Search Results for author: Zhiwei Deng

Found 32 papers, 14 papers with code

ICONS: Influence Consensus for Vision-Language Data Selection

no code implementations31 Dec 2024 Xindi Wu, Mengzhou Xia, Rulin Shao, Zhiwei Deng, Pang Wei Koh, Olga Russakovsky

In this work, we introduce ICONS, a gradient-driven Influence CONsensus approach for vision-language data Selection that selects a compact training dataset for efficient multi-task training.

Language Modeling Language Modelling

Influential Language Data Selection via Gradient Trajectory Pursuit

no code implementations22 Oct 2024 Zhiwei Deng, Tao Li, Yang Li

Curating a desirable dataset for training has been the core of building highly capable large language models (Touvron et al., 2023; Achiam et al., 2023; Team et al., 2024).

A Label is Worth a Thousand Images in Dataset Distillation

1 code implementation15 Jun 2024 Tian Qin, Zhiwei Deng, David Alvarez-Melis

Understanding how and why data distillation methods work is vital not only for improving these methods but also for revealing fundamental characteristics of "good" training data.

Dataset Distillation

What is Dataset Distillation Learning?

1 code implementation6 Jun 2024 William Yang, Ye Zhu, Zhiwei Deng, Olga Russakovsky

We reveal distilled data cannot serve as a substitute for real data during training outside the standard evaluation setting for dataset distillation.

Dataset Distillation

Devil's Advocate: Anticipatory Reflection for LLM Agents

no code implementations25 May 2024 Haoyu Wang, Tao Li, Zhiwei Deng, Dan Roth, Yang Li

The experimental results suggest that our introspection-driven approach not only enhances the agent's ability to navigate unanticipated challenges through a robust mechanism of plan execution, but also improves efficiency by reducing the number of trials and plan revisions by 45% needed to achieve a task.

Navigate

TauAD: MRI-free Tau Anomaly Detection in PET Imaging via Conditioned Diffusion Models

no code implementations21 May 2024 Lujia Zhong, Shuo Huang, Jiaxin Yue, Jianwei Zhang, Zhiwei Deng, Wenhao Chi, Yonggang Shi

By classifying the A4 subjects according to their anomaly map using the SVM trained on ADNI data, we show that our method can successfully group preclinical subjects with significantly different cognitive functions, which further demonstrates the effectiveness of our method in capturing biologically relevant anomaly in tau PET imaging.

Anomaly Detection Anomaly Localization

Perceptual Group Tokenizer: Building Perception with Iterative Grouping

no code implementations30 Nov 2023 Zhiwei Deng, Ting Chen, Yang Li

In this paper, we propose the Perceptual Group Tokenizer, a model that entirely relies on grouping operations to extract visual features and perform self-supervised representation learning, where a series of grouping operations are used to iteratively hypothesize the context for pixels or superpixels to refine feature representations.

Representation Learning Self-Supervised Image Classification +2

Discovery and Expansion of New Domains within Diffusion Models

no code implementations13 Oct 2023 Ye Zhu, Yu Wu, Duo Xu, Zhiwei Deng, Yan Yan, Olga Russakovsky

In this work, we study the generalization properties of diffusion models in a few-shot setup, introduce a novel tuning-free paradigm to synthesize the target out-of-domain (OOD) data, and demonstrate its advantages compared to existing methods in data-sparse scenarios with large domain gaps.

Denoising Image Generation

A Zero-Shot Language Agent for Computer Control with Structured Reflection

no code implementations12 Oct 2023 Tao Li, Gang Li, Zhiwei Deng, Bryan Wang, Yang Li

To perform a task, recent works often require a model to learn from trace examples of the task via either supervised learning or few/many-shot prompting.

Management

Vision-Language Dataset Distillation

2 code implementations15 Aug 2023 Xindi Wu, Byron Zhang, Zhiwei Deng, Olga Russakovsky

In this work, we design the first vision-language dataset distillation method, building on the idea of trajectory matching.

Dataset Distillation Image Classification +3

Boundary Guided Learning-Free Semantic Control with Diffusion Models

1 code implementation NeurIPS 2023 Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan

Applying pre-trained generative denoising diffusion models (DDMs) for downstream tasks such as image semantic editing usually requires either fine-tuning DDMs or learning auxiliary editing networks in the existing literature.

