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Found 20 papers, 12 papers with code
SocialED: A Python Library for Social Event Detection
SocialED is a comprehensive, open-source Python library designed to support social event detection (SED) tasks, integrating 19 detection algorithms and 14 diverse datasets.
Towards Effective, Efficient and Unsupervised Social Event Detection in the Hyperbolic Space
Specifically, the proposed framework first models social messages into semantic-based message anchors, and then leverages the structure of the anchor graph and the expressiveness of the hyperbolic space to acquire structure- and geometry-aware anchor representations.
Multi-View Incongruity Learning for Multimodal Sarcasm Detection
Experimental results demonstrate the superiority of MICL on benchmark datasets, along with the analyses showcasing MICL's advancement in mitigating the effect of spurious correlation.
Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification
Uncertainty Quantification (UQ) is crucial for reliable image segmentation.
Does Knowledge Localization Hold True? Surprising Differences Between Entity and Relation Perspectives in Language Models
Contrary to prior research suggesting that knowledge is stored in MLP weights, our experiments demonstrate that relational knowledge is also significantly encoded in attention modules.
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism
We present a novel local aggregation strategy utilizing Bayesian optimization to incorporate global knowledge while retaining local characteristics.
Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image Restoration
However, several practical challenges remain, including meeting the specific and simultaneous demands of different tasks, balancing relationships between tasks, and effectively utilizing task correlations in model design.
Adaptive Differentially Private Structural Entropy Minimization for Unsupervised Social Event Detection
In this process, our method can adaptively apply differential privacy based on the events occurring each day in an open environment to maximize the use of the privacy budget.
Table-Filling via Mean Teacher for Cross-domain Aspect Sentiment Triplet Extraction
This allows the model to benefit from the OD extraction paradigm and region-level alignment.
Model Guidance via Explanations Turns Image Classifiers into Segmentation Models
On the other hand, losses can be imposed on differentiable heatmaps, which has been shown to serve for (1)~improving heatmaps to be more human-interpretable, (2)~regularization of networks towards better generalization, (3)~training diverse ensembles of networks, and (4)~for explicitly ignoring confounding input features.
UNO Arena for Evaluating Sequential Decision-Making Capability of Large Language Models
In order to answer this question, we propose the UNO Arena based on the card game UNO to evaluate the sequential decision-making capability of LLMs and explain in detail why we choose UNO.
Relational Prompt-based Pre-trained Language Models for Social Event Detection
In this paper, we approach social event detection from a new perspective based on Pre-trained Language Models (PLMs), and present RPLM_SED (Relational prompt-based Pre-trained Language Models for Social Event Detection).
Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent
Large Language Models (LLMs) have revolutionized open-domain dialogue agents but encounter challenges in multi-character role-playing (MCRP) scenarios.
CLIP-Driven Semantic Discovery Network for Visible-Infrared Person Re-Identification
Additionally, acknowledging the complementary nature of semantic details across different modalities, we integrate text features from the bimodal language descriptions to achieve comprehensive semantics.
Assessing Knowledge Editing in Language Models via Relation Perspective
Knowledge Editing (KE) for modifying factual knowledge in Large Language Models (LLMs) has been receiving increasing attention.
MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Models
As a result, it is natural for people to believe that LLMs have also mastered abilities such as time understanding and reasoning.
Lifelong Intent Detection via Multi-Strategy Rebalancing
In this paper, we propose Lifelong Intent Detection (LID), which continually trains an ID model on new data to learn newly emerging intents while avoiding catastrophically forgetting old data.
How Shift Equivariance Impacts Metric Learning for Instance Segmentation
In our work, we contribute a comprehensive formal analysis of the shift equivariance properties of encoder-decoder-style CNNs, which yields a clear picture of what can and cannot be achieved with metric learning in the face of same-looking objects.
Verification Code Recognition Based on Active and Deep Learning
However, the advantages of convolutional neural networks depend on the data used by the training classifier, particularly the size of the training set.
