Search Results for author:
Found 69 papers, 28 papers with code
KLMo: Knowledge Graph Enhanced Pretrained Language Model with Fine-Grained Relationships
In this work, we propose to incorporate KG (including both entities and relations) into the language learning process to obtain KG-enhanced pretrained Language Model, namely KLMo.
Real-time Indexing for Large-scale Recommendation by Streaming Vector Quantization Retriever
Considering simple models lack the ability to produce precise predictions, most of the existing methods mainly focus on incorporating complicated ranking models.
Robust Low-Light Human Pose Estimation through Illumination-Texture Modulation
As critical visual details become obscured, the low visibility and high ISO noise in extremely low-light images pose a significant challenge to human pose estimation.
AgentPose: Progressive Distribution Alignment via Feature Agent for Human Pose Distillation
Pose distillation is widely adopted to reduce model size in human pose estimation.
DuoCast: Duo-Probabilistic Meteorology-Aware Model for Extended Precipitation Nowcasting
Recently, extended short-term precipitation nowcasting struggles with decreasing precision because of insufficient consideration of meteorological knowledge, such as weather fronts which significantly influence precipitation intensity, duration, and spatial distribution.
Energy Consumption Optimization, Response Time Differences and Indicators in Cortical Working Memory Revealed by Nonequilibrium
Experimental validation is challenging due to evolutionary variability, making our theoretical approach valuable for quantifying complex dynamics.
DaYu: Data-Driven Model for Geostationary Satellite Observed Cloud Images Forecasting
Unlike existing data-driven weather forecasting models, DaYu is specifically designed for geostationary satellite observations, with a temporal resolution of 0. 5 hours and a spatial resolution of ${0. 05}^\circ$ $\times$ ${0. 05}^\circ$.
Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens.
Enhancing Robustness in Large Language Models: Prompting for Mitigating the Impact of Irrelevant Information
The ATF method, as demonstrated by experimental results, significantly improves the reasoning performance of LLMs and prompting techniques, even in the presence of irrelevant information on the GSMIR dataset.
StructEval: Deepen and Broaden Large Language Model Assessment via Structured Evaluation
Evaluation is the baton for the development of large language models.
From Sim-to-Real: Toward General Event-based Low-light Frame Interpolation with Per-scene Optimization
This approach utilizes the internal statistics of a sequence to handle degraded event data under low-light conditions, improving the generalizability to different lighting and camera settings.
Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing
Few-shot and zero-shot text classification aim to recognize samples from novel classes with limited labeled samples or no labeled samples at all.
Interest Clock: Time Perception in Real-Time Streaming Recommendation System
Time modeling aims to enable recommendation systems to perceive time changes to capture users' dynamic preferences over time, which is an important and challenging problem in recommendation systems.
Diffusion Deepfake
To address this critical issue, we investigate the impact of enhancing training data diversity on representative detection methods.
Event-Based Motion Magnification
In this work, we propose a dual-camera system consisting of an event camera and a conventional RGB camera for video motion magnification, providing temporally-dense information from the event stream and spatially-dense data from the RGB images.
Trinity: Syncretizing Multi-/Long-tail/Long-term Interests All in One
Interest modeling in recommender system has been a constant topic for improving user experience, and typical interest modeling tasks (e. g. multi-interest, long-tail interest and long-term interest) have been investigated in many existing works.
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
Black-box hard-label adversarial attack on text is a practical and challenging task, as the text data space is inherently discrete and non-differentiable, and only the predicted label is accessible.
Real-Time Exposure Correction via Collaborative Transformations and Adaptive Sampling
Specifically the global transformation adjusts the overall appearance using image-adaptive 3D LUTs to provide decent global contrast and sharp details while the pixel transformation compensates for local context.
UFineBench: Towards Text-based Person Retrieval with Ultra-fine Granularity
Firstly, we construct a new \textbf{dataset} named UFine6926.
Enhancing the Spatial Awareness Capability of Multi-Modal Large Language Model
The Multi-Modal Large Language Model (MLLM) refers to an extension of the Large Language Model (LLM) equipped with the capability to receive and infer multi-modal data.
Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone Mapping
Furthermore, we utilize local Laplacian filters to refine the edge details in the high-frequency components in an adaptive manner.
Enhancing the machine vision performance with multi-spectral light sources
The results show that for both models there are always some non-pure white light sources, whose accuracy is better than pure white light, which suggests the potential of multi-spectral light sources to further enhance the effectiveness of machine vision.
Enhancing Subtask Performance of Multi-modal Large Language Model
Finally, the results from multiple pre-trained models for the same subtask are compared using the LLM, and the best result is chosen as the outcome for that subtask.
