Search Results for author:
Found 6 papers, 3 papers with code
Protecting Your LLMs with Information Bottleneck
The advent of large language models (LLMs) has revolutionized the field of natural language processing, yet they might be attacked to produce harmful content.
Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning
One of the notorious issues for Reinforcement Learning (RL) is poor sample efficiency.
STIGCN: spatial–temporal interaction‑aware graph convolution network for pedestrian trajectory prediction
STIGCN considers the correlation between social interaction and pedestrian movement factors to achieve more accurate interaction modeling.
Mildly Constrained Evaluation Policy for Offline Reinforcement Learning
Offline reinforcement learning (RL) methodologies enforce constraints on the policy to adhere closely to the behavior policy, thereby stabilizing value learning and mitigating the selection of out-of-distribution (OOD) actions during test time.
An Order-Complexity Model for Aesthetic Quality Assessment of Homophony Music Performance
In order to guide the generation task of AI music performance, and to improve the performance effect of human performers, this paper uses Birkhoff's aesthetic measure to propose a method of objective measurement of beauty.
An Order-Complexity Model for Aesthetic Quality Assessment of Symbolic Homophony Music Scores
Computational aesthetics evaluation has made great achievements in the field of visual arts, but the research work on music still needs to be explored.
