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Found 7 papers, 1 papers with code
Probability-density-aware Semi-supervised Learning
Semi-supervised learning (SSL) assumes that neighbor points lie in the same category (neighbor assumption), and points in different clusters belong to various categories (cluster assumption).
Open-Set Video-based Facial Expression Recognition with Human Expression-sensitive Prompting
In Video-based Facial Expression Recognition (V-FER), models are typically trained on closed-set datasets with a fixed number of known classes.
SPECAT: SPatial-spEctral Cumulative-Attention Transformer for High-Resolution Hyperspectral Image Reconstruction
Our experimental results demonstrate the superiority of SPECAT achieving 40. 3 dB in hyperspectral reconstruction benchmarks outperforming the state-of-the-art (SOTA) algorithms by 1. 2 dB while using only 5% of the network parameters and 10% of the computational cost.
A New Baseline Assumption of Integated Gradients Based on Shaply value
The selection of appropriate baselines in IG is crucial for crafting meaningful and unbiased explanations of model predictions in diverse settings.
CasIL: Cognizing and Imitating Skills via a Dual Cognition-Action Architecture
Heuristically, we extend the usual notion of action to a dual Cognition (high-level)-Action (low-level) architecture by introducing intuitive human cognitive priors, and propose a novel skill IL framework through human-robot interaction, called Cognition-Action-based Skill Imitation Learning (CasIL), for the robotic agent to effectively cognize and imitate the critical skills from raw visual demonstrations.
Exploiting Code Symmetries for Learning Program Semantics
This paper tackles the challenge of teaching code semantics to Large Language Models (LLMs) for program analysis by incorporating code symmetries into the model architecture.
Keeping Minimal Experience to Achieve Efficient Interpretable Policy Distillation
Although deep reinforcement learning has become a universal solution for complex control tasks, its real-world applicability is still limited because lacking security guarantees for policies.
