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Found 8 papers, 1 papers with code
Position Engineering: Boosting Large Language Models through Positional Information Manipulation
Position engineering thus represents a promising new strategy for exploiting the capabilities of large language models.
LLM-ABR: Designing Adaptive Bitrate Algorithms via Large Language Models
We present LLM-ABR, the first system that utilizes the generative capabilities of large language models (LLMs) to autonomously design adaptive bitrate (ABR) algorithms tailored for diverse network characteristics.
Transfer Learning-Enhanced Instantaneous Multi-Person Indoor Localization by CSI
Passive indoor localization, integral to smart buildings, emergency response, and indoor navigation, has traditionally been limited by a focus on single-target localization and reliance on multi-packet CSI.
TSNet-SAC: Leveraging Transformers for Efficient Task Scheduling
In future 6G Mobile Edge Computing (MEC), autopilot systems require the capability of processing multimodal data with strong interdependencies.
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning
Empowered by the robust relation net built on SSL, we found that BEYOND outperforms baselines in terms of both detection ability and speed.
Gradient Boosting Machine: A Survey
In this survey, we discuss several different types of gradient boosting algorithms and illustrate their mathematical frameworks in detail: 1. introduction of gradient boosting leads to 2. objective function optimization, 3. loss function estimations, and 4. model constructions.
Unsupervised Discovery of Object Landmarks as Structural Representations
Deep neural networks can model images with rich latent representations, but they cannot naturally conceptualize structures of object categories in a human-perceptible way.
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries
Our training objective encourages better localization on single images, incorporates text phrases in a broad range, and properly pairs image regions with text phrases into positive and negative examples.
