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Found 36 papers, 12 papers with code
Seed1.5-VL Technical Report
We present Seed1. 5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning.
New Recipe for Semi-supervised Community Detection: Clique Annealing under Crystallization Kinetics
To address these limitations, we draw a parallel between crystallization kinetics and community detection to integrate the spontaneity of the annealing process into community detection.
Data Assetization via Resources-decoupled Federated Learning
With the development of the digital economy, data is increasingly recognized as an essential resource for both work and life.
Proof-of-Data: A Consensus Protocol for Collaborative Intelligence
Existing research on federated learning has been focused on the setting where learning is coordinated by a centralized entity.
A Full-History Network Dataset for BTC Asset Decentralization Profiling
Since its advent in 2009, Bitcoin (BTC) has garnered increasing attention from both academia and industry.
Knowledge Enhanced Multi-intent Transformer Network for Recommendation
However, simply integrating KG into recommendation usually brings in negative feedback in industry, due to the ignorance of the following two factors: i) users' multiple intents, which involve diverse nodes in KG.
WarpDiffusion: Efficient Diffusion Model for High-Fidelity Virtual Try-on
Image-based Virtual Try-On (VITON) aims to transfer an in-shop garment image onto a target person.
From Asset Flow to Status, Action and Intention Discovery: Early Malice Detection in Cryptocurrency
An ideal detection model is expected to achieve all three critical properties of (I) early detection, (II) good interpretability, and (III) versatility for various illicit activities.
AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Pose
We present AvatarVerse, a stable pipeline for generating expressive high-quality 3D avatars from nothing but text descriptions and pose guidance.
HandMIM: Pose-Aware Self-Supervised Learning for 3D Hand Mesh Estimation
Our approach involves a unified and multi-granularity strategy that includes a pseudo keypoint alignment module in the teacher-student framework for learning pose-aware semantic class tokens.
Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation
Specifically, MHCPL timely chooses useful social information according to the interactive history and builds a dynamic hypergraph with three types of multiplex relations from different views.
MeMaHand: Exploiting Mesh-Mano Interaction for Single Image Two-Hand Reconstruction
Existing methods proposed for hand reconstruction tasks usually parameterize a generic 3D hand model or predict hand mesh positions directly.
GP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learning
Specifically, compared with the previous global warping mechanism, LFGP employs local flows to warp garments parts individually, and assembles the local warped results via the global garment parsing, resulting in reasonable warped parts and a semantic-correct intact garment even with challenging inputs. On the other hand, our DGT training strategy dynamically truncates the gradient in the overlap area and the warped garment is no more required to meet the boundary constraint, which effectively avoids the texture squeezing problem.
Evolve Path Tracer: Early Detection of Malicious Addresses in Cryptocurrency
To detect fraud behaviors of malicious addresses in the early stage, we present Evolve Path Tracer, which consists of Evolve Path Encoder LSTM, Evolve Path Graph GCN, and Hierarchical Survival Predictor.
Toward Intention Discovery for Early Malice Detection in Bitcoin
% With the type-dependent selection strategy and global status vectors, our model can be applied to detect various illicit activities with strong interpretability.
Data Provenance via Differential Auditing
In this paper, we introduce Data Provenance via Differential Auditing (DPDA), a practical framework for auditing data provenance with a different approach based on statistically significant differentials, i. e., after carefully designed transformation, perturbed input data from the target model's training set would result in much more drastic changes in the output than those from the model's non-training set.
Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning
Specifically, we first construct local and non-local graphs for user/item in KG, exploring more KG facts for KGR.
PASTA-GAN++: A Versatile Framework for High-Resolution Unpaired Virtual Try-on
In this work, we take a step forwards to explore versatile virtual try-on solutions, which we argue should possess three main properties, namely, they should support unsupervised training, arbitrary garment categories, and controllable garment editing.
Automatic Noisy Label Correction for Fine-Grained Entity Typing
Fine-grained entity typing (FET) aims to assign proper semantic types to entity mentions according to their context, which is a fundamental task in various entity-leveraging applications.
Declaration-based Prompt Tuning for Visual Question Answering
In recent years, the pre-training-then-fine-tuning paradigm has yielded immense success on a wide spectrum of cross-modal tasks, such as visual question answering (VQA), in which a visual-language (VL) model is first optimized via self-supervised task objectives, e. g., masked language modeling (MLM) and image-text matching (ITM), and then fine-tuned to adapt to downstream task (e. g., VQA) via a brand-new objective function, e. g., answer prediction.
Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System
Different from traditional contrastive learning methods which generate two graph views by uniform data augmentation schemes such as corruption or dropping, we comprehensively consider three different graph views for KG-aware recommendation, including global-level structural view, local-level collaborative and semantic views.
Blind Face Restoration via Integrating Face Shape and Generative Priors
Moreover, we introduce hybrid-level losses to jointly train the shape and generative priors together with other network parts such that these two priors better adapt to our blind face restoration task.
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations
IKT's prediction of future student performance is made using a Tree-Augmented Naive Bayes Classifier (TAN), therefore its predictions are easier to explain than deep learning-based student models.
Geometry-Entangled Visual Semantic Transformer for Image Captioning
However, those fusion-based models, they are still criticized for the lack of geometry information for inter and intra attention refinement.
Heterogeneous Graph Neural Network with Multi-view Representation Learning
Graph neural networks for heterogeneous graph embedding is to project nodes into a low-dimensional space by exploring the heterogeneity and semantics of the heterogeneous graph.
Data Pricing in Machine Learning Pipelines
We also investigate pricing in the step of collaborative training of machine learning models, and overview pricing machine learning models for end users in the step of machine learning deployment.
Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions.
Target Guided Emotion Aware Chat Machine
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions.
PNEN: Pyramid Non-Local Enhanced Networks
Additionally, the pyramid non-local block can be directly incorporated into convolution neural networks for other image restoration tasks.
Collaborative Learning for Faster StyleGAN Embedding
The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator.
Stack-VS: Stacked Visual-Semantic Attention for Image Caption Generation
Recently, automatic image caption generation has been an important focus of the work on multimodal translation task.
A Benchmark for Edge-Preserving Image Smoothing
This benchmark includes an image dataset with groundtruth image smoothing results as well as baseline algorithms that can generate competitive edge-preserving smoothing results for a wide range of image contents.
Dynamic Student Classiffication on Memory Networks for Knowledge Tracing
Knowledge Tracing (KT) is the assessment of student’s knowledge state and predicting whether that student may or may not answer the next problem correctly based on a number of previous practices and outcomes in their learning process.
Automatic Image Stylization Using Deep Fully Convolutional Networks
Such photo adjustment tools lack a semantic understanding of image contents and the resulting global color transform limits the range of artistic styles it can represent.
Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing
In Intelligent Tutoring System (ITS), tracing the student's knowledge state during learning has been studied for several decades in order to provide more supportive learning instructions.
