97 citations · 350 across the 22 of their papers we have counts for
24 papers
LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models
Peng Xu, Wenqi Shao, Kaipeng Zhang +7
Large Vision-Language Models (LVLMs) have recently played a dominant role in multimodal vision-language learning. Despite the great success, it lacks a holistic evaluation of their…
Adaptive Multi-Modal Cross-Entropy Loss for Stereo Matching
Peng Xu, Zhiyu Xiang, Chenyu Qiao +2
Despite the great success of deep learning in stereo matching, recovering accurate disparity maps is still challenging. Currently, L1 and cross-entropy are the two most widely used…
SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anything
Ge-Peng Ji, Deng-Ping Fan, Peng Xu +3
Segmenting anything is a ground-breaking step toward artificial general intelligence, and the Segment Anything Model (SAM) greatly fosters the foundation models for computer vision…
How to Understand Masked Autoencoders
Shuhao Cao, Peng Xu, David A. Clifton
"Masked Autoencoders (MAE) Are Scalable Vision Learners" revolutionizes the self-supervised learning method in that it not only achieves the state-of-the-art for image pre-training…
Unsupervised Long-Term Person Re-Identification with Clothes Change
Mingkun Li, Shupeng Cheng, Peng Xu +3
We investigate unsupervised person re-identification (Re-ID) with clothes change, a new challenging problem with more practical usability and scalability to real-world deployment.…
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
Tiezheng Yu, Rita Frieske, Peng Xu +9
Automatic speech recognition (ASR) on low resource languages improves the access of linguistic minorities to technological advantages provided by artificial intelligence (AI). In t…
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition
Wenliang Dai, Samuel Cahyawijaya, Tiezheng Yu +10
With the rise of deep learning and intelligent vehicle, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-car…
Hierarchical Neural Data Synthesis for Semantic Parsing
Wei Yang, Peng Xu, Yanshuai Cao
Semantic parsing datasets are expensive to collect. Moreover, even the questions pertinent to a given domain, which are the input of a semantic parsing system, might not be readily…
ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation
Holy Lovenia, Samuel Cahyawijaya, Genta Indra Winata +11
Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken la…
Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning
Dhruv Shah, Peng Xu, Yao Lu +4
Reinforcement learning can train policies that effectively perform complex tasks. However for long-horizon tasks, the performance of these methods degrades with horizon, often nece…
Contrastive Document Representation Learning with Graph Attention Networks
Peng Xu, Xinchi Chen, Xiaofei Ma +2
Recent progress in pretrained Transformer-based language models has shown great success in learning contextual representation of text. However, due to the quadratic self-attention…
Attention-guided Generative Models for Extractive Question Answering
Peng Xu, Davis Liang, Zhiheng Huang +1
We propose a novel method for applying Transformer models to extractive question answering (QA) tasks. Recently, pretrained generative sequence-to-sequence (seq2seq) models have ac…
Multiplicative Position-aware Transformer Models for Language Understanding
Zhiheng Huang, Davis Liang, Peng Xu +1
Transformer models, which leverage architectural improvements like self-attention, perform remarkably well on Natural Language Processing (NLP) tasks. The self-attention mechanism…
Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answering
Alexander Hanbo Li, Patrick Ng, Peng Xu +3
The current state-of-the-art generative models for open-domain question answering (ODQA) have focused on generating direct answers from unstructured textual information. However, a…
Cross-lingual Spoken Language Understanding with Regularized Representation Alignment
Zihan Liu, Genta Indra Winata, Peng Xu +2
Despite the promising results of current cross-lingual models for spoken language understanding systems, they still suffer from imperfect cross-lingual representation alignments be…
Improve Transformer Models with Better Relative Position Embeddings
Zhiheng Huang, Davis Liang, Peng Xu +1
Transformer architectures rely on explicit position encodings in order to preserve a notion of word order. In this paper, we argue that existing work does not fully utilize positio…
Embedding-based Zero-shot Retrieval through Query Generation
Davis Liang, Peng Xu, Siamak Shakeri +4
Passage retrieval addresses the problem of locating relevant passages, usually from a large corpus, given a query. In practice, lexical term-matching algorithms like BM25 are popul…
EmoGraph: Capturing Emotion Correlations using Graph Networks
Peng Xu, Zihan Liu, Genta Indra Winata +2
Most emotion recognition methods tackle the emotion understanding task by considering individual emotion independently while ignoring their fuzziness nature and the interconnection…
TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding
Zhiheng Huang, Peng Xu, Davis Liang +2
Bidirectional Encoder Representations from Transformers (BERT) has recently achieved state-of-the-art performance on a broad range of NLP tasks including sentence classification, m…
SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong
Steven Schwarcz, Peng Xu, David D'Ambrosio +4
We introduce a new high resolution, high frame rate stereo video dataset, which we call SPIN, for tracking and action recognition in the game of ping pong. The corpus consists of p…
Boosting Image Recognition with Non-differentiable Constraints
Xuan Li, Yuchen Lu, Peng Xu +3
In this paper, we study the problem of image recognition with non-differentiable constraints. A lot of real-life recognition applications require a rich output structure with deter…
CAiRE: An Empathetic Neural Chatbot
Zhaojiang Lin, Peng Xu, Genta Indra Winata +4
In this paper, we present an end-to-end empathetic conversation agent CAiRE. Our system adapts TransferTransfo (Wolf et al., 2019) learning approach that fine-tunes a large-scale p…
Passage Ranking with Weak Supervision
Peng Xu, Xiaofei Ma, Ramesh Nallapati +1
In this paper, we propose a \textit{weak supervision} framework for neural ranking tasks based on the data programming paradigm \citep{Ratner2016}, which enables us to leverage mul…
Anomaly Detection for Skin Disease Images Using Variational Autoencoder
Yuchen Lu, Peng Xu
In this paper, we demonstrate the potential of applying Variational Autoencoder (VAE) [10] for anomaly detection in skin disease images. VAE is a class of deep generative models wh…