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Found 13 papers, 8 papers with code
Protein-ligand binding representation learning from fine-grained interactions
The binding between proteins and ligands plays a crucial role in the realm of drug discovery.
Preference Ranking Optimization for Human Alignment
In this manner, PRO effectively transforms human alignment into aligning the probability ranking of n responses generated by LLM with the preference ranking of humans towards these responses.
CPNet: Exploiting CLIP-based Attention Condenser and Probability Map Guidance for High-fidelity Talking Face Generation
Recently, talking face generation has drawn ever-increasing attention from the research community in computer vision due to its arduous challenges and widespread application scenarios, e. g. movie animation and virtual anchor.
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
(2) How can we enhance LLMs' ability to utilize tools?
THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression
To address this bottleneck and accelerate training, a widely-deployed approach is compression.
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
Text recognition is a long-standing research problem for document digitalization.
Ranked #3 on
Handwritten Text Recognition
on IAM
Decentralized Global Connectivity Maintenance for Multi-Robot Navigation: A Reinforcement Learning Approach
The problem of multi-robot navigation of connectivity maintenance is challenging in multi-robot applications.
Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction
We develop a novel framework that adds the regularizers of the sparse group lasso to a family of adaptive optimizers in deep learning, such as Momentum, Adagrad, Adam, AMSGrad, AdaHessian, and create a new class of optimizers, which are named Group Momentum, Group Adagrad, Group Adam, Group AMSGrad and Group AdaHessian, etc., accordingly.
DocBank: A Benchmark Dataset for Document Layout Analysis
DocBank is constructed using a simple yet effective way with weak supervision from the \LaTeX{} documents available on the arXiv. com.
SegAttnGAN: Text to Image Generation with Segmentation Attention
In this paper, we propose a novel generative network (SegAttnGAN) that utilizes additional segmentation information for the text-to-image synthesis task.
TableBank: Table Benchmark for Image-based Table Detection and Recognition
We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet.
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
In this paper, we propose the \textbf{LayoutLM} to jointly model interactions between text and layout information across scanned document images, which is beneficial for a great number of real-world document image understanding tasks such as information extraction from scanned documents.
Ranked #7 on
Relation Extraction
on FUNSD
TableBank: A Benchmark Dataset for Table Detection and Recognition
We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet.
