Search Results for author:
Found 26 papers, 19 papers with code
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-Task Learning for Offensive Language Detection
Nowadays, offensive content in social media has become a serious problem, and automatically detecting offensive language is an essential task.
Modality-Transferable Emotion Embeddings for Low-Resource Multimodal Emotion Recognition
Despite the recent achievements made in the multi-modal emotion recognition task, two problems still exist and have not been well investigated: 1) the relationship between different emotion categories are not utilized, which leads to sub-optimal performance; and 2) current models fail to cope well with low-resource emotions, especially for unseen emotions.
Dimsum @LaySumm 20: BART-based Approach for Scientific Document Summarization
Lay summarization aims to generate lay summaries of scientific papers automatically.
Multi-hop Question Generation with Graph Convolutional Network
Multi-hop Question Generation (QG) aims to generate answer-related questions by aggregating and reasoning over multiple scattered evidence from different paragraphs.
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-TaskLearning for Offensive Language Detection
Nowadays, offensive content in social media has become a serious problem, and automatically detecting offensive language is an essential task.
CrossNER: Evaluating Cross-Domain Named Entity Recognition
Cross-domain named entity recognition (NER) models are able to cope with the scarcity issue of NER samples in target domains.
Multimodal End-to-End Sparse Model for Emotion Recognition
Existing works on multimodal affective computing tasks, such as emotion recognition, generally adopt a two-phase pipeline, first extracting feature representations for each single modality with hand-crafted algorithms and then performing end-to-end learning with the extracted features.
Weakly-supervised Multi-task Learning for Multimodal Affect Recognition
In this paper, we propose to leverage these datasets using weakly-supervised multi-task learning to improve the generalization performance on each of them.
Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization
Multimodal abstractive summarization (MAS) models that summarize videos (vision modality) and their corresponding transcripts (text modality) are able to extract the essential information from massive multimodal data on the Internet.
Greenformer: Factorization Toolkit for Efficient Deep Neural Networks
While the recent advances in deep neural networks (DNN) bring remarkable success, the computational cost also increases considerably.
ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation
ASCEND (A Spontaneous Chinese-English Dataset) is a high-quality Mandarin Chinese-English code-switching corpus built on spontaneous multi-turn conversational dialogue sources collected in Hong Kong.
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
We further conduct experiments with Fairseq S2T Transformer, a state-of-the-art ASR model, on the biggest existing dataset, Common Voice zh-HK, and our proposed MDCC, and the results show the effectiveness of our dataset.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition
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.
Survey of Hallucination in Natural Language Generation
This advancement has led to more fluent and coherent NLG, leading to improved development in downstream tasks such as abstractive summarization, dialogue generation and data-to-text generation.
Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation
Furthermore, the original textual language understanding and generation ability of the PLM is maintained after VLKD, which makes our model versatile for both multimodal and unimodal tasks.
Kaggle Competition: Cantonese Audio-Visual Speech Recognition for In-car Commands
With the rise of deep learning and intelligent vehicles, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities.
Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-training
Large-scale vision-language pre-trained (VLP) models are prone to hallucinate non-existent visual objects when generating text based on visual information.
NusaCrowd: Open Source Initiative for Indonesian NLP Resources
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
It is, for example, better at deductive than inductive reasoning.
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence.
Ranked #5 on
visual instruction following
on LLaVA-Bench
Visual Instruction Tuning with Polite Flamingo
This side effect negatively impacts the model's ability to format responses appropriately -- for instance, its "politeness" -- due to the overly succinct and unformatted nature of raw annotations, resulting in reduced human preference.
mCLIP: Multilingual CLIP via Cross-lingual Transfer
Furthermore, to enhance the token- and sentence-level multilingual representation of the MTE, we propose to train it with machine translation and contrastive learning jointly before the TriKD to provide a better initialization.
Survey of Social Bias in Vision-Language Models
This survey aims to provide researchers with a high-level insight into the similarities and differences of social bias studies in pre-trained models across NLP, CV, and VL.
Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models
Object hallucination poses a significant challenge in vision-language (VL) models, often leading to the generation of nonsensical or unfaithful responses with non-existent objects.
Dimsum @LaySumm 20
Lay summarization aims to generate lay summaries of scientific papers automatically.
CI-AVSR: A Cantonese Audio-Visual Speech Datasetfor In-car Command Recognition
With the rise of deep learning and intelligent vehicles, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities.
