4 papers
POPI: Personalizing LLMs via Optimized Natural Language Preference Inference
Yizhuo Chen, Xin Liu, Ruijie Wang +7
Large language models (LLMs) are typically aligned with population-level preferences, despite substantial variation across individual users. We introduce POPI, a user-level persona…
SPARQL-LLM: Real-Time SPARQL Query Generation from Natural Language Questions
Panayiotis Smeros, Vincent Emonet, Ruijie Wang +2
The advent of large language models is contributing to the emergence of novel approaches that promise to better tackle the challenge of generating structured queries, such as SPARQ…
Aligning Large Language Models with Implicit Preferences from User-Generated Content
Zhaoxuan Tan, Zheng Li, Tianyi Liu +10
Learning from preference feedback is essential for aligning large language models (LLMs) with human values and improving the quality of generated responses. However, existing prefe…
Multimodal Instruction Tuning with Hybrid State Space Models
Jianing Zhou, Han Li, Shuai Zhang +5
Handling lengthy context is crucial for enhancing the recognition and understanding capabilities of multimodal large language models (MLLMs) in applications such as processing high…