Search Results for author: Hao Ma

Found 41 papers, 15 papers with code

Adversarial Driving Behavior Generation Incorporating Human Risk Cognition for Autonomous Vehicle Evaluation

no code implementations29 Sep 2023 Zhen Liu, Hang Gao, Hao Ma, Shuo Cai, Yunfeng Hu, Ting Qu, Hong Chen, Xun Gong

Autonomous vehicle (AV) evaluation has been the subject of increased interest in recent years both in industry and in academia.

Reinforcement Learning (RL)

Effective Long-Context Scaling of Foundation Models

1 code implementation27 Sep 2023 Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma

We also examine the impact of various design choices in the pretraining process, including the data mix and the training curriculum of sequence lengths -- our ablation experiments suggest that having abundant long texts in the pretrain dataset is not the key to achieving strong performance, and we empirically verify that long context continual pretraining is more efficient and similarly effective compared to pretraining from scratch with long sequences.

Continual Pretraining Language Modelling

Detection of brain activations induced by naturalistic stimuli in a pseudo model-driven way

no code implementations3 Dec 2022 Jiangcong Liu, Hao Ma, Yun Guan, Fan Wu, Le Xu, Yang Zhang, Lixia Tian

We evaluated the effectiveness of AINS with both statistical and predictive analyses on individual differences in sex and intelligence quotient (IQ), based on the four movie fMRI runs included in the Human Connectome Project dataset.

A Tightly Coupled LiDAR-IMU Odometry through Iterated Point-Level Undistortion

2 code implementations25 Sep 2022 Keke Liu, Hao Ma, Zemin Wang

Scan undistortion is a key module for LiDAR odometry in high dynamic environment with high rotation and translation speed.


IDPG: An Instance-Dependent Prompt Generation Method

no code implementations NAACL 2022 Zhuofeng Wu, Sinong Wang, Jiatao Gu, Rui Hou, Yuxiao Dong, V. G. Vinod Vydiswaran, Hao Ma

Prompt tuning is a new, efficient NLP transfer learning paradigm that adds a task-specific prompt in each input instance during the model training stage.

Language Modelling Natural Language Understanding +1

Heat Conduction Plate Layout Optimization using Physics-driven Convolutional Neural Networks

no code implementations21 Jan 2022 Hao Ma, Yang Sun, Mario Chiarelli

The layout optimization of the heat conduction is essential during design in engineering, especially for thermal sensible products.

RID-Noise: Towards Robust Inverse Design under Noisy Environments

1 code implementation7 Dec 2021 Jia-Qi Yang, Ke-Bin Fan, Hao Ma, De-Chuan Zhan

We also define a sample-wise weight, which can be used in the maximum weighted likelihood estimation of an inverse model based on a cINN.

Robust Design

Reducing Target Group Bias in Hate Speech Detectors

no code implementations7 Dec 2021 Darsh J Shah, Sinong Wang, Han Fang, Hao Ma, Luke Zettlemoyer

The ubiquity of offensive and hateful content on online fora necessitates the need for automatic solutions that detect such content competently across target groups.

text-classification Text Classification

UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning

1 code implementation ACL 2022 Yuning Mao, Lambert Mathias, Rui Hou, Amjad Almahairi, Hao Ma, Jiawei Han, Wen-tau Yih, Madian Khabsa

Recent parameter-efficient language model tuning (PELT) methods manage to match the performance of fine-tuning with much fewer trainable parameters and perform especially well when training data is limited.

Language Modelling Model Selection

Entailment as Few-Shot Learner

2 code implementations29 Apr 2021 Sinong Wang, Han Fang, Madian Khabsa, Hanzi Mao, Hao Ma

Large pre-trained language models (LMs) have demonstrated remarkable ability as few-shot learners.

Contrastive Learning Data Augmentation +8

On Unifying Misinformation Detection

1 code implementation NAACL 2021 Nayeon Lee, Belinda Z. Li, Sinong Wang, Pascale Fung, Hao Ma, Wen-tau Yih, Madian Khabsa

In this paper, we introduce UnifiedM2, a general-purpose misinformation model that jointly models multiple domains of misinformation with a single, unified setup.

Few-Shot Learning Misinformation

A Method of Generating Measurable Panoramic Image for Indoor Mobile Measurement System

no code implementations27 Oct 2020 Hao Ma, Jingbin Liu, Zhirong Hu, Hongyu Qiu, Dong Xu, Zemin Wang, Xiaodong Gong, Sheng Yang

This paper designs a technique route to generate high-quality panoramic image with depth information, which involves two critical research hotspots: fusion of LiDAR and image data and image stitching.

