Avg
23 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Avg
Most implemented papers
KNN-Averaging for Noisy Multi-objective Optimisation
Multi-objective optimisation is a popular approach for finding solutions to complex problems with large search spaces that reliably yields good optimisation results.
Towards High-Quality Temporal Action Detection with Sparse Proposals
Towards high-quality temporal action detection, we introduce Sparse Proposals to interact with the hierarchical features.
Using Autoencoders on Differentially Private Federated Learning GANs
In order to maintain user privacy, a combination of federated learning, differential privacy and GANs can be used to work with private data without giving away a users' privacy.
Holistic Sentence Embeddings for Better Out-of-Distribution Detection
lancopku/avg-avg
•
•
On the basis of the observations that token averaging and layer combination contribute to improving OOD detection, we propose a simple embedding approach named Avg-Avg, which averages all token representations from each intermediate layer as the sentence embedding and significantly surpasses the state-of-the-art on a comprehensive suite of benchmarks by a 9. 33% FAR95 margin.
Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification
kanji95/Hierarchical-Ensembles
•
•
NeurIPS 2023
We investigate the problem of reducing mistake severity for fine-grained classification.
Temporally Aligning Long Audio Interviews with Questions: A Case Study in Multimodal Data Integration
The problem of audio-to-text alignment has seen significant amount of research using complete supervision during training.
CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders
antofuller/croma
•
•
NeurIPS 2023
We show that these objectives are complementary when leveraged on spatially aligned multimodal data.
Binding-Adaptive Diffusion Models for Structure-Based Drug Design
Then the selected protein-ligand subcomplex is processed with SE(3)-equivariant neural networks, and transmitted back to each atom of the complex for augmenting the target-aware 3D molecule diffusion generation with binding interaction information.
A Lightweight Inception Boosted U-Net Neural Network for Routability Prediction
harleyhk/ibunet
•
•
As the modern CPU, GPU, and NPU chip design complexity and transistor counts keep increasing, and with the relentless shrinking of semiconductor technology nodes to nearly 1 nanometer, the placement and routing have gradually become the two most pivotal processes in modern very-large-scale-integrated (VLSI) circuit back-end design.
Large Language Models as Zero-shot Dialogue State Tracker through Function Calling
Large language models (LLMs) are increasingly prevalent in conversational systems due to their advanced understanding and generative capabilities in general contexts.
