activity
20182021
most citedLearning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning

5 citations · 7 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL2021

Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation

Yuning Mao, Wenchang Ma, Deren Lei +2

Prior studies on text-to-text generation typically assume that the model could figure out what to attend to in the input and what to include in the output via seq2seq learning, wit…

cs.AI2020

Learning to Reason in Round-based Games: Multi-task Sequence Generation for Purchasing Decision Making in First-person Shooters

Yilei Zeng, Deren Lei, Beichen Li +3

Sequential reasoning is a complex human ability, with extensive previous research focusing on gaming AI in a single continuous game, round-based decision makings extending to a seq…

cs.AI20205 cited

Learning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning

Deren Lei, Gangrong Jiang, Xiaotao Gu +3

Walk-based models have shown their advantages in knowledge graph (KG) reasoning by achieving decent performance while providing interpretable decisions. However, the sparse reward…

cs.CL2019

Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization

Siyao Li, Deren Lei, Pengda Qin +1

Deep reinforcement learning (RL) has been a commonly-used strategy for the abstractive summarization task to address both the exposure bias and non-differentiable task issues. Howe…

cs.CL20192 cited

Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

Wenhan Xiong, Jiawei Wu, Deren Lei +4

Existing entity typing systems usually exploit the type hierarchy provided by knowledge base (KB) schema to model label correlations and thus improve the overall performance. Such…

cs.CL2018

Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications

Deren Lei, Zichen Sun, Yijun Xiao +1

Deep neural networks with remarkably strong generalization performances are usually over-parameterized. Despite explicit regularization strategies are used for practitioners to avo…