183 citations · 390 across the 7 of their papers we have counts for
7 papers
Adversary-Aware DPO: Enhancing Safety Alignment in Vision Language Models via Adversarial Training
Fenghua Weng, Jian Lou, Jun Feng +2
Safety alignment is critical in pre-training large language models (LLMs) to generate responses aligned with human values and refuse harmful queries. Unlike LLM, the current safety…
Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning
Ryuichi Takanobu, Tao Zhuang, Minlie Huang +3
In this paper, we investigate the task of aggregating search results from heterogeneous sources in an E-commerce environment. First, unlike traditional aggregated web search that m…
Relation Mention Extraction from Noisy Data with Hierarchical Reinforcement Learning
Jun Feng, Minlie Huang, Yijie Zhang +2
In this paper we address a task of relation mention extraction from noisy data: extracting representative phrases for a particular relation from noisy sentences that are collected…
Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning
Jun Feng, Heng Li, Minlie Huang +4
Ranking is a fundamental and widely studied problem in scenarios such as search, advertising, and recommendation. However, joint optimization for multi-scenario ranking, which aims…
Reinforcement Learning for Relation Classification from Noisy Data
Jun Feng, Minlie Huang, Li Zhao +2
Existing relation classification methods that rely on distant supervision assume that a bag of sentences mentioning an entity pair are all describing a relation for the entity pair…
Knowlege Graph Embedding by Flexible Translation
Jun Feng, Mantong Zhou, Yu Hao +2
Knowledge graph embedding refers to projecting entities and relations in knowledge graph into continuous vector spaces. State-of-the-art methods, such as TransE, TransH, and TransR…
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks
Yuyu Zhang, Hanjun Dai, Chang Xu +5
Click prediction is one of the fundamental problems in sponsored search. Most of existing studies took advantage of machine learning approaches to predict ad click for each event o…