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From the 2 of 12 linked papers with an AI index.

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cs.AI2026

Compile, Then Page: Executable SOP Programs and a Capability-Gated Runtime for Procedural LLM Agents

Chenglin Yu, Li Yin, Ying Yu +4

The paper proposes compiling standard operating procedures into executable pseudo‑code and running them with a program‑guided stack machine that pages the active frame while a larg…

cs.AI2026

The Hidden Footprint: Making Storage a First-Class Metric for LLM Agent Evaluation

Chenglin Yu, Hongquan Gui, Ying Yu +3

The paper introduces AgentFootprint, a benchmark that measures the persistent storage footprint left by large language model agents after execution, providing metrics on retention,…

cs.AI2026

InfiCoEvalChain: A Blockchain-Based Decentralized Framework for Collaborative LLM Evaluation

Yifan Yang, Jinjia Li, Kunxi Li +7

The rapid advancement of large language models (LLMs) demands increasingly reliable evaluation, yet current centralized evaluation suffers from opacity, overfitting, and hardware-i…

cs.AI2026

Canonical Intermediate Representation for LLM-based optimization problem formulation and code generation

Zhongyuan Lyu, Shuoyu Hu, Lujie Liu +2

Automatically formulating optimization models from natural language descriptions is a growing focus in operations research, yet current LLM-based approaches struggle with the compo…

cs.AI2026

InfiAgent: An Infinite-Horizon Framework for General-Purpose Autonomous Agents

Chenglin Yu, Yuchen Wang, Songmiao Wang +2

LLM agents can reason and use tools, but they often break down on long-horizon tasks due to unbounded context growth and accumulated errors. Common remedies such as context compres…

cs.AI2025

InfiAgent: Self-Evolving Pyramid Agent Framework for Infinite Scenarios

Chenglin Yu, Yang Yu, Songmiao Wang +5

Large Language Model (LLM) agents have demonstrated remarkable capabilities in organizing and executing complex tasks, and many such agents are now widely used in various applicati…