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Found 64 papers, 20 papers with code
Beyond Text: Incorporating Metadata and Label Structure for Multi-Label Document Classification using Heterogeneous Graphs
The other is label heterogeneous graph, which is constructed based on both the labels’ hierarchy and their statistical dependencies.
What are the limits of cross-lingual dense passage retrieval for low-resource languages?
Our results on the MKQA and AmQA datasets show that language alignment brings improvements to mDPR for the low-resource languages, but the improvements are modest and the results remain low.
Optimizing Highway Ramp Merge Safety and Efficiency via Spatio-Temporal Cooperative Control and Vehicle-Road Coordination
Based on this selected target gap, a cooperative control method is formulated, enabling the pre-programming of vehicle trajectories.
LayoutDiT: Exploring Content-Graphic Balance in Layout Generation with Diffusion Transformer
To address these challenges, we introduce LayoutDiT, an effective framework that balances content and graphic features to generate high-quality, visually appealing layouts.
Fine-tuning Multimodal Large Language Models for Product Bundling
Recent advances in product bundling have leveraged multimodal information through sophisticated encoders, but remain constrained by limited semantic understanding and a narrow scope of knowledge.
A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting
However, the reasoning capability of LLMs on temporal event forecasting has been under-explored.
IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model
The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities.
Spatio-temporal cooperative control Method of Highway Ramp Merge Based on Vehicle-road Coordination
The merging area of highway ramps faces multiple challenges, including traffic congestion, collision risks, speed mismatches, driver behavior uncertainties, limited visibility, and bottleneck effects.
Step-Back Profiling: Distilling User History for Personalized Scientific Writing
To conduct the experiments, we construct a Personalized Scientific Writing (PSW) dataset to study multi-user personalization.
GEB-1.3B: Open Lightweight Large Language Model
Recently developed large language models (LLMs) such as ChatGPT, Claude, and Llama have demonstrated impressive abilities, and even surpass human-level performance in several tasks.
FuXi-ENS: A machine learning model for medium-range ensemble weather forecasting
This innovative approach makes FuXi-ENS an advancement over the traditional ones that use L1 loss combined with the KL loss in standard VAE models for ensemble weather forecasting.
ID-Aligner: Enhancing Identity-Preserving Text-to-Image Generation with Reward Feedback Learning
The rapid development of diffusion models has triggered diverse applications.
Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
Current distillation techniques often dichotomize into two distinct aspects: i) ODE Trajectory Preservation; and ii) ODE Trajectory Reformulation.
LAECIPS: Large Vision Model Assisted Adaptive Edge-Cloud Collaboration for IoT-based Perception System
We propose to update the edge model and its collaboration strategy with the cloud under the supervision of the large vision model, so as to adapt to the dynamic IoT data streams.
ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback
Specifically, for an input conditional control, we use a pre-trained discriminative reward model to extract the corresponding condition of the generated images, and then optimize the consistency loss between the input conditional control and extracted condition.
UniFL: Improve Latent Diffusion Model via Unified Feedback Learning
Latent diffusion models (LDM) have revolutionized text-to-image generation, leading to the proliferation of various advanced models and diverse downstream applications.
ByteEdit: Boost, Comply and Accelerate Generative Image Editing
Recent advancements in diffusion-based generative image editing have sparked a profound revolution, reshaping the landscape of image outpainting and inpainting tasks.
ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models
Especially, after learning a deep understanding of pure resolution priors, ResAdapter trained on the general dataset, generates resolution-free images with personalized diffusion models while preserving their original style domain.
Grounding Language Models for Visual Entity Recognition
We introduce AutoVER, an Autoregressive model for Visual Entity Recognition.
DiffusionGPT: LLM-Driven Text-to-Image Generation System
Diffusion models have opened up new avenues for the field of image generation, resulting in the proliferation of high-quality models shared on open-source platforms.
MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation
The growing demand for high-fidelity video generation from textual descriptions has catalyzed significant research in this field.
Diversity-Based Recruitment in Crowdsensing By Combinatorial Multi-Armed Bandits
Additionally, it accommodates the variability in task completion quality caused by overlaps in the same round, which can range from the maximum individual worker's quality to the summation of qualities of all assigned workers in the overlap.
