collaborators

5 papers

cs.CL2026

Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following

Qingyu Ren, Qianyu He, Powei Chang +5

Language models often struggle to follow multi-constraint instructions that are crucial for real-world applications. Existing reinforcement learning (RL) approaches suffer from dep…

cs.IR2026

What Makes an Ideal Quote? Recommending "Unexpected yet Rational" Quotations via Novelty

Bowei Zhang, Jin Xiao, Guanglei Yue +4

Quotation recommendation aims to enrich writing by suggesting quotes that complement a given context, yet existing systems mostly optimize surface-level topical relevance and ignor…

cs.AI2025

Beyond the Trade-off: Self-Supervised Reinforcement Learning for Reasoning Models' Instruction Following

Qingyu Ren, Qianyu He, Bowei Zhang +6

Reasoning models excel in complex problem solving but exhibit a concerning trade off between reasoning capabilities and instruction following abilities. Existing approaches for imp…

cs.CE2025

ChemHTS: Hierarchical Tool Stacking for Enhancing Chemical Agents

Zhucong Li, Jin Xiao, Bowei Zhang +5

Large Language Models (LLMs) have demonstrated remarkable potential in scientific research, particularly in chemistry-related tasks such as molecular design, reaction prediction, a…

cs.CL2025

QUILL: Quotation Generation Enhancement of Large Language Models

Jin Xiao, Bowei Zhang, Qianyu He +6

While Large language models (LLMs) have become excellent writing assistants, they still struggle with quotation generation. This is because they either hallucinate when providing f…