Enhancing Cell Proliferation and Migration by MIR-Carbonyl Vibrational Coupling: Insights from Transcriptome Profiling
Cell proliferation and migration highly relate to normal tissue self-healing, therefore it is highly significant for artificial controlling.
Towards General Low-Light Raw Noise Synthesis and Modeling
To address this issue, we introduce a new perspective to synthesize the signal-independent noise by a generative model.
Ranked #2 on
Image Denoising
on SID SonyA7S2 x300
6G Network Business Support System
6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional perception, global coverage, green and low-carbon, native network security, etc.
Reconstructing Three-decade Global Fine-Grained Nighttime Light Observations by a New Super-Resolution Framework
We provide the long-term and fine-grained nighttime light observations to promote research on human activities.
Regulating the Hydrophobic Domain in Peptide-Catecholamine Coassembled Nanostructures for Fluorescence Enhancement
Hydrophobic domains provide specific microenvironment for essential functional activities in life.
FuXi: A cascade machine learning forecasting system for 15-day global weather forecast
Over the past few years, due to the rapid development of machine learning (ML) models for weather forecasting, state-of-the-art ML models have shown superior performance compared to the European Centre for Medium-Range Weather Forecasts (ECMWF)'s high-resolution forecast (HRES) in 10-day forecasts at a spatial resolution of 0. 25 degree.
Constrained Proximal Policy Optimization
The problem of constrained reinforcement learning (CRL) holds significant importance as it provides a framework for addressing critical safety satisfaction concerns in the field of reinforcement learning (RL).
Nonconvex Robust High-Order Tensor Completion Using Randomized Low-Rank Approximation
To the best of our knowledge, this is the first study to incorporate the randomized low-rank approximation into the RHTC problem.
PLIP: Language-Image Pre-training for Person Representation Learning
To address this issue, we propose a novel language-image pre-training framework for person representation learning, termed PLIP.
Ranked #7 on
Text based Person Retrieval
on ICFG-PEDES
Binary stochasticity enabled highly efficient neuromorphic deep learning achieves better-than-software accuracy
We propose a binary stochastic learning algorithm that modifies all elementary neural network operations, by introducing (i) stochastic binarization of both the forwarding signals and the activation function derivatives, (ii) signed binarization of the backpropagating errors, and (iii) step-wised weight updates.
Boosting Few-Shot Text Classification via Distribution Estimation
Distribution estimation has been demonstrated as one of the most effective approaches in dealing with few-shot image classification, as the low-level patterns and underlying representations can be easily transferred across different tasks in computer vision domain.
Few-Shot Image Classification
Few-Shot Text Classification
+1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report
While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints.
Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report
The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing.
Realistic Bokeh Effect Rendering on Mobile GPUs, Mobile AI & AIM 2022 challenge: Report
In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based bokeh effect rendering approach that can run on modern smartphone GPUs using TensorFlow Lite.
Generalized Nonconvex Approach for Low-Tubal-Rank Tensor Recovery
The tensor-tensor product-induced tensor nuclear norm (t-TNN) (Lu et al., 2020) minimization for low-tubal-rank tensor recovery attracts broad attention recently.
The Second Place Solution for The 4th Large-scale Video Object Segmentation Challenge--Track 3: Referring Video Object Segmentation
The referring video object segmentation task (RVOS) aims to segment object instances in a given video referred by a language expression in all video frames.
Pyramid Region-based Slot Attention Network for Temporal Action Proposal Generation
Based on PRSlot modules, we present a novel Pyramid Region-based Slot Attention Network termed PRSA-Net to learn a unified visual representation with rich temporal and semantic context for better proposal generation.
Probing Visual-Audio Representation for Video Highlight Detection via Hard-Pairs Guided Contrastive Learning
Our proposed method mainly leverages the intra-modality encoding and cross-modality co-occurrence encoding for fully representation modeling.
Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection
Multi-label aspect category detection allows a given review sentence to contain multiple aspect categories, which is shown to be more practical in sentiment analysis and attracting increasing attention.
A Simple Meta-learning Paradigm for Zero-shot Intent Classification with Mixture Attention Mechanism
Zero-shot intent classification is a vital and challenging task in dialogue systems, which aims to deal with numerous fast-emerging unacquainted intents without annotated training data.
Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation
A high-resolution network exhibits remarkable capability in extracting multi-scale features for human pose estimation, but fails to capture long-range interactions between joints and has high computational complexity.