DreamTuner: Single Image is Enough for Subject-Driven Generation
Diffusion-based models have demonstrated impressive capabilities for text-to-image generation and are expected for personalized applications of subject-driven generation, which require the generation of customized concepts with one or a few reference images.
FuXi-S2S: A machine learning model that outperforms conventional global subseasonal forecast models
Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge.
On the Communication Complexity of Decentralized Bilevel Optimization
To the best of our knowledge, this is the first time such favorable theoretical results have been achieved with mild assumptions in the heterogeneous setting.
Instructed Language Models with Retrievers Are Powerful Entity Linkers
Generative approaches powered by large language models (LLMs) have demonstrated emergent abilities in tasks that require complex reasoning abilities.
Coherent Entity Disambiguation via Modeling Topic and Categorical Dependency
We propose CoherentED, an ED system equipped with novel designs aimed at enhancing the coherence of entity predictions.
AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration
Therefore, we propose to search the optimal time steps sequence and compressed model architecture in a unified framework to achieve effective image generation for diffusion models without any further training.
UGC: Unified GAN Compression for Efficient Image-to-Image Translation
Recent years have witnessed the prevailing progress of Generative Adversarial Networks (GANs) in image-to-image translation.
DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection
This paper reveals that the recently developed Diffusion Model is a scalable data engine for object detection.
DLIP: Distilling Language-Image Pre-training
Furthermore, DLIP succeeds in retaining more than 95% of the performance with 22. 4% parameters and 24. 8% FLOPs compared to the teacher model and accelerates inference speed by 2. 7x.
AlignDet: Aligning Pre-training and Fine-tuning in Object Detection
To this end, we propose AlignDet, a unified pre-training framework that can be adapted to various existing detectors to alleviate the discrepancies.
You Can Trade Your Experience in Distributed Multi-Agent Multi-Armed Bandits
In this paper, we propose a transaction-based multi-agent MAB framework, where agents can trade their bandit experience with each other to improve their total individual rewards.
When Decentralized Optimization Meets Federated Learning
Federated learning is a new learning paradigm for extracting knowledge from distributed data.
Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning
Recent advances in text-to-image (T2I) diffusion models have enabled impressive image generation capabilities guided by text prompts.
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation
Recently, open-vocabulary learning has emerged to accomplish segmentation for arbitrary categories of text-based descriptions, which popularizes the segmentation system to more general-purpose application scenarios.
Ranked #7 on
Open Vocabulary Panoptic Segmentation
on ADE20K
Masked Vision-Language Transformers for Scene Text Recognition
MVLT is trained in two stages: in the first stage, we design a STR-tailored pretraining method based on a masking strategy; in the second stage, we fine-tune our model and adopt an iterative correction method to improve the performance.
FedVeca: Federated Vectorized Averaging on Non-IID Data with Adaptive Bi-directional Global Objective
However, the clients' Non-Independent and Identically Distributed (Non-IID) data negatively affect the trained model, and clients with different numbers of local updates may cause significant gaps to the local gradients in each communication round.
Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic Segmentation
Consequently, we offer the first attempt to provide lightweight SSSS models via a novel multi-granularity distillation (MGD) scheme, where multi-granularity is captured from three aspects: i) complementary teacher structure; ii) labeled-unlabeled data cooperative distillation; iii) hierarchical and multi-levels loss setting.
Knowledge Distillation
Semi-Supervised Semantic Segmentation
Parallel Pre-trained Transformers (PPT) for Synthetic Data-based Instance Segmentation
Recently, Synthetic data-based Instance Segmentation has become an exceedingly favorable optimization paradigm since it leverages simulation rendering and physics to generate high-quality image-annotation pairs.
TRT-ViT: TensorRT-oriented Vision Transformer
We revisit the existing excellent Transformers from the perspective of practical application.
SepViT: Separable Vision Transformer
Vision Transformers have witnessed prevailing success in a series of vision tasks.
ScalableViT: Rethinking the Context-oriented Generalization of Vision Transformer
The vanilla self-attention mechanism inherently relies on pre-defined and steadfast computational dimensions.
