10 citations · 26 across the 9 of their papers we have counts for
4 papers · 1 filter
LIGE-GR: A Smooth Leap from Ranking to Generative Recommendation in the LLM Era
Venkat Srinivas, Chenzhang He, Sam Woodmansee +64
The remarkable success of large language models (LLMs) has provided important inspiration for the next generation of recommender systems. Structurally, recommendation and language…
Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise
Bo Long, Deepak Agarwal, Jelena Markovic-Voronov +2
The Transformer is the foundational building block of modern AI, yet offers no principled handling of \emph{uncertainty}, which is prevalent in real applications: cold-start tokens…
Sampling for Quality: Training-Free Reward-Guided LLM Decoding via Sequential Monte Carlo
Jelena Markovic-Voronov, Wenhui Zhu, Bo Long +5
We introduce a principled probabilistic framework for reward-guided decoding in large language models, addressing the limitations of standard decoding methods that optimize token-l…
Parallel Matrix Factorization for Binary Response
Rajiv Khanna, Liang Zhang, Deepak Agarwal +1
Predicting user affinity to items is an important problem in applications like content optimization, computational advertising, and many more. While bilinear random effect models (…