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20242026
most citedQ*: Improving Multi-step Reasoning for LLMs with Deliberative Planning

9 citations · 9 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

HTN-Orchestrate: A Hierarchical Task Network Framework for Multi-Agent Orchestration

Yanchen Deng, Jianguo Huang, Yao Long Teng +6

Orchestrating multiple agents on a complex task requires reconciling local subtask execution with global task planning. Dynamic dispatch approaches provide execution flexibility bu…

cs.AI2026

Prism-1: Position- and Rival-Independent Scoring for System One Models

Yao Long Teng, Jianguo Huang, Yanchen Deng +2

Given a state and a set of options, such as intents, tools or interface elements, System One decision models return a distribution over the options in one forward pass, without gen…

cs.AI2026

Consider, Then Choose: Order-Invariant Decisions in System One Models

Jianguo Huang, Yao Long Teng, Yanchen Deng +1

System One models answer typed questions in a single forward pass and promise the same answer for the same input. For choice questions, this promise fails: the answer depends on th…

cond-mat.mtrl-sci2026

AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations

Penghui Yang, Zhonghan Zhang, Yue Li +6

Density functional theory (DFT) serves as the basis for computational discovery in materials science and chemistry, yet each calculation demands extensive human effort: adjusting a…

cs.AI2026

MIND-Skill: Quality-Guaranteed Skill Generation via Multi-Agent Induction and Deduction

Yixuan Li, Mingshu Cai, Ziyang Xiao +3

Large language model (LLM) powered AI agents have emerged as a promising paradigm for autonomous problem-solving, yet they continue to struggle with complex, multi-step real-world…