Prospect trade-off comparison framework: Mining online reviews for consumer decision support
Extracts aspect–opinion–sentiment structures with a QLoRA-adapted Qwen model, then models compensatory consumer trade-offs for decision support.
Hi,
保持变化,保持探索,保持思考。
I am an undergraduate in Data Science and Big Data Technology at Chongqing University, originally from Danyang, Jiangsu.
My interests currently sit around Natural Language Processing, Large Language Models, Model Behavior & Evaluation, and Reliable AI Systems.
I want to pair research judgment with the ability to build: choosing worthwhile questions, then testing them carefully in research and code. I am always happy to connect.
📝 Revising our PTOC paper after a minor-revision decision from IPM.
💻 Won Provincial First Prize in the Chinese Collegiate Computing Competition (4C)!
🔍 Our cross-platform ranking paper is under review at AEI.
🏅 Received the National Scholarship!
🏆 Won First Prize in the National English Competition for College Students!
Extracts aspect–opinion–sentiment structures with a QLoRA-adapted Qwen model, then models compensatory consumer trade-offs for decision support.
Probes platform signals in review representations, removes their linear directions with LEACE, and aligns cross-platform semantics before ranking.