1 citations · 3 across the 8 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.IR2026
Collaborative Memory Augmentation for Generative Recommendation
Enze Liu, Zhen Tian, Wayne Xin Zhao
Generative Recommendation (GR) has exhibited great potential by modeling item transitions as a sequence-to-sequence task. Despite the success of GR, existing frameworks primarily f…
cs.IR2026
ClawRec: A Claw-Native Recommender System
Chenghao Wu, Kesha Ou, Xiaolei Wang +8
Recommender systems have become integral to navigating the modern digital ecosystem. Yet most deployed systems remain confined within single-platform boundaries, observing localize…
cs.CR2026
Identifying AI Web Scrapers Using Canary Tokens
Steven Seiden, Triss Ren, Caroline Zhang +3
From pre-training to query-time augmentation, web-scraped data helps to improve the quality and contextual relevancy of content generated by large language models (LLMs). However,…