Search Results for author: Jintao Li

Found 24 papers, 7 papers with code

FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs

no code implementations8 Jan 2024 Shulin Zeng, Jun Liu, Guohao Dai, Xinhao Yang, Tianyu Fu, Hongyi Wang, Wenheng Ma, Hanbo Sun, Shiyao Li, Zixiao Huang, Yadong Dai, Jintao Li, Zehao Wang, Ruoyu Zhang, Kairui Wen, Xuefei Ning, Yu Wang

However, existing GPU and transformer-based accelerators cannot efficiently process compressed LLMs, due to the following unresolved challenges: low computational efficiency, underutilized memory bandwidth, and large compilation overheads.

Computational Efficiency Language Modelling +2

Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting

no code implementations16 Oct 2023 Qiong Nan, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Guang Yang, Jintao Li, Kai Shu

To break such a dilemma, a feasible but not well-studied solution is to leverage social contexts (e. g., comments) from historical news for training a detection model and apply it to newly emerging news without social contexts.

Fake News Detection

Combating Online Misinformation Videos: Characterization, Detection, and Future Directions

2 code implementations7 Feb 2023 Yuyan Bu, Qiang Sheng, Juan Cao, Peng Qi, Danding Wang, Jintao Li

With information consumption via online video streaming becoming increasingly popular, misinformation video poses a new threat to the health of the online information ecosystem.

Misinformation Recommendation Systems +1

Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer

no code implementations COLING 2022 Qiong Nan, Danding Wang, Yongchun Zhu, Qiang Sheng, Yuhui Shi, Juan Cao, Jintao Li

To address this issue, we propose a Domain- and Instance-level Transfer Framework for Fake News Detection (DITFEND), which could improve the performance of specific target domains.

Fake News Detection Language Modelling +2

Delving into the Frequency: Temporally Consistent Human Motion Transfer in the Fourier Space

no code implementations1 Sep 2022 Guang Yang, Wu Liu, Xinchen Liu, Xiaoyan Gu, Juan Cao, Jintao Li

To close the frequency gap between the natural and synthetic videos, we propose a novel Frequency-based human MOtion TRansfer framework, named FreMOTR, which can effectively mitigate the spatial artifacts and the temporal inconsistency of the synthesized videos.

DeepFake Detection Face Swapping

Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo

1 code implementation6 May 2022 Qiang Sheng, Juan Cao, H. Russell Bernard, Kai Shu, Jintao Li, Huan Liu

False news that spreads on social media has proliferated over the past years and has led to multi-aspect threats in the real world.

A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement

no code implementations21 Mar 2022 Yuting Yang, Pei Huang, Juan Cao, Jintao Li, Yun Lin, Jin Song Dong, Feifei Ma, Jian Zhang

Our attack technique targets the inherent vulnerabilities of NLP models, allowing us to generate samples even without interacting with the victim NLP model, as long as it is based on pre-trained language models (PLMs).

Adversarial Attack

DRAG: Dynamic Region-Aware GCN for Privacy-Leaking Image Detection

1 code implementation17 Mar 2022 Guang Yang, Juan Cao, Qiang Sheng, Peng Qi, Xirong Li, Jintao Li

However, these methods have two limitations: 1) they neglect other important elements like scenes, textures, and objects beyond the capacity of pretrained object detectors; 2) the correlation among objects is fixed, but a fixed correlation is not appropriate for all the images.

A Dual Prompt Learning Framework for Few-Shot Dialogue State Tracking

no code implementations15 Jan 2022 Yuting Yang, Wenqiang Lei, Pei Huang, Juan Cao, Jintao Li, Tat-Seng Chua

In this paper, we focus on how to utilize the language understanding and generation ability of pre-trained language models for DST.

Dialogue State Tracking Language Modelling

Quantifying Robustness to Adversarial Word Substitutions

no code implementations11 Jan 2022 Yuting Yang, Pei Huang, Feifei Ma, Juan Cao, Meishan Zhang, Jian Zhang, Jintao Li

Deep-learning-based NLP models are found to be vulnerable to word substitution perturbations.

MDFEND: Multi-domain Fake News Detection

1 code implementation4 Jan 2022 Qiong Nan, Juan Cao, Yongchun Zhu, Yanyan Wang, Jintao Li

In this paper, we first design a benchmark of fake news dataset for MFND with domain label annotated, namely Weibo21, which consists of 4, 488 fake news and 4, 640 real news from 9 different domains.

