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Rui Mao

AAAI 2026×5ACL 2026×3ICML 2026×2KDD 2026推理社会与人本智能体与工具强化学习与后训练效率与系统
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0 一作 · 11 篇 · AAAI 2026 / ACL 2026 / ICML 2026 / KDD 2026

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2026 顶会论文

11
作者位次 #8/10ACL 2026Findings· Findings of ACL

MAXS : Meta-Adaptive Exploration with LLM Agents

Jian Zhang · Zhiyuan Wang · Zhangqi Wang · Yu He · Haoran Luo · li Yuan · Lingling Zhang · Rui Mao · Haiping Zhu (Xi&#x27 · an Jiaotong University)

摘要

Large Language Model (LLM) Agents exhibit inherent reasoning abilities through the collaboration of multiple tools.However, during agent inference, existing methods often suffer from (i) locally myopic generation, due to the absence of lookahead, and (ii) trajectory instability, where minor early...

推理效率与系统智能体与工具OpenReview 项目页
作者位次 #7/8ACL 2026Findings· Findings of ACL

P rompt- R 1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning

Wenjin Liu · Haoran Luo · Xueyuan Lin · Haoming Liu · Tiesunlong Shen · Jiapu Wang · Rui Mao · Erik Cambria

摘要

Recently, various excellent and powerful large language models (LLMs) have been utilized to solve a wide range of human problems. However, when faced with complex problems, most users are often unable to provide accurate and effective prompts to interact with LLMs, thus limiting their performance...

推理智能体与工具强化学习与后训练OpenReview 项目页
作者位次 #6/9ACL 2026Findings· Findings of ACL

L ex G enius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence

Wenjin Liu · Haoran Luo · Xin Feng · Xiang Ji · Lijuan Zhou · Rui Mao · Jiapu Wang · Shirui Pan · Erik Cambria

摘要

Legal general intelligence (GI) refers to artificial intelligence (AI) that encompasses legal understanding, reasoning, and decision-making, simulating the expertise of legal experts across domains. However, existing benchmarks are result-oriented and fail to systematically evaluate the legal int...

社会与人本评测与基准推理OpenReview 项目页

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