lag, disciplinary bias, and Matthew effects. He…
cs.AI2024
RevOrder: A Novel Method for Enhanced Arithmetic in Language Models
Si Shen, Peijun Shen, Danhao Zhu
This paper presents RevOrder, a novel technique aimed at improving arithmetic operations in large language models (LLMs) by reversing the output digits in addition, subtraction, an…