76 citations · 128 across the 17 of their papers we have counts for
8 papers · 1 filter
PILA: Plug-and-Play Insertion for LLM-native Advertising
Zhaowei Zhang, Yuhan Fu, Yihang Zhang +6
How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recently emerged as a critical pr…
LLMs Know More Than Words: A Genre Study with Syntax, Metaphor & Phonetics
Weiye Shi, Zhaowei Zhang, Shaoheng Yan +1
Large language models (LLMs) demonstrate remarkable potential across diverse language related tasks, yet whether they capture deeper linguistic properties, such as syntactic struct…
Amulet: ReAlignment During Test Time for Personalized Preference Adaptation of LLMs
Zhaowei Zhang, Fengshuo Bai, Qizhi Chen +5
How to align large language models (LLMs) with user preferences from a static general dataset has been frequently studied. However, user preferences are usually personalized, chang…
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment
Mingzhi Wang, Chengdong Ma, Qizhi Chen +7
Self-play methods have demonstrated remarkable success in enhancing model capabilities across various domains. In the context of Reinforcement Learning from Human Feedback (RLHF),…
Efficient Model-agnostic Alignment via Bayesian Persuasion
Fengshuo Bai, Mingzhi Wang, Zhaowei Zhang +4
With recent advancements in large language models (LLMs), alignment has emerged as an effective technique for keeping LLMs consensus with human intent. Current methods primarily in…
ValueDCG: Measuring Comprehensive Human Value Understanding Ability of Language Models
Zhaowei Zhang, Fengshuo Bai, Jun Gao +1
Personal values are a crucial factor behind human decision-making. Considering that Large Language Models (LLMs) have been shown to impact human decisions significantly, it is esse…
Heterogeneous Value Alignment Evaluation for Large Language Models
Zhaowei Zhang, Ceyao Zhang, Nian Liu +5
The emergent capabilities of Large Language Models (LLMs) have made it crucial to align their values with those of humans. However, current methodologies typically attempt to assig…
Continuous Decomposition of Granularity for Neural Paraphrase Generation
Xiaodong Gu, Zhaowei Zhang, Sang-Woo Lee +2
While Transformers have had significant success in paragraph generation, they treat sentences as linear sequences of tokens and often neglect their hierarchical information. Prior…