Search Results for author: Ge Gao

Found 30 papers, 11 papers with code

BU-NEmo: an Affective Dataset of Gun Violence News

no code implementations LREC 2022 Carley Reardon, Sejin Paik, Ge Gao, Meet Parekh, Yanling Zhao, Lei Guo, Margrit Betke, Derry Tanti Wijaya

As such, we introduce a U. S. gun violence news dataset that contains news headline and image pairings from 840 news articles with 15K high-quality, crowdsourced annotations on emotional responses to the news pairings.

Aligning LLM Agents by Learning Latent Preference from User Edits

1 code implementation23 Apr 2024 Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra

In a typical setting such as writing assistants, the user interacts with a language agent to generate a response given a context, and may optionally edit the agent response to personalize it based on their latent preference, in addition to improving the correctness.

Descriptive Language Modelling +2

NatSGD: A Dataset with Speech, Gestures, and Demonstrations for Robot Learning in Natural Human-Robot Interaction

no code implementations4 Mar 2024 Snehesh Shrestha, Yantian Zha, Saketh Banagiri, Ge Gao, Yiannis Aloimonos, Cornelia Fermuller

NatSGD serves as a foundational resource at the intersection of machine learning and HRI research, and we demonstrate its effectiveness in training robots to understand tasks through multimodal human commands, emphasizing the significance of jointly considering speech and gestures.

Emojis Decoded: Leveraging ChatGPT for Enhanced Understanding in Social Media Communications

no code implementations22 Jan 2024 YuHang Zhou, Paiheng Xu, Xiyao Wang, Xuan Lu, Ge Gao, Wei Ai

Our objective is to validate the hypothesis that ChatGPT can serve as a viable alternative to human annotators in emoji research and that its ability to explain emoji meanings can enhance clarity and transparency in online communications.

GridFormer: Point-Grid Transformer for Surface Reconstruction

1 code implementation4 Jan 2024 Shengtao Li, Ge Gao, Yudong Liu, Yu-Shen Liu, Ming Gu

Our method maximizes the spatial expressiveness of grid features and maintains computational efficiency.

Computational Efficiency Surface Reconstruction

NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views

no code implementations21 Dec 2023 Han Huang, Yulun Wu, Junsheng Zhou, Ge Gao, Ming Gu, Yu-Shen Liu

To achieve this, we train a neural network to learn a global implicit field from the on-surface points obtained from SfM and then leverage it as a coarse geometric constraint.

Surface Reconstruction valid

Accelerating Learnt Video Codecs with Gradient Decay and Layer-wise Distillation

no code implementations5 Dec 2023 Tianhao Peng, Ge Gao, Heming Sun, Fan Zhang, David Bull

In recent years, end-to-end learnt video codecs have demonstrated their potential to compete with conventional coding algorithms in term of compression efficiency.

Decoder Video Compression

Policy-Gradient Training of Language Models for Ranking

no code implementations6 Oct 2023 Ge Gao, Jonathan D. Chang, Claire Cardie, Kianté Brantley, Thorsten Joachim

Text retrieval plays a crucial role in incorporating factual knowledge for decision making into language processing pipelines, ranging from chat-based web search to question answering systems.

Decision Making Domain Generalization +3

Emoji Promotes Developer Participation and Issue Resolution on GitHub

no code implementations30 Aug 2023 YuHang Zhou, Xuan Lu, Ge Gao, Qiaozhu Mei, Wei Ai

In this paper, we study how emoji usage influences developer participation and issue resolution in virtual workspaces.

Causal Inference

HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation

1 code implementation NeurIPS 2023 Ho Man Kwan, Ge Gao, Fan Zhang, Andrew Gower, David Bull

Learning-based video compression is currently a popular research topic, offering the potential to compete with conventional standard video codecs.

Model Compression Quantization +1

Continually Improving Extractive QA via Human Feedback

1 code implementation21 May 2023 Ge Gao, Hung-Ting Chen, Yoav Artzi, Eunsol Choi

We study continually improving an extractive question answering (QA) system via human user feedback.

Domain Adaptation Extractive Question-Answering +1

An Offline Time-aware Apprenticeship Learning Framework for Evolving Reward Functions

no code implementations15 May 2023 Xi Yang, Ge Gao, Min Chi

Apprenticeship learning (AL) is a process of inducing effective decision-making policies via observing and imitating experts' demonstrations.

