4 papers
Adapting Generative Recommenders for Multi-Turn Interaction
Yu-Chen Den, Zhi Rui Tam, Yung-Yu Shih +4
Generative recommenders decode items from a user's interaction history, but offer no way for users to correct a recommendation that misses their current intent. Adding conversation…
RepICL: Reusable In-Context Prediction Across Heterogeneous Representation Spaces
Yu-Hsiang Liu, Kuan-Yu Chen, Chih-Sheng Chen +3
Frozen representations are widely reused for downstream classification, yet each new task typically requires fitting a new predictor. We ask whether the few-shot prediction procedu…
BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification
Yi-Siang Wang, Kuan-Yu Chen, Yu-Chen Den +1
Large language models (LLMs) have recently been adapted to tabular prediction by serializing structured features into natural language, but their performance in low-data regimes re…
ICICLE: Expanding Retrieval with In-Context Documents
Yu-Chen Den, Yung-Yu Shih, Zhi Rui Tam +4
Generative retrieval (GR) maps queries directly to document identifiers (docids) using parametric knowledge, However, this design makes corpus expansion costly: adding new document…