2 citations · 2 across the 6 of their papers we have counts for
7 papers
AffectWorld: Benchmarking Emotion-Driven Future World Prediction
Changhao Song, Yacong Chen, Hui Gao +2
The world encompasses both physical environments and human actors. Predicting its evolution requires understanding both physical laws and how emotions shape human actions. However,…
Adam's Law: Textual Frequency Law on Large Language Models
Hongyuan Adam Lu, Z. L., Victor Wei +5
While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldom studied. We propose a novel re…
Large Emotional World Model
Changhao Song, Yazhou Zhang, Hui Gao +2
The world is governed by both physical laws and affective dynamics. Physical laws govern state transitions, while affective dynamics shape human actions, decisions, and interaction…
Large Language Models for Subjective Language Understanding: A Survey
Changhao Song, Yazhou Zhang, Hui Gao +2
Subjective language understanding refers to a broad set of natural language processing tasks where the goal is to interpret or generate content that conveys personal feelings, opin…
The Scaling Law for LoRA Base on Mutual Information Upper Bound
Jing Zhang, Hui Gao, Peng Zhang +3
LoRA (Low-Rank Adaptation) is a widely used model fine-tuning method. In fine-tuning, the law among model performance, model parameters, and data complexity has been a focal issue…
SEE: Sememe Entanglement Encoding for Transformer-bases Models Compression
Jing Zhang, Shuzhen Sun, Peng Zhang +5
Transformer-based large language models exhibit groundbreaking capabilities, but their storage and computational costs are prohibitively high, limiting their application in resourc…
Quantum Implicit Neural Representations
Jiaming Zhao, Wenbo Qiao, Peng Zhang +1
Implicit neural representations have emerged as a powerful paradigm to represent signals such as images and sounds. This approach aims to utilize neural networks to parameterize th…