Deep Learning
Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium
Lagrangian approach, which involves adding a regularization term to the loss function.
Self-Labeling the Job Shop Scheduling Problem
An obstacle in applying supervised paradigms to such problems is the need for costly target solutions often produced with exact solvers.
Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing
Union14M-Benchmark). Code will be available at https://github.com/qqqyd/ViSu.
Diffusion of Thought: Chain-of-Thought Reasoning in Diffusion Language Models Jiacheng Y e
Recently, diffusion models have garnered significant interest in the field of text processing due to their many potential advantages compared to conventional autoregressive models.
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models Hannah Rose Kirk 1
Human feedback is central to the alignment of Large Language Models (LLMs).
TAIA: Large Language Models are Out-of-Distribution Data Learners
However, in certain specialized domains, such as healthcare or harmless content generation, it is nearly impossible to obtain a large volume of high-quality data that matches the downstream distribution.
Coarse-to-Fine Concept Bottleneck Models
Deep learning algorithms have recently gained significant attention due to their impressive performance.