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cs.CL2026

ADE: Agentic Data Evolution Framework for Human-Centered Objectives

Yang Yu, Yilin Jiang, Zexuan Fei +6

Aligning large language models to human-centered objectives is difficult when targets are non-executable and context-dependent, limiting reliable verification and scalable supervis…

cs.CL2026

ELBench: A Multi-Dimensional Benchmark for Education-Facing Large Language Models

Yilin Jiang, Xiaorong Zhu, Fei Tan +9

Large language models are increasingly deployed in education as tutors, teaching assistants, and content generators. These roles place demands that ordinary question answering does…

cs.CL2026

CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Players via Proactive Engagement

Hong Qian, Yuanhao Liu, Zihan Zhou +7

While LLM-based agents excel at individual tasks, effective collaboration with realistic human partners remains challenging. Most of the existing conversation-level collaborative s…

cs.CL2026

AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment

Yixuan Wang, Yue Huang, Hong Qian +7

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…

cs.CL2026

HACHIMI: Scalable and Controllable Student Persona Generation via Orchestrated Agents

Yilin Jiang, Fei Tan, Xuanyu Yin +2

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 educa…

cs.CL2026

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

Yuan Fang, Yiming Luo, Aimin Zhou +1

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…