Decision Making

HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare

no code implementations18 Feb 2023 Ge Gao, Song Ju, Markel Sanz Ausin, Min Chi

Reinforcement learning (RL) has been extensively researched for enhancing human-environment interactions in various human-centric tasks, including e-learning and healthcare.

Off-policy evaluation

Variational Latent Branching Model for Off-Policy Evaluation

1 code implementation28 Jan 2023 Qitong Gao, Ge Gao, Min Chi, Miroslav Pajic

In this work, we propose the variational latent branching model (VLBM) to learn the transition function of MDPs by formulating the environmental dynamics as a compact latent space, from which the next states and rewards are then sampled.

Off-policy evaluation Variational Inference

Client Selection in Federated Learning: Principles, Challenges, and Opportunities

no code implementations3 Nov 2022 Lei Fu, Huanle Zhang, Ge Gao, Mi Zhang, Xin Liu

As a privacy-preserving paradigm for training Machine Learning (ML) models, Federated Learning (FL) has received tremendous attention from both industry and academia.

Fairness Federated Learning +1

Taking a Language Detour: How International Migrants Speaking a Minority Language Seek COVID-Related Information in Their Host Countries

no code implementations7 Sep 2022 Ge Gao, Jian Zheng, Eun Kyoung Choe, Naomi Yamashita

Our data indicated that participants often took language detours, or visits to Mandarin resources for information about the COVID outbreak in their host countries.

Facilitating Global Team Meetings Between Language-Based Subgroups: When and How Can Machine Translation Help?

no code implementations7 Sep 2022 Yongle Zhang, Dennis Asamoah Owusu, Marine Carpuat, Ge Gao

We manipulated the exchange of subgroup conversation logs prior to team meetings: with MT-mediated exchanges versus without.

Machine Translation

Modeling and Validating Temporal Rules with Semantic Petri-Net for Digital Twins

no code implementations4 Mar 2022 Han Liu, Xiaoyu Song, Ge Gao, Hehua Zhang, Yu-Shen Liu, Ming Gu

Semantic rule checking on RDFS/OWL data has been widely used in the construction industry.

Guidance and Teaching Network for Video Salient Object Detection

no code implementations21 May 2021 Yingxia Jiao, Xiao Wang, Yu-Cheng Chou, Shouyuan Yang, Ge-Peng Ji, Rong Zhu, Ge Gao

Owing to the difficulties of mining spatial-temporal cues, the existing approaches for video salient object detection (VSOD) are limited in understanding complex and noisy scenarios, and often fail in inferring prominent objects.

Object object-detection +2

Early Performance Prediction using Interpretable Patterns in Programming Process Data

no code implementations10 Feb 2021 Ge Gao, Samiha Marwan, Thomas W. Price

From the log data, we extract patterns of behaviors that are predictive of students' success using an approach called differential sequence mining.

Neural Image Compression via Attentional Multi-Scale Back Projection and Frequency Decomposition

no code implementations ICCV 2021 Ge Gao, Pei You, Rong pan, Shunyuan Han, Yuanyuan Zhang, Yuchao Dai, Hojae Lee

In recent years, neural image compression emerges as a rapidly developing topic in computer vision, where the state-of-the-art approaches now exhibit superior compression performance than their conventional counterparts.

Image Compression MS-SSIM +1

6D Object Pose Regression via Supervised Learning on Point Clouds

1 code implementation24 Jan 2020 Ge Gao, Mikko Lauri, Yulong Wang, Xiaolin Hu, Jianwei Zhang, Simone Frintrop

We use depth information represented by point clouds as the input to both deep networks and geometry-based pose refinement and use separate networks for rotation and translation regression.

Object regression +1

Neural Metaphor Detection in Context

1 code implementation EMNLP 2018 Ge Gao, Eunsol Choi, Yejin Choi, Luke Zettlemoyer

We present end-to-end neural models for detecting metaphorical word use in context.

Occlusion Resistant Object Rotation Regression from Point Cloud Segments

no code implementations16 Aug 2018 Ge Gao, Mikko Lauri, Jianwei Zhang, Simone Frintrop

Rotation estimation of known rigid objects is important for robotic applications such as dexterous manipulation.

Object regression

Saliency-guided Adaptive Seeding for Supervoxel Segmentation

no code implementations13 Apr 2017 Ge Gao, Mikko Lauri, Jianwei Zhang, Simone Frintrop

We propose a new saliency-guided method for generating supervoxels in 3D space.


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