Search Results for author:
Found 7 papers, 3 papers with code
Base of RoPE Bounds Context Length
We revisit the role of RoPE in LLMs and propose a novel property of long-term decay, we derive that the \textit{base of RoPE bounds context length}: there is an absolute lower bound for the base value to obtain certain context length capability.
Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild
Multimodal fusion is a significant method for most multimodal tasks.
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
As Large Language Models (LLMs) continue to advance in performance, their size has escalated significantly, with current LLMs containing billions or even trillions of parameters.
SVFAP: Self-supervised Video Facial Affect Perceiver
Video-based facial affect analysis has recently attracted increasing attention owing to its critical role in human-computer interaction.
Ranked #3 on
Dynamic Facial Expression Recognition
on FERV39k
Dynamic Facial Expression Recognition
Emotion Recognition
+2
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
Pseudo Labels Regularization for Imbalanced Partial-Label Learning
Partial-label learning (PLL) is an important branch of weakly supervised learning where the single ground truth resides in a set of candidate labels, while the research rarely considers the label imbalance.
IRNet: Iterative Refinement Network for Noisy Partial Label Learning
In this paper, we relax this assumption and focus on a more general problem, noisy PLL, where the ground-truth label may not exist in the candidate set.