Soft-CP: A Credible and Effective Data Augmentation for Semantic Segmentation of Medical Lesions
The medical datasets are usually faced with the problem of scarcity and data imbalance.
Activation Modulation and Recalibration Scheme for Weakly Supervised Semantic Segmentation
Extensive experiments show that AMR establishes a new state-of-the-art performance on the PASCAL VOC 2012 dataset, surpassing not only current methods trained with the image-level of supervision but also some methods relying on stronger supervision, such as saliency label.
Uncovering the Dark Side of Telegram: Fakes, Clones, Scams, and Conspiracy Movements
We study the channels that Telegram marks as verified or scam, highlighting analogies and differences.
Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme
In this work, we revisit the role of discriminator in GAN compression and design a novel generator-discriminator cooperative compression scheme for GAN compression, termed GCC.
Online Multi-Granularity Distillation for GAN Compression
It reveals that OMGD provides a feasible solution for the deployment of real-time image translation on resource-constrained devices.
Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video
In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video.
Spoken Language Understanding for Task-oriented Dialogue Systems with Augmented Memory Networks
We adopt a key-value memory network to model slot context dynamically and to track more important slot tags decoded before, which are then fed into our decoder for slot tagging.
Auction-Based Combinatorial Multi-Armed Bandit Mechanisms with Strategic Arms
The multi-armed bandit (MAB) model has been deeply studied to solve many online learning problems, such as rate allocation in communication networks, Ad recommendation in social networks, etc.
Robust Sequence Submodular Maximization
Compared to robust submodular maximization for set function, new challenges arise when sequence functions are concerned.
Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos
Temporal grounding of natural language in untrimmed videos is a fundamental yet challenging multimedia task facilitating cross-media visual content retrieval.
Fine-Grained Image Captioning with Global-Local Discriminative Objective
This is primarily due to (i) the conservative characteristic of traditional training objectives that drives the model to generate correct but hardly discriminative captions for similar images and (ii) the uneven word distribution of the ground-truth captions, which encourages generating highly frequent words/phrases while suppressing the less frequent but more concrete ones.
Combinatorial Multi-Armed Bandit Based Unknown Worker Recruitment in Heterogeneous Crowdsensing
In each round, every task may be covered by more than one recruited workers, but its completion quality only depends on these workers' maximum sensing quality.
Adversarially Trained Multi-Singer Sequence-To-Sequence Singing Synthesizer
This paper presents a high quality singing synthesizer that is able to model a voice with limited available recordings.
XiaoiceSing: A High-Quality and Integrated Singing Voice Synthesis System
This paper presents XiaoiceSing, a high-quality singing voice synthesis system which employs an integrated network for spectrum, F0 and duration modeling.
Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video
Temporally language grounding in untrimmed videos is a newly-raised task in video understanding.
PMC-GANs: Generating Multi-Scale High-Quality Pedestrian with Multimodal Cascaded GANs
Recently, generative adversarial networks (GANs) have shown great advantages in synthesizing images, leading to a boost of explorations of using faked images to augment data.
Data-driven prediction of vortex-induced vibration response of marine risers subjected to three-dimensional current
The load model and hydrodynamic parameters in present VIV prediction tools are developed based on two-dimensional (2D) flow conditions, as it is challenging to consider the effect of 3D flow along the risers.
Visual Saliency Maps Can Apply to Facial Expression Recognition
Human eyes concentrate different facial regions during distinct cognitive activities.
Facial Expression Recognition
Facial Expression Recognition (FER)
+2
Hand Gesture Recognition with Leap Motion
The recent introduction of depth cameras like Leap Motion Controller allows researchers to exploit the depth information to recognize hand gesture more robustly.
Polarimetric Hierarchical Semantic Model and Scattering Mechanism Based PolSAR Image Classification
For polarimetric SAR (PolSAR) image classification, it is a challenge to classify the aggregated terrain types, such as the urban area, into semantic homogenous regions due to sharp bright-dark variations in intensity.
Room-temperature implementation of the Deutsch-Jozsa algorithm with a single electronic spin in diamond
The nitrogen-vacancy defect center (NV center) is a promising candidate for quantum information processing due to the possibility of coherent manipulation of individual spins in the absence of the cryogenic requirement.
Quantum Physics
