activity
20142025
most citedReinforcement Learning for Relation Classification from Noisy Data

183 citations · 390 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2025

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…

cs.IR2019★ 20 cited

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…

cs.CL2018★ 7 cited

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…

cs.AI2018★ 14 cited

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…

cs.IR2018★ 183 cited

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…

cs.CL2015★ 2 cited

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…