Latest Research
ID-Animator: Zero-Shot Identity-Preserving Human Video Generation
Based on this pipeline, a random face reference training method is further devised to precisely capture the ID-relevant embeddings from reference images, thus improving the fidelity and generalization capacity of our model for ID-specific video generation.
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts
ise-uiuc/xft
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We introduce XFT, a simple yet powerful training scheme, by simply merging upcycled Mixture-of-Experts (MoE) to unleash the performance limit of instruction-tuned code Large Language Models (LLMs).
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
This survey aims to fill this gap by primarily focusing on poisoning attacks and their countermeasures.
Deep neural networks for choice analysis: Enhancing behavioral regularity with gradient regularization
Moreover, the proposed framework is applicable to other NN-based choice models such as TasteNets.
Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
princeton-vl/multislam_diffpose
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The backbone is trained end-to-end using a novel differentiable solver for wide-baseline two-view pose.
Metric-guided Image Reconstruction Bounds via Conformal Prediction
We apply our method to sparse-view CT for downstream radiotherapy planning and show 1) that metric-guided bounds have valid coverage for downstream metrics while conventional pixel-wise bounds do not and 2) anatomical differences of upper/lower bounds between metric-guided and pixel-wise methods.
Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image Classification
This paper presents an innovative disjoint sampling approach for training SOTA models on Hyperspectral image classification (HSIC) tasks.
Pyramid Hierarchical Transformer for Hyperspectral Image Classification
The traditional Transformer model encounters challenges with variable-length input sequences, particularly in Hyperspectral Image Classification (HSIC), leading to efficiency and scalability concerns.
UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition
This paper presents the UniMER dataset to provide the first study on Mathematical Expression Recognition (MER) towards complex real-world scenarios.
CASPR: Automated Evaluation Metric for Contrastive Summarization
Summarizing comparative opinions about entities (e. g., hotels, phones) from a set of source reviews, often referred to as contrastive summarization, can considerably aid users in decision making.
