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Found 15 papers, 3 papers with code
LLaMandement: Large Language Models for Summarization of French Legislative Proposals
This report introduces LLaMandement, a state-of-the-art Large Language Model, fine-tuned by the French government and designed to enhance the efficiency and efficacy of processing parliamentary sessions (including the production of bench memoranda and documents required for interministerial meetings) by generating neutral summaries of legislative proposals.
Predicting Token Impact Towards Efficient Vision Transformer
Token filtering to reduce irrelevant tokens prior to self-attention is a straightforward way to enable efficient vision Transformer.
SIEDOB: Semantic Image Editing by Disentangling Object and Background
Moreover, to produce high-quality edited images, we propose some innovative designs, including Semantic-Aware Self-Propagation Module, Boundary-Anchored Patch Discriminator, and Style-Diversity Object Generator, and integrate them into SIEDOB.
Reference-Guided Large-Scale Face Inpainting with Identity and Texture Control
To introduce strong control for face inpainting, we propose a novel reference-guided face inpainting method that fills the large-scale missing region with identity and texture control guided by a reference face image.
Context-Consistent Semantic Image Editing with Style-Preserved Modulation
Semantic image editing utilizes local semantic label maps to generate the desired content in the edited region.
Unified smoke and fire detection in an evolutionary framework with self-supervised progressive data augment
Few researches have studied simultaneous detection of smoke and flame accompanying fires due to their different physical natures that lead to uncertain fluid patterns.
TransPPG: Two-stream Transformer for Remote Heart Rate Estimate
Non-contact facial video-based heart rate estimation using remote photoplethysmography (rPPG) has shown great potential in many applications (e. g., remote health care) and achieved creditable results in constrained scenarios.
Adaptive Template Enhancement for Improved Person Recognition using Small Datasets
A novel instance-based method for the classification of electroencephalography (EEG) signals is presented and evaluated in this paper.
Reinforcement Learning Based Sparse Black-box Adversarial Attack on Video Recognition Models
Attacks are only performed on selected key regions and key frames to reduce the high computation cost of searching adversarial perturbations on a video due to its high dimensionality.
Video Anomaly Detection By The Duality Of Normality-Granted Optical Flow
The normality-granted optical flow is predicted from a single frame, to keep the motion knowledge focused on normal patterns.
Risk Prediction on Traffic Accidents using a Compact Neural Model for Multimodal Information Fusion over Urban Big Data
Predicting risk map of traffic accidents is vital for accident prevention and early planning of emergency response.
Weighted Ensemble-model and Network Analysis: A method to predict fluid intelligence via naturalistic functional connectivity
Methods: In this study, inspired by multi-layer brain network structure, we propose a new method namely Weighted Ensemble-model and Network Analysis, which combines the machine learning and graph theory for improved fluid intelligence prediction.
Design and verification of the HXI collimator onboard the ASO-S mission
The HXI collimator (HXI-C) is a spatial modulation X-ray telescope designed to observe hard X-rays emitted by energetic electrons in solar flares.
Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics High Energy Physics - Experiment
Anomaly Detection and Localization in Crowded Scenes by Motion-field Shape Description and Similarity-based Statistical Learning
In crowded scenes, detection and localization of abnormal behaviors is challenging in that high-density people make object segmentation and tracking extremely difficult.
Neural Aesthetic Image Reviewer
Through multi-task learning, the proposed models can rate aesthetic images as well as produce comments in an end-to-end manner.