Image Stitching

A marine radioisotope gamma-ray spectrum analysis method based on Monte Carlo simulation and MLP neural network

no code implementations24 Oct 2020 Wenhan Dai, Zhi Zeng, Daowei Dou, Hao Ma, Jianping Chen, Junli Li, HUI ZHANG

We apply multilayer perceptron (MLP) to analyze the 662 keV full energy peak of Cs-137 in the seawater spectrum.

To Pretrain or Not to Pretrain: Examining the Benefits of Pretrainng on Resource Rich Tasks

no code implementations ACL 2020 Sinong Wang, Madian Khabsa, Hao Ma

Pretraining NLP models with variants of Masked Language Model (MLM) objectives has recently led to a significant improvements on many tasks.

Language Modelling text-classification +1

To Pretrain or Not to Pretrain: Examining the Benefits of Pretraining on Resource Rich Tasks

no code implementations15 Jun 2020 Sinong Wang, Madian Khabsa, Hao Ma

Pretraining NLP models with variants of Masked Language Model (MLM) objectives has recently led to a significant improvements on many tasks.

Language Modelling text-classification +1

Linformer: Self-Attention with Linear Complexity

13 code implementations8 Jun 2020 Sinong Wang, Belinda Z. Li, Madian Khabsa, Han Fang, Hao Ma

Large transformer models have shown extraordinary success in achieving state-of-the-art results in many natural language processing applications.

Language Modelling

Language Models as Fact Checkers?

no code implementations WS 2020 Nayeon Lee, Belinda Z. Li, Sinong Wang, Wen-tau Yih, Hao Ma, Madian Khabsa

Recent work has suggested that language models (LMs) store both common-sense and factual knowledge learned from pre-training data.

Common Sense Reasoning Language Modelling +2

A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural Networks

no code implementations16 May 2020 Hao Ma, Xiangyu Hu, Yuxuan Zhang, Nils Thuerey, Oskar J. Haidn

For the data-driven based method, the introduction of physical equation not only is able to speed up the convergence, but also produces physically more consistent solutions.

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

1 code implementation26 Jun 2019 Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang

Previous research shows that 1) popular network embedding benchmarks, such as DeepWalk, are in essence implicitly factorizing a matrix with a closed form, and 2)the explicit factorization of such matrix generates more powerful embeddings than existing methods.

Network Embedding

DeepInf: Social Influence Prediction with Deep Learning

1 code implementation15 Jul 2018 Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, Jie Tang

Inspired by the recent success of deep neural networks in a wide range of computing applications, we design an end-to-end framework, DeepInf, to learn users' latent feature representation for predicting social influence.

Feature Engineering Representation Learning

A Web-scale system for scientific knowledge exploration

no code implementations ACL 2018 Zhihong Shen, Hao Ma, Kuansan Wang

To enable efficient exploration of Web-scale scientific knowledge, it is necessary to organize scientific publications into a hierarchical concept structure.

Efficient Exploration TAG

Revisiting Knowledge Base Embedding as Tensor Decomposition

no code implementations ICLR 2018 Jiezhong Qiu, Hao Ma, Yuxiao Dong, Kuansan Wang, Jie Tang

We study the problem of knowledge base (KB) embedding, which is usually addressed through two frameworks---neural KB embedding and tensor decomposition.

Link Prediction Tensor Decomposition

Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

4 code implementations9 Oct 2017 Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang

This work lays the theoretical foundation for skip-gram based network embedding methods, leading to a better understanding of latent network representation learning.

Network Embedding

A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering

no code implementations29 Sep 2017 Bin Bi, Hao Ma

This paper proposes a novel neural machine reading model for open-domain question answering at scale.

Open-Domain Question Answering Passage Ranking +2

KeyVec: Key-semantics Preserving Document Representations

no code implementations27 Sep 2017 Bin Bi, Hao Ma

Previous studies have demonstrated the empirical success of word embeddings in various applications.

BIG-bench Machine Learning document understanding +1

A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations

no code implementations17 Apr 2017 Yuxiao Dong, Hao Ma, Zhihong Shen, Kuansan Wang

We find that science has benefited from the shift from individual work to collaborative effort, with over 90% of the world-leading innovations generated by collaborations in this century, nearly four times higher than they were in the 1900s.

Digital Libraries Social and Information Networks Physics and Society

An Overview of Microsoft Academic Service (MAS) and Applications

no code implementations WWW 2015 Arnab Sinha, Zhihong Shen, Yang song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, Kuansan Wang

In addition to obtaining these entities from the publisher feeds as in the previous effort, we in this version include data mining results from the Web index and an in-house knowledge base from Bing, a major commercial search engine.

An experimental study on implicit social recommendation

no code implementations SIGIR’13 2013 Hao Ma

In this paper, we study the following two research problems: (1) In some systems without explicit social information, can we still improve recommender systems using implicit social information?

Recommendation Systems

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