most citedDecoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

math.OC2024

A Vectorized Positive Semidefinite Penalty Method for Unconstrained Binary Quadratic Programming

Xinyue Huo, Ran Gu

The unconstrained binary quadratic programming (UBQP) problem is a class of problems of significant importance in many practical applications, such as in combinatorial optimization…

cs.IR2024★ 2 cited

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Keqin Bao, Jizhi Zhang, Yang Zhang +3

Adapting Large Language Models (LLMs) for recommendation requires careful consideration of the decoding process, given the inherent differences between generating items and natural…