7 papers
Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units
Chao Hao, Zezheng Wang, Yanhua Huang +4
This paper investigates the enhancement of reasoning capabilities in language models through token-level multi-model collaboration. Our approach selects the optimal tokens from the…
Beyond Quality: Unlocking Diversity in Ad Headline Generation with Large Language Models
Chang Wang, Siyu Yan, Depeng Yuan +8
The generation of ad headlines plays a vital role in modern advertising, where both quality and diversity are essential to engage a broad range of audience segments. Current approa…
A Metric for MLLM Alignment in Large-scale Recommendation
Yubin Zhang, Yanhua Huang, Haiming Xu +6
Multimodal recommendation has emerged as a critical technique in modern recommender systems, leveraging content representations from advanced multimodal large language models (MLLM…
Towards Large-scale Generative Ranking
Yanhua Huang, Yuqi Chen, Xiong Cao +17
Generative recommendation has recently emerged as a promising paradigm in information retrieval. However, generative ranking systems are still understudied, particularly with respe…
Learning Harmonized Representations for Speculative Sampling
Lefan Zhang, Xiaodan Wang, Yanhua Huang +1
Speculative sampling is a promising approach to accelerate the decoding stage for Large Language Models (LLMs). Recent advancements that leverage target LLM's contextual informatio…
Look into the Future: Deep Contextualized Sequential Recommendation
Lei Zheng, Ning Li, Yanhuan Huang +3
Sequential recommendation aims to estimate how a user's interests evolve over time via uncovering valuable patterns from user behavior history. Many previous sequential models have…