7.1k citations · 8.9k across the 43 of their papers we have counts for
44 papers
Micro-Expression Recognition via Fine-Grained Dynamic Perception
Zhiwen Shao, Yifan Cheng, Fan Zhang +4
Facial micro-expression recognition (MER) is a challenging task, due to the transience, subtlety, and dynamics of micro-expressions (MEs). Most existing methods resort to hand-craf…
Understanding LLMs' Fluid Intelligence Deficiency: An Analysis of the ARC Task
Junjie Wu, Mo Yu, Lemao Liu +2
While LLMs have exhibited strong performance on various NLP tasks, it is noteworthy that most of these tasks rely on utilizing the vast amount of knowledge encoded in LLMs' paramet…
The Stochastic Parrot on LLM's Shoulder: A Summative Assessment of Physical Concept Understanding
Mo Yu, Lemao Liu, Junjie Wu +5
In a systematic way, we investigate a widely asked question: Do LLMs really understand what they say?, which relates to the more familiar term Stochastic Parrot. To this end, we pr…
G-VEval: A Versatile Metric for Evaluating Image and Video Captions Using GPT-4o
Tony Cheng Tong, Sirui He, Zhiwen Shao +1
Evaluation metric of visual captioning is important yet not thoroughly explored. Traditional metrics like BLEU, METEOR, CIDEr, and ROUGE often miss semantic depth, while trained me…
CurvNet: Latent Contour Representation and Iterative Data Engine for Curvature Angle Estimation
Zhiwen Shao, Yichen Yuan, Lizhuang Ma +1
Curvature angle is a quantitative measurement of a curve, in which Cobb angle is customized for spinal curvature. Automatic Cobb angle measurement from X-ray images is crucial for…
Selection-p: Self-Supervised Task-Agnostic Prompt Compression for Faithfulness and Transferability
Tsz Ting Chung, Leyang Cui, Lemao Liu +3
Large Language Models (LLMs) have demonstrated impressive capabilities in a wide range of natural language processing tasks when leveraging in-context learning. To mitigate the add…
Rethinking Targeted Adversarial Attacks For Neural Machine Translation
Junjie Wu, Lemao Liu, Wei Bi +1
Targeted adversarial attacks are widely used to evaluate the robustness of neural machine translation systems. Unfortunately, this paper first identifies a critical issue in the ex…
RoboDreamer: Learning Compositional World Models for Robot Imagination
Siyuan Zhou, Yilun Du, Jiaben Chen +3
Text-to-video models have demonstrated substantial potential in robotic decision-making, enabling the imagination of realistic plans of future actions as well as accurate environme…
Towards General Error Diagnosis via Behavioral Testing in Machine Translation
Junjie Wu, Lemao Liu, Dit-Yan Yeung
Behavioral testing offers a crucial means of diagnosing linguistic errors and assessing capabilities of NLP models. However, applying behavioral testing to machine translation (MT)…
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving
Kai Chen, Lanqing Hong, Hang Xu +2
Autonomous driving has attracted much attention over the years but turns out to be harder than expected, probably due to the difficulty of labeled data collection for model trainin…
Stereo Waterdrop Removal with Row-wise Dilated Attention
Zifan Shi, Na Fan, Dit-Yan Yeung +1
Existing vision systems for autonomous driving or robots are sensitive to waterdrops adhered to windows or camera lenses. Most recent waterdrop removal approaches take a single ima…
Multilingual and Multi-Aspect Hate Speech Analysis
Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang +2
Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual multi-aspect hate s…
Knowledge Query Network: How Knowledge Interacts with Skills
Jinseok Lee, Dit-Yan Yeung
Knowledge Tracing (KT) is to trace the knowledge of students as they solve a sequence of problems represented by their related skills. This involves abstract concepts of students'…
Movable-Object-Aware Visual SLAM via Weakly Supervised Semantic Segmentation
Ting Sun, Yuxiang Sun, Ming Liu +1
Moving objects can greatly jeopardize the performance of a visual simultaneous localization and mapping (vSLAM) system which relies on the static-world assumption. Motion removal h…
Marginalized Average Attentional Network for Weakly-Supervised Learning
Yuan Yuan, Yueming Lyu, Xi Shen +2
In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most sali…
Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues
Ting Sun, Lei Tai, Zhihan Gao +2
This paper proposes a novel weakly-supervised semantic segmentation method using image-level label only. The class-specific activation maps from the well-trained classifiers are us…
Effective Feature Learning with Unsupervised Learning for Improving the Predictive Models in Massive Open Online Courses
Mucong Ding, Kai Yang, Dit-Yan Yeung +1
The effectiveness of learning in massive open online courses (MOOCs) can be significantly enhanced by introducing personalized intervention schemes which rely on building predictiv…
Coupled Recurrent Network (CRN)
Lin Sun, Kui Jia, Yuejia Shen +3
Many semantic video analysis tasks can benefit from multiple, heterogenous signals. For example, in addition to the original RGB input sequences, sequences of optical flow are usua…
Semi-Semantic Line-Cluster Assisted Monocular SLAM for Indoor Environments
Ting Sun, Dezhen Song, Dit-Yan Yeung +1
This paper presents a novel method to reduce the scale drift for indoor monocular simultaneous localization and mapping (SLAM). We leverage the prior knowledge that in the indoor e…
Point-cloud-based place recognition using CNN feature extraction
Ting Sun, Ming Liu, Haoyang Ye +1
This paper proposes a novel point-cloud-based place recognition system that adopts a deep learning approach for feature extraction. By using a convolutional neural network pre-trai…
Machine Learning for Spatiotemporal Sequence Forecasting: A Survey
Xingjian Shi, Dit-Yan Yeung
Spatiotemporal systems are common in the real-world. Forecasting the multi-step future of these spatiotemporal systems based on the past observations, or, Spatiotemporal Sequence F…
Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization
Chun-Kit Yeung, Dit-Yan Yeung
Knowledge tracing is one of the key research areas for empowering personalized education. It is a task to model students' mastery level of a knowledge component (KC) based on their…
GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs
Jiani Zhang, Xingjian Shi, Junyuan Xie +3
We propose a new network architecture, Gated Attention Networks (GaAN), for learning on graphs. Unlike the traditional multi-head attention mechanism, which equally consumes all at…
Gesture-based Piloting of an Aerial Robot using Monocular Vision
Ting Sun, Shengyi Nie, Dit-Yan Yeung +1
Aerial robots are becoming popular among general public, and with the development of artificial intelligence (AI), there is a trend to equip aerial robots with a natural user inter…