2 citations · 2 across the 4 of their papers we have counts for
3 papers · 1 filter
Efficient Item ID Generation for Large-Scale LLM-based Recommendation
Anushya Subbiah, Vikram Aggarwal, James Pine +3
Integrating product catalogs and user behavior into LLMs can enhance recommendations with broad world knowledge, but the scale of real-world item catalogs, often containing million…
Improved Estimation of Ranks for Learning Item Recommenders with Negative Sampling
Anushya Subbiah, Steffen Rendle, Vikram Aggarwal
In recommendation systems, there has been a growth in the number of recommendable items (# of movies, music, products). When the set of recommendable items is large, training and e…
Item-Language Model for Conversational Recommendation
Li Yang, Anushya Subbiah, Hardik Patel +5
Large-language Models (LLMs) have been extremely successful at tasks like complex dialogue understanding, reasoning and coding due to their emergent abilities. These emergent abili…