Search Results for author:
Found 5 papers, 2 papers with code
RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning
In this paper, we propose RLEMMO, a Meta-Black-Box Optimization framework, which maintains a population of solutions and incorporates a reinforcement learning agent for flexibly adjusting individual-level searching strategies to match the up-to-date optimization status, hence boosting the search performance on MMOP.
InternLM2 Technical Report
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization
Compared to previous models which can also skip words, our model achieves better trade-offs between performance and efficiency.
Learning to Compose over Tree Structures via POS Tags
Recursive Neural Network (RecNN), a type of models which compose words or phrases recursively over syntactic tree structures, has been proven to have superior ability to obtain sentence representation for a variety of NLP tasks.
A Novel Framework for Recurrent Neural Networks with Enhancing Information Processing and Transmission between Units
This paper proposes a novel framework for recurrent neural networks (RNNs) inspired by the human memory models in the field of cognitive neuroscience to enhance information processing and transmission between adjacent RNNs' units.
