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Found 30 papers, 11 papers with code
Contrastive Learning of Sentence Representations
Learning sentence representations which capture rich semantic meanings has been crucial for many NLP tasks.
NeRF2Points: Large-Scale Point Cloud Generation From Street Views' Radiance Field Optimization
Neural Radiance Fields (NeRF) have emerged as a paradigm-shifting methodology for the photorealistic rendering of objects and environments, enabling the synthesis of novel viewpoints with remarkable fidelity.
Unsupervised Spatial-Temporal Feature Enrichment and Fidelity Preservation Network for Skeleton based Action Recognition
To address this problem, the overfitting mechanism behind the unsupervised learning for skeleton based action recognition is first investigated.
Transfer and Alignment Network for Generalized Category Discovery
On the other hand, we use these prototypes to calibrate noisy prototypes estimated from unlabeled data based on category similarities, which allows for more accurate estimation of prototypes for novel categories that can be used as reliable learning targets later.
Generalized Category Discovery with Large Language Models in the Loop
Then we propose a Scalable Query strategy to allow LLMs to choose true neighbors of the selected samples from multiple candidate samples.
Learning Triangular Distribution in Visual World
Convolution neural network is successful in pervasive vision tasks, including label distribution learning, which usually takes the form of learning an injection from the non-linear visual features to the well-defined labels.
A Diffusion Weighted Graph Framework for New Intent Discovery
New Intent Discovery (NID) aims to recognize both new and known intents from unlabeled data with the aid of limited labeled data containing only known intents.
DNA: Denoised Neighborhood Aggregation for Fine-grained Category Discovery
Specifically, we retrieve k-nearest neighbors of a query as its positive keys to capture semantic similarities between data and then aggregate information from the neighbors to learn compact cluster representations, which can make fine-grained categories more separatable.
DAA: A Delta Age AdaIN operation for age estimation via binary code transformer
Inspired by the transfer learning, we designed the Delta Age AdaIN (DAA) operation to obtain the feature difference with each age, which obtains the style map of each age through the learned values representing the mean and standard deviation.
Generalized Category Discovery with Decoupled Prototypical Network
Furthermore, the coupled training approach prevents these models transferring category-specific knowledge explicitly from labeled data to unlabeled data, which can lose high-level semantic information and impair model performance.
UV-Based 3D Hand-Object Reconstruction with Grasp Optimization
We propose a novel framework for 3D hand shape reconstruction and hand-object grasp optimization from a single RGB image.
Fine-grained Category Discovery under Coarse-grained supervision with Hierarchical Weighted Self-contrastive Learning
Novel category discovery aims at adapting models trained on known categories to novel categories.
Annotation of Chinese Predicate Heads and Relevant Elements
This annotation guideline emphasizes the role of the predicate as the structural center of a sentence.
Progenitor, environment, and modelling of the interacting transient, AT 2016jbu (Gaia16cfr)
We present the bolometric lightcurve, identification and analysis of the progenitor candidate, and preliminary modelling of AT2016jbu (Gaia16cfr).
High Energy Astrophysical Phenomena Solar and Stellar Astrophysics
I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling
Reconstructing a high-precision and high-fidelity 3D human hand from a color image plays a central role in replicating a realistic virtual hand in human-computer interaction and virtual reality applications.
A Boundary Regression Model for Nested Named Entity Recognition
Then, a regression operation is introduced to regress boundaries of NEs in a sentence.
Semantic-preserving Reinforcement Learning Attack Against Graph Neural Networks for Malware Detection
As an increasing number of deep-learning-based malware scanners have been proposed, the existing evasion techniques, including code obfuscation and polymorphic malware, are found to be less effective.
Risk Modelling on Liquidations with Lévy Processes
The results have semi-explicit expressions in terms of the scale functions and the L\'{e}vy triplets associated with the two underlying L\'{e}vy processes.
Integrating Boundary Assembling into a DNN Framework for Named Entity Recognition in Chinese Social Media Text
Named entity recognition is a challenging task in Natural Language Processing, especially for informal and noisy social media text.
Mitigating Class Boundary Label Uncertainty to Reduce Both Model Bias and Variance
To overcome this dilemma, we take a different perspective and investigate a new approach to handle inaccuracy and uncertainty in the training data labels, which are inevitable in many applications where labels are conceptual and labeling is performed by human annotators.
SummerTime: Variable-length Time SeriesSummarization with Applications to PhysicalActivity Analysis
Summarization conducted by the \textit{SummerTime} method will be a fixed-length feature vector which can be used in-place of the time series dataset for use with classical machine learning methods.
Flow Rate Control in Smart District Heating Systems Using Deep Reinforcement Learning
At high latitudes, many cities adopt a centralized heating system to improve the energy generation efficiency and to reduce pollution.
Generalized Expected Discounted Penalty Function at General Drawdown for Lévy Risk Processes
This paper considers an insurance surplus process modeled by a spectrally negative L\'{e}vy process.
On the Ca-strong 1991bg-like type Ia supernova 2016hnk: evidence for a Chandrasekhar-mass explosion
Our modeling suggests that the narrow [Ca II] features observed in the nebular spectrum are associated with $^{48}$Ca from electron capture during the explosion, which is expected to occur only in white dwarfs that explode near or at the $M_{\rm Ch}$ limit.
Solar and Stellar Astrophysics High Energy Astrophysical Phenomena
Predicting the Quality of Short Narratives from Social Media
An important and difficult challenge in building computational models for narratives is the automatic evaluation of narrative quality.
A Semantic QA-Based Approach for Text Summarization Evaluation
In this paper, we will present some preliminary results on one especially useful and challenging problem in NLP system evaluation: how to pinpoint content differences of two text passages (especially for large pas-sages such as articles and books).
Bag-of-Words Method Applied to Accelerometer Measurements for the Purpose of Classification and Energy Estimation
For this, our approach utilizes a mathematical model originating in natural language processing, the bag-of-words model, that has in the past years been appearing in diverse disciplines outside of the natural language processing field such as image processing.
Topic Modeling over Short Texts by Incorporating Word Embeddings
Inferring topics from the overwhelming amount of short texts becomes a critical but challenging task for many content analysis tasks, such as content charactering, user interest profiling, and emerging topic detecting.
An Experimental Study of LSTM Encoder-Decoder Model for Text Simplification
Text simplification (TS) aims to reduce the lexical and structural complexity of a text, while still retaining the semantic meaning.
