activity
20192026
most citedCompositional Languages Emerge in a Neural Iterated Learning Model

34 citations · 63 across the 13 of their papers we have counts for

collaborators
Showing cs.LGShow all

10 papers · 1 filter

cs.LG2025

Token Hidden Reward: Steering Exploration-Exploitation in Group Relative Deep Reinforcement Learning

Wenlong Deng, Yi Ren, Yushu Li +4

Reinforcement learning with verifiable rewards has significantly advanced the reasoning capabilities of large language models, yet how to explicitly steer training toward explorati…

cs.LG2025

Learning Dynamics of Deep Learning -- Force Analysis of Deep Neural Networks

Yi Ren

This thesis explores how deep learning models learn over time, using ideas inspired by force analysis. Specifically, we zoom in on the model's training procedure to see how one tra…

cs.LG2025

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization

Wenlong Deng, Yi Ren, Muchen Li +3

Reinforcement learning (RL) has become popular in enhancing the reasoning capabilities of large language models (LLMs), with Group Relative Policy Optimization (GRPO) emerging as a…

cs.LG2024

Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamics

Yi Ren, Danica J. Sutherland

Obtaining compositional mappings is important for the model to generalize well compositionally. To better understand when and how to encourage the model to learn such mappings, we…

cs.LG20241 cited

Learning Dynamics of LLM Finetuning

Yi Ren, Danica J. Sutherland

Learning dynamics, which describes how the learning of specific training examples influences the model's predictions on other examples, gives us a powerful tool for understanding t…

cs.LG2024

lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning

Shangmin Guo, Yi Ren, Stefano V. Albrecht +1

Although much research has been done on proposing new models or loss functions to improve the generalisation of artificial neural networks (ANNs), less attention has been directed…