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Found 14 papers, 3 papers with code
Different Data, Different Modalities! Reinforced Data Splitting for Effective Multimodal Information Extraction from Social Media Posts
In this paper, we argue that different social media posts should consider different modalities for multimodal information extraction.
Precise Drive with VLM: First Prize Solution for PRCV 2024 Drive LM challenge
This technical report outlines the methodologies we applied for the PRCV Challenge, focusing on cognition and decision-making in driving scenarios.
Privacy Policy Analysis through Prompt Engineering for LLMs
In this paper, we propose, apply, and assess PAPEL (Privacy Policy Analysis through Prompt Engineering for LLMs), a framework harnessing the power of Large Language Models (LLMs) through prompt engineering to automate the analysis of privacy policies.
Online Electric Vehicle Charging Detection Based on Memory-based Transformer using Smart Meter Data
It dynamically leverages coarse-scale historical information using an M-TR encoder from an extended global temporal window, in conjunction with an M-TR decoder that concentrates on a limited time frame, local window, aiming to capture the fine-scale characteristics of the smart meter data.
Clustering-based Multitasking Deep Neural Network for Solar Photovoltaics Power Generation Prediction
For each type, a deep neural network (DNN) is employed and trained until the accuracy cannot be improved.
RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation
We propose a two-stage method, RuDi, that distills the knowledge of black-box teacher models into rule-based student models.
Multi-task Optimization Based Co-training for Electricity Consumption Prediction
The performance of MTO-CT is evaluated on solving each of these two sets of tasks in comparison to solving each task in the set independently without knowledge sharing under the same settings, which demonstrates the superiority of MTO-CT in terms of prediction accuracy.
Evolutionary Ensemble Learning for Multivariate Time Series Prediction
In this framework, a specific pipeline is encoded as a candidate solution and a multi-objective evolutionary algorithm is applied under different population sizes to produce multiple Pareto optimal sets (POSs).
Multi-objective Scheduling of Electric Vehicle Charging/Discharging with Time of Use Tariff
Optimal coordinated charging is a multi-objective optimization problem (MOOP) in nature, with objective functions such as minimum price charging and minimum disruptions to the grid.
Robust Speaker Extraction Network Based on Iterative Refined Adaptation
dataset confirm the superior performance of the proposed method over the network without IRA in terms of SI-SDR and PESQ improvement.
Deep Multi-task Network for Delay Estimation and Echo Cancellation
In this paper, a multi-task network is proposed to address both ref-delay estimation and echo cancellation tasks.
On Loss Functions and Recurrency Training for GAN-based Speech Enhancement Systems
Recent work has shown that it is feasible to use generative adversarial networks (GANs) for speech enhancement, however, these approaches have not been compared to state-of-the-art (SOTA) non GAN-based approaches.
Audio and Speech Processing Sound
DELTA: A DEep learning based Language Technology plAtform
In this paper we present DELTA, a deep learning based language technology platform.
Ranked #3 on
Named Entity Recognition
on CoNLL 2003 (English)