Fake News Detection

DPUV3INT8: A Compiler View to programmable FPGA Inference Engines

no code implementations8 Oct 2021 Paolo D'Alberto, Jiangsha Ma, Jintao Li, Yiming Hu, Manasa Bollavaram, Shaoxia Fang

We have a FPGA design, we make it fast, efficient, and tested for a few important examples.

The role of the cell cycle in collective cell dynamics

no code implementations14 Dec 2020 Jintao Li, Simon K. Schnyder, Matthew S. Turner, Ryoichi Yamamoto

We develop a simple model of the cell cycle, the fundamental regulatory network controlling growth and division, and couple this to the physical forces arising within the cell collective.

Biological Physics Soft Condensed Matter

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax

2 code implementations CVPR 2020 Yu Li, Tao Wang, Bingyi Kang, Sheng Tang, Chunfeng Wang, Jintao Li, Jiashi Feng

Solving long-tail large vocabulary object detection with deep learning based models is a challenging and demanding task, which is however under-explored. In this work, we provide the first systematic analysis on the underperformance of state-of-the-art models in front of long-tail distribution.

Image Classification Instance Segmentation +5

Asymmetric GAN for Unpaired Image-to-image Translation

no code implementations25 Dec 2019 Yu Li, Sheng Tang, Rui Zhang, Yongdong Zhang, Jintao Li, Shuicheng Yan

While in situations where two domains are asymmetric in complexity, i. e., the amount of information between two domains is different, these approaches pose problems of poor generation quality, mapping ambiguity, and model sensitivity.

Image-to-Image Translation Translation

Exploiting Multi-domain Visual Information for Fake News Detection

no code implementations13 Aug 2019 Peng Qi, Juan Cao, Tianyun Yang, Junbo Guo, Jintao Li

In the real world, fake-news images may have significantly different characteristics from real-news images at both physical and semantic levels, which can be clearly reflected in the frequency and pixel domain, respectively.

Fake News Detection

How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing Style

no code implementations2 Feb 2019 Yuting Yang, Juan Cao, Mingyan Lu, Jintao Li, Chia-Wen Lin

SNQAM performs excellently on predicting quality, presenting interpretable quality score and giving accessible suggestions on how to improve it according to writing guidelines we referred to.

Tree-structured Kronecker Convolutional Network for Semantic Segmentation

no code implementations12 Dec 2018 Tianyi Wu, Sheng Tang, Rui Zhang, Juan Cao, Jintao Li

Therefore, it can capture partial information and enlarge the receptive field of filters simultaneously without introducing extra parameters.

Semantic Segmentation

Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks

1 code implementation12 Dec 2017 Bo Wu, Wen-Huang Cheng, Yongdong Zhang, Qiushi Huang, Jintao Li, Tao Mei

With a joint embedding network, we obtain a unified deep representation of multi-modal user-post data in a common embedding space.

Social Media Popularity Prediction

Scale-Adaptive Convolutions for Scene Parsing

no code implementations ICCV 2017 Rui Zhang, Sheng Tang, Yongdong Zhang, Jintao Li, Shuicheng Yan

Through adding a new scale regression layer, we can dynamically infer the position-adaptive scale coefficients which are adopted to resize the convolutional patches.

regression Scene Parsing

One-Shot Fine-Grained Instance Retrieval

no code implementations4 Jul 2017 Hantao Yao, Shiliang Zhang, Yongdong Zhang, Jintao Li, Qi Tian

Aiming to conquer this issue, we propose a retrieval task named One-Shot Fine-Grained Instance Retrieval (OSFGIR).

Fine-Grained Visual Categorization Image Retrieval +1

Deep Representation Learning with Part Loss for Person Re-Identification

no code implementations4 Jul 2017 Hantao Yao, Shiliang Zhang, Yongdong Zhang, Jintao Li, Qi Tian

The representation learning risk is evaluated by the proposed part loss, which automatically generates several parts for an image, and computes the person classification loss on each part separately.

Classification General Classification +2

Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description

no code implementations CVPR 2017 Xishan Zhang, Ke Gao, Yongdong Zhang, Dongming Zhang, Jintao Li, Qi Tian

This paper contributes to: 1)The first in-depth study of the weakness inherent in data-driven static fusion methods for video captioning.

Video Captioning Video Description

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