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Aimin Zhou

ACL 2026×4AAAI 2026CVPR 2026ICML 2026KDD 2026评测与基准社会与人本多模态推理智能体与工具
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合作网络12
0 一作 · 8 篇 · ACL 2026 / AAAI 2026 / CVPR 2026 / ICML 2026 / KDD 2026

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2026 顶会论文

8
作者位次 #9/10ACL 2026Poster· Natural Language Processing

A lpha C ontext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment

Yixuan Wang · Yue Huang · Hong Qian · Yunzhao Wei · Yifei Ding · Wenkai Wang · Zhi Liu · Zhongjing Huang · Aimin Zhou · Jiajun Guo

摘要

Creativity has become a core competence in the era of LLMs and human–AI collaboration, underpinning innovation in real-world problem solving. Crucially, the systematic improvement of creativity necessitates scientifically valid assessment instruments. Psychometric research recognizes context-base...

社会与人本推理评测与基准OpenReview 项目页
作者位次 #4/6ACL 2026Findings· Findings of ACL

SCMAPR : Self-Correcting Multi-Agent Prompt Refinement for Complex-Scenario Text-to-Video Generation

Chengyi Yang · Pengzhen Li · Jiayin Qi · Aimin Zhou · Ji Wu · Ji Liu

摘要

Text-to-Video (T2V) generation has benefited from recent advances in diffusion models, yet current systems still struggle under complex scenarios, which are generally exacerbated by the ambiguity and underspecification of text prompts. In this work, we formulate complex-scenario prompt refinement...

智能体与工具多模态评测与基准OpenReview 项目页
作者位次 #3/4ACL 2026Findings· Findings of ACL

Reverse Constitutional AI : A Framework for Controllable Toxic Data Generation via Probability-Clamped RLAIF

Yuan Fang · Yiming Luo · Aimin Zhou · Fei Tan

摘要

Ensuring the safety of large language models (LLMs) requires robust red teaming, yet the systematic synthesis of high-quality toxic data remains under-explored. We propose Reverse Constitutional AI (R-CAI), a framework for automated and controllable adversarial data generation that moves beyond i...

安全对齐与偏好多模态OpenReview 项目页
作者位次 #5/5ACL 2026Findings· Findings of ACL

HACHIMI : Scalable and Controllable Student Persona Generation via Orchestrated Agents

Yilin Jiang · Fei Tan · Xuanyu Yin · Leng Jing · Aimin Zhou

摘要

Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles with limited control over educational theory and population distributions. We formalize this as Theory-Aligned and Distribution-Controllable Persona...

社会与人本推理智能体与工具OpenReview 项目页

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