Denoising

Adaptive Appearance Rendering

1 code implementation24 Apr 2021 Mengyao Zhai, Ruizhi Deng, Jiacheng Chen, Lei Chen, Zhiwei Deng, Greg Mori

Hence, we develop an approach based on intermediate representations of poses and appearance: our pose-guided appearance rendering network firstly encodes the targets' poses using an encoder-decoder neural network.

Decoder Video Generation

BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps

1 code implementation ACL 2020 Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha

To this end, we propose BabyWalk, a new VLN agent that is learned to navigate by decomposing long instructions into shorter ones (BabySteps) and completing them sequentially.

Imitation Learning Navigate +1

Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation

no code implementations31 Mar 2020 Felix Yu, Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky

In the Vision-and-Language Navigation (VLN) task, an agent with egocentric vision navigates to a destination given natural language instructions.

Vision and Language Navigation

Policy Message Passing: A New Algorithm for Probabilistic Graph Inference

no code implementations ICLR 2020 Zhiwei Deng, Greg Mori

A general graph-structured neural network architecture operates on graphs through two core components: (1) complex enough message functions; (2) a fixed information aggregation process.

Continuous Graph Flow

no code implementations7 Aug 2019 Zhiwei Deng, Megha Nawhal, Lili Meng, Greg Mori

In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data.

Density Estimation Graph Generation

Structured Label Inference for Visual Understanding

1 code implementation18 Feb 2018 Nelson Nauata, Hexiang Hu, Guang-Tong Zhou, Zhiwei Deng, Zicheng Liao, Greg Mori

In this paper, we exploit this rich structure for performing graph-based inference in label space for a number of tasks: multi-label image and video classification and action detection in untrimmed videos.

Action Detection General Classification +3

Sparsely Aggregated Convolutional Networks

2 code implementations ECCV 2018 Ligeng Zhu, Ruizhi Deng, Michael Maire, Zhiwei Deng, Greg Mori, Ping Tan

We explore a key architectural aspect of deep convolutional neural networks: the pattern of internal skip connections used to aggregate outputs of earlier layers for consumption by deeper layers.

Factorized Variational Autoencoders for Modeling Audience Reactions to Movies

no code implementations CVPR 2017 Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain Matthews, Greg Mori

Matrix and tensor factorization methods are often used for finding underlying low-dimensional patterns from noisy data.

Active Learning for Structured Prediction from Partially Labeled Data

no code implementations7 Jun 2017 Mehran Khodabandeh, Zhiwei Deng, Mostafa S. Ibrahim, Shinichi Satoh, Greg Mori

We propose a general purpose active learning algorithm for structured prediction, gathering labeled data for training a model that outputs a set of related labels for an image or video.

Active Learning Prediction +1

Generic Tubelet Proposals for Action Localization

no code implementations30 May 2017 Jiawei He, Mostafa S. Ibrahim, Zhiwei Deng, Greg Mori

Our class-independent TPN outperforms other tubelet generation methods, and our unified temporal deep network achieves state-of-the-art localization results on all three datasets.

Action Classification Action Localization +1

LabelBank: Revisiting Global Perspectives for Semantic Segmentation

1 code implementation29 Mar 2017 Hexiang Hu, Zhiwei Deng, Guang-Tong Zhou, Fei Sha, Greg Mori

We advocate that holistic inference of image concepts provides valuable information for detailed pixel labeling.

Segmentation Semantic Segmentation

Recalling Holistic Information for Semantic Segmentation

no code implementations24 Nov 2016 Hexiang Hu, Zhiwei Deng, Guang-Tong Zhou, Fei Sha, Greg Mori

We advocate that high-recall holistic inference of image concepts provides valuable information for detailed pixel labeling.

Segmentation Semantic Segmentation

Hierarchical Deep Temporal Models for Group Activity Recognition

1 code implementation9 Jul 2016 Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori

In order to model both person-level and group-level dynamics, we present a 2-stage deep temporal model for the group activity recognition problem.

Group Activity Recognition

A Hierarchical Deep Temporal Model for Group Activity Recognition

1 code implementation CVPR 2016 Moustafa Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori

In group activity recognition, the temporal dynamics of the whole activity can be inferred based on the dynamics of the individual people representing the activity.

Group Activity Recognition

Deep Structured Models For Group Activity Recognition

no code implementations12 Jun 2015 Zhiwei Deng, Mengyao Zhai, Lei Chen, Yuhao Liu, Srikanth Muralidharan, Mehrsan Javan Roshtkhari, Greg Mori

This paper presents a deep neural-network-based hierarchical graphical model for individual and group activity recognition in surveillance scenes.

Group Activity Recognition

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