3 papers
cs.LG2026
From Tokenizer Bias to Backbone Capability: A Controlled Study of LLMs for Time Series Forecasting
Xinyu Zhang, Shanshan Feng, Xutao Li +3
Using pre-trained large language models (LLMs) as a backbone for time series prediction has recently attracted growing research interest. Existing approaches typically split time s…
cs.IR2025
Efficient Model-Agnostic Continual Learning for Next POI Recommendation
Chenhao Wang, Shanshan Feng, Lisi Chen +2
Next point-of-interest (POI) recommendation improves personalized location-based services by predicting users' next destinations based on their historical check-ins. However, most…
cs.CL2025
LLMs can Find Mathematical Reasoning Mistakes by Pedagogical Chain-of-Thought
Zhuoxuan Jiang, Haoyuan Peng, Shanshan Feng +2
Self-correction is emerging as a promising approach to mitigate the issue of hallucination in Large Language Models (LLMs). To facilitate effective self-correction, recent research…