research
∙
09/21/2023
ORTexME: Occlusion-Robust Human Shape and Pose via Temporal Average Texture and Mesh Encoding
In 3D human shape and pose estimation from a monocular video, models tra...
share
research
∙
09/14/2023
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
Learning a recommender system model from an item's raw modality features...
research
∙
09/13/2023
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Recommender systems (RS) have achieved significant success by leveraging...
research
∙
08/09/2023
Adaptive Intellect Unleashed: The Feasibility of Knowledge Transfer in Large Language Models
We conduct the first empirical study on using knowledge transfer to impr...
research
∙
06/21/2023
Prompt Sapper: A LLM-Empowered Production Tool for Building AI Chains
The emergence of foundation models, such as large language models (LLMs)...
research
∙
06/20/2023
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
Generative Pre-trained Transformer (GPT) models have exhibited exciting ...
research
∙
06/15/2023
Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling
Policy optimization methods are powerful algorithms in Reinforcement Lea...
research
∙
06/04/2023
Prompt Sapper: LLM-Empowered Software Engineering Infrastructure for AI-Native Services
Foundation models, such as GPT-4, DALL-E have brought unprecedented AI "...
research
∙
05/24/2023
GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions
Generalization to unseen tasks is an important ability for few-shot lear...
research
∙
05/19/2023
Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights
Text-based collaborative filtering (TCF) has become the mainstream appro...
research
∙
05/19/2023
DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment
Sensitivity to severe occlusion and large view angles limits the usage s...
research
∙
05/06/2023
Transform-Equivariant Consistency Learning for Temporal Sentence Grounding
This paper addresses the temporal sentence grounding (TSG). Although exi...
research
∙
03/18/2023
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Fine-tuning large pre-trained language models on downstream tasks has be...
research
∙
02/24/2023
Hiding Data Helps: On the Benefits of Masking for Sparse Coding
Sparse coding refers to modeling a signal as sparse linear combinations ...
research
∙
01/05/2023
Hypotheses Tree Building for One-Shot Temporal Sentence Localization
Given an untrimmed video, temporal sentence localization (TSL) aims to l...
research
∙
01/02/2023
Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding
Temporal sentence grounding (TSG) aims to identify the temporal boundary...
research
∙
12/01/2022
Pre-averaging fractional processes contaminated by noise, with an application to turbulence
In this article, we consider the problem of estimating fractional proces...
research
∙
10/26/2022
M^3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design
Multi-task learning (MTL) encapsulates multiple learned tasks in a singl...
research
∙
08/29/2022
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Diffusion models (DMs) have shown great potential for high-quality image...
research
∙
08/25/2022
Bottom-Up 2D Pose Estimation via Dual Anatomical Centers for Small-Scale Persons
In multi-person 2D pose estimation, the bottom-up methods simultaneously...
research
∙
07/26/2022
Learning Visual Representation from Modality-Shared Contrastive Language-Image Pre-training
Large-scale multi-modal contrastive pre-training has demonstrated great ...
research
∙
07/12/2022
Backdoor Attacks on Crowd Counting
Crowd counting is a regression task that estimates the number of people ...
research
∙
06/01/2022
Towards the Development of A Three-Dimensional SBP-SAT FDTD Method: Theory and Validation
To enhance the scalability and performance of the traditional finite-dif...
research
∙
05/23/2022
Local Byte Fusion for Neural Machine Translation
Subword tokenization schemes are the dominant technique used in current ...
research
∙
05/16/2022
Efficient Algorithms for Planning with Participation Constraints
We consider the problem of planning with participation constraints intro...
research
∙
05/03/2022
SemAttack: Natural Textual Attacks via Different Semantic Spaces
Recent studies show that pre-trained language models (LMs) are vulnerabl...
research
∙
05/02/2022
Dual networks based 3D Multi-Person Pose Estimation from Monocular Video
Monocular 3D human pose estimation has made progress in recent years. Mo...
research
∙
03/12/2022
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy
Vision transformers (ViTs) have gained increasing popularity as they are...
research
∙
02/22/2022
A Deep Reinforcement Learning based Approach for NOMA-based Random Access Network with Truncated Channel Inversion Power Control
As a main use case of 5G and Beyond wireless network, the ever-increasin...
research
∙
02/22/2022
A SBP-SAT FDTD Subgridding Method Using Staggered Yee's Grids Without Modifying Field Components
A summation-by-parts simultaneous approximation term (SBP-SAT) finite-di...
research
∙
01/14/2022
Unsupervised Temporal Video Grounding with Deep Semantic Clustering
Temporal video grounding (TVG) aims to localize a target segment in a vi...
research
∙
01/03/2022
Memory-Guided Semantic Learning Network for Temporal Sentence Grounding
Temporal sentence grounding (TSG) is crucial and fundamental for video u...
research
∙
11/04/2021
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
Large-scale pre-trained language models have achieved tremendous success...
research
∙
10/30/2021
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models
Gigantic pre-trained models have become central to natural language proc...
research
∙
10/18/2021
A Stable FDTD Subgridding Scheme with SBP-SAT for Transient Electromagnetic Analysis
We proposed a provably stable FDTD subgridding method for accurate and e...
research
∙
10/16/2021
A Good Prompt Is Worth Millions of Parameters? Low-resource Prompt-based Learning for Vision-Language Models
Large pretrained vision-language (VL) models can learn a new task with a...
research
∙
10/16/2021
What do Compressed Large Language Models Forget? Robustness Challenges in Model Compression
Recent works have focused on compressing pre-trained language models (PL...
research
∙
09/23/2021
Outlier-Robust Sparse Estimation via Non-Convex Optimization
We explore the connection between outlier-robust high-dimensional statis...
research
∙
06/08/2021
VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
Most existing video-and-language (VidL) research focuses on a single dat...
research
∙
06/08/2021
Chasing Sparsity in Vision Transformers: An End-to-End Exploration
Vision transformers (ViTs) have recently received explosive popularity, ...
research
∙
05/12/2021
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time
We study the problem of learning Bayesian networks where an ϵ-fraction o...
research
∙
04/23/2021
Playing Lottery Tickets with Vision and Language
Large-scale transformer-based pre-training has recently revolutionized v...
research
∙
04/12/2021
Automated Mechanism Design for Classification with Partial Verification
We study the problem of automated mechanism design with partial verifica...
research
∙
04/01/2021
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training
Vision-and-language pre-training has achieved impressive success in lear...
research
∙
04/01/2021
CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning
This work concerns video-language pre-training and representation learni...
research
∙
03/30/2021
The Elastic Lottery Ticket Hypothesis
Lottery Ticket Hypothesis raises keen attention to identifying sparse tr...
research
∙
03/22/2021
Adversarial Feature Augmentation and Normalization for Visual Recognition
Recent advances in computer vision take advantage of adversarial data au...
research
∙
03/22/2021
Context-aware Biaffine Localizing Network for Temporal Sentence Grounding
This paper addresses the problem of temporal sentence grounding (TSG), w...
research
∙
03/12/2021
Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning
Few-shot text classification is a fundamental NLP task in which a model ...
research
∙
02/28/2021
