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Found 38 papers, 11 papers with code
DialogueTRM: Exploring Multi-Modal Emotional Dynamics in a Conversation
Emotion dynamics formulates principles explaining the emotional fluctuation during conversations.
PAI at SemEval-2022 Task 11: Name Entity Recognition with Contextualized Entity Representations and Robust Loss Functions
This paper describes our system used in the SemEval-2022 Task 11 Multilingual Complex Named Entity Recognition, achieving 3rd for track 1 on the leaderboard.
Tree-Regularized Tabular Embeddings
Tabular neural network (NN) has attracted remarkable attentions and its recent advances have gradually narrowed the performance gap with respect to tree-based models on many public datasets.
VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Reality
As consumer Virtual Reality (VR) and Mixed Reality (MR) technologies gain momentum, there's a growing focus on the development of engagements with 3D virtual content.
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
Moreover, we theoretically establish that the number of distinguishable eigenvalues plays a pivotal role in determining the expressive power of spectral graph neural networks.
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
A simple neural network then learns the implicit mapping from the intra- and inter-sample relations to an adaptive, sample-wise knowledge fusion ratio in a bilevel-optimization manner.
PIE-NeRF: Physics-based Interactive Elastodynamics with NeRF
We show that physics-based simulations can be seamlessly integrated with NeRF to generate high-quality elastodynamics of real-world objects.
PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamics
We introduce PhysGaussian, a new method that seamlessly integrates physically grounded Newtonian dynamics within 3D Gaussians to achieve high-quality novel motion synthesis.
DeepInception: Hypnotize Large Language Model to Be Jailbreaker
Despite remarkable success in various applications, large language models (LLMs) are vulnerable to adversarial jailbreaks that make the safety guardrails void.
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
To tackle this issue, we propose a method to abstract the collective information of atomic groups into a few $\textit{Neural Atoms}$ by implicitly projecting the atoms of a molecular.
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
We propose a hybrid neural network and physics framework for reduced-order modeling of elastoplasticity and fracture.
Teacher-Student Architecture for Knowledge Distillation: A Survey
Recently, Teacher-Student architectures have been effectively and widely embraced on various knowledge distillation (KD) objectives, including knowledge compression, knowledge expansion, knowledge adaptation, and knowledge enhancement.
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored.
PAI at SemEval-2023 Task 2: A Universal System for Named Entity Recognition with External Entity Information
The MultiCoNER II task aims to detect complex, ambiguous, and fine-grained named entities in low-context situations and noisy scenarios like the presence of spelling mistakes and typos for multiple languages.
PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification
In this work, we aim to identify parameters characterizing a physical system from a set of multi-view videos without any assumption on object geometry or topology.
Teacher-Student Architecture for Knowledge Learning: A Survey
To tackle this issue, Teacher-Student architectures were first utilized in knowledge distillation, where simple student networks can achieve comparable performance to deep teacher networks.
Confidence-Guided Unsupervised Domain Adaptation for Cerebellum Segmentation
To dispense with the manual annotation requirement, we propose to train a model to adaptively transfer the annotation from the cerebellum on the Allen Brain Human Brain Atlas to the BigBrain in an unsupervised manner, taking into account the different staining and spacing between sections.
Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval
Our model adapts to multi-scale feature inputs, favors multi-source retrieval methods, and can dynamically filter redundant features.
Ranked #8 on
Cross-Modal Retrieval
on RSITMD
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification
Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data.
Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup
To address these issues, we propose the Adversarial Mixing Policy (AMP), organized in a min-max-rand formulation, to relax the Locally Linear Constraints in Mixup.
CE-Dedup: Cost-Effective Convolutional Neural Nets Training based on Image Deduplication
To this end, this paper proposes a framework to assess the impact of the near-duplicate images on CNN training performance, called CE-Dedup.
1213Li at SemEval-2021 Task 6: Detection of Propaganda with Multi-modal Attention and Pre-trained Models
This paper presents the solution proposed by the 1213Li team for subtask 3 in SemEval-2021 Task 6: identifying the multiple persuasion techniques used in the multi-modal content of the meme.
Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years.
Monadic Pavlovian associative learning in a backpropagation-free photonic network
Here we experimentally demonstrate a form of backpropagation-free learning using a single (or monadic) associative hardware element.
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems.
CSLNSpeech: solving extended speech separation problem with the help of Chinese sign language
We design a general deep learning network for learning the combination of three modalities, audio, face, and sign language information, for better solving the speech separation problem.
Cross-ethnicity Face Anti-spoofing Recognition Challenge: A Review
Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing.
Towards Accurate Scene Text Recognition with Semantic Reasoning Networks
Scene text image contains two levels of contents: visual texture and semantic information.
Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest
In this paper, we study the problem of out-of-distribution detection in skin disease images.
CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofing
Ethnic bias has proven to negatively affect the performance of face recognition systems, and it remains an open research problem in face anti-spoofing.
Hierarchical Context Enhanced Multi-Domain Dialogue System for Multi-domain Task Completion
Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings.
Lagrangian-Eulerian Multi-Density Topology Optimization with the Material Point Method
A quadrature-level connectivity graph-based method is adopted to avoid the artificial checkerboard issues commonly existing in multi-resolution topology optimization methods.
Computational Physics Computational Engineering, Finance, and Science Graphics
An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification
This paper describes our approach in DSTC 8 Track 4: Schema-Guided Dialogue State Tracking.
Static and Dynamic Fusion for Multi-modal Cross-ethnicity Face Anti-spoofing
Regardless of the usage of deep learning and handcrafted methods, the dynamic information from videos and the effect of cross-ethnicity are rarely considered in face anti-spoofing.
Boosting Image Recognition with Non-differentiable Constraints
In this paper, we study the problem of image recognition with non-differentiable constraints.
An End-to-end Video Text Detector with Online Tracking
Most existing methods attempt to enhance the performance of video text detection by cooperating with video text tracking, but treat these two tasks separately.
The ParallelEye Dataset: Constructing Large-Scale Artificial Scenes for Traffic Vision Research
As a result, we present a viable implementation pipeline for constructing large-scale artificial scenes for traffic vision research.
Training and Testing Object Detectors with Virtual Images
In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive labeled data.
