3 papers
cs.CL2026
Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs
Shenglai Zeng, Tianqi Zheng, Chuan Tian +10
Personalizing large language models (LLMs) to individual users requires incorporating extensive interaction histories and profiles, but input token constraints make this impractica…
cs.IR2024
AmazonQAC: A Large-Scale, Naturalistic Query Autocomplete Dataset
Dante Everaert, Rohit Patki, Tianqi Zheng +1
Query Autocomplete (QAC) is a critical feature in modern search engines, facilitating user interaction by predicting search queries based on input prefixes. Despite its widespread…
cs.CL2024
Retrieval Augmented Spelling Correction for E-Commerce Applications
Xuan Guo, Rohit Patki, Dante Everaert +1
The rapid introduction of new brand names into everyday language poses a unique challenge for e-commerce spelling correction services, which must distinguish genuine misspellings f…