8 papers
Your LLM, Your Style: Behavioral Mode Axes for LLM Behavioral Control
Haoze Liu, Run Liu, Haiying Xu +6
Large language models (LLMs) increasingly act in interactive settings where their behavioral styles affect user experience, safety, and downstream decision making. Existing LLM per…
See2Think: Do Multimodal Models Really Use Intermediate Visual States?
Siyu Yan, Zhuoran Yan, Haiying Xu +10
Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether they truly rely on these vi…
DataEvolver: Self-Evolving Multi-Agent Data Construction for Text-Rich Image Generation
Siyu Yan, Yizhen Gao, Yilin Wang +2
Text-rich image generation is one of the most challenging settings in image generation, since models must simultaneously produce visually realistic images and render legible, seman…
Eliciting Trustworthiness Priors of Large Language Models via Economic Games
Siyu Yan, Lusha Zhu, Jian-Qiao Zhu
One critical aspect of building human-centered, trustworthy artificial intelligence (AI) systems is maintaining calibrated trust: appropriate reliance on AI systems outperforms bot…
A Survey of Inductive Reasoning for Large Language Models
Kedi Chen, Dezhao Ruan, Yuhao Dan +12
Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamental types, which is characterized by i…
Beyond Quality: Unlocking Diversity in Ad Headline Generation with Large Language Models
Chang Wang, Siyu Yan, Depeng Yuan +8
The generation of ad headlines plays a vital role in modern advertising, where both quality and diversity are essential to engage a broad range of audience segments. Current approa…
DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search
Zerui Yang, Yuwei Wan, Siyu Yan +4
Recent advances in large language models have demonstrated considerable potential in scientific domains such as drug repositioning. However, their effectiveness remains constrained…
AgentRM: Enhancing Agent Generalization with Reward Modeling
Yu Xia, Jingru Fan, Weize Chen +7
Existing LLM-based agents have achieved strong performance on held-in tasks, but their generalizability to unseen tasks remains poor. Hence, some recent work focus on fine-tuning t…