Ranked #30 on
Pose Estimation
on COCO test-dev
Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior
We introduce a Noise Disentanglement Module (NDM) to disentangle the noise and content in the reflectance maps with the reliable aid of unpaired clean images.
Ranked #2 on
Low-Light Image Enhancement
on MEF
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
Satellite video cameras can provide continuous observation for a large-scale area, which is important for many remote sensing applications.
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling
Intent classification (IC) and slot filling (SF) are critical building blocks in task-oriented dialogue systems.
DARDet: A Dense Anchor-free Rotated Object Detector in Aerial Images
Rotated object detection in aerial images has received increasing attention for a wide range of applications.
Single Person Pose Estimation: A Survey
Human pose estimation in unconstrained images and videos is a fundamental computer vision task.
Low-resolution Human Pose Estimation
Human pose estimation has achieved significant progress on images with high imaging resolution.
TexSmart: A System for Enhanced Natural Language Understanding
This paper introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
Concept-Based Label Embedding via Dynamic Routing for Hierarchical Text Classification
In this paper, we propose a novel concept-based label embedding method that can explicitly represent the concept and model the sharing mechanism among classes for the hierarchical text classification.
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction
In this paper, we propose a Pre-trained masked Language model with Misspelled knowledgE (PLOME) for CSC, which jointly learns how to understand language and correct spelling errors.
UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction
Keyphrase Prediction (KP) task aims at predicting several keyphrases that can summarize the main idea of the given document.
Turnover-Adjusted Information Ratio
In this paper, we study the behavior of information ratio (IR) as determined by the fundamental law of active investment management.
Efficient Deep Image Denoising via Class Specific Convolution
In this paper, we propose an efficient deep neural network for image denoising based on pixel-wise classification.
Adaptive Variational Quantum Imaginary Time Evolution Approach for Ground State Preparation
This ensures the state is able to follow the quantum imaginary time evolution path in the system Hilbert space rather than in a restricted variational manifold set by a predefined fixed ansatz.
Chemical Physics Strongly Correlated Electrons Computational Physics Quantum Physics
Arbitrary-Oriented Ship Detection through Center-Head Point Extraction
Moreover, we introduce a new dataset for multi-class arbitrary-oriented ship detection in remote sensing images at a fixed ground sample distance (GSD) which is named FGSD2021.
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
Super strong paramagnetism of aromatic peptides adsorbed with monovalent cations
We experimentally demonstrated that the AYFFF self-assemblies adsorbed with various monovalent cations (Na+, K+, and Li+) show unexpectedly super strong paramagnetism.
Biological Physics
Information Coefficient as a Performance Measure of Stock Selection Models
Information coefficient (IC) is a widely used metric for measuring investment managers' skills in selecting stocks.
Joint COCO and Mapillary Workshop at ICCV 2019 Keypoint Detection Challenge Track Technical Report: Distribution-Aware Coordinate Representation for Human Pose Estimation
Taking them together, we formulate a novel Distribution-Aware coordinate Representation for Keypoint (DARK) method.
Gutzwiller Hybrid Quantum-Classical Computing Approach for Correlated Materials
Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational quantum eigensolver (VQE), that can address open challenges in quantum chemistry, physics and material science.
Strongly Correlated Electrons Materials Science Computational Physics
Distribution-Aware Coordinate Representation for Human Pose Estimation
Interestingly, we found that the process of decoding the predicted heatmaps into the final joint coordinates in the original image space is surprisingly significant for human pose estimation performance, which nevertheless was not recognised before.
Ranked #2 on
Multi-Person Pose Estimation
on MS COCO
(using extra training data)
Tensor Restricted Isometry Property Analysis For a Large Class of Random Measurement Ensembles
In previous work, theoretical analysis based on the tensor Restricted Isometry Property (t-RIP) established the robust recovery guarantees of a low-tubal-rank tensor.
Event Detection without Triggers
The goal of event detection (ED) is to detect the occurrences of events and categorize them.
Hierarchical Photo-Scene Encoder for Album Storytelling
In this paper, we propose a novel model with a hierarchical photo-scene encoder and a reconstructor for the task of album storytelling.
Ranked #5 on
Image-guided Story Ending Generation
on VIST-E
Fast Human Pose Estimation
In this work, we investigate the under-studied but practically critical pose model efficiency problem.
Ranked #9 on
Pose Estimation
on Leeds Sports Poses
Overcoming the time limitation in Molecular Dynamics simulation of crystal nucleation: a persistent-embryo approach
The crystal nucleation from liquid in most cases is too rare to be accessed within the limited timescales of the conventional molecular dynamics (MD) simulation.
Materials Science Soft Condensed Matter
