b'Jie Tang'

research

∙ 09/13/2023

SafetyBench: Evaluating the Safety of Large Language Models with Multiple Choice Questions

With the rapid development of Large Language Models (LLMs), increasing a...

0 Zhexin Zhang, et al. ∙

research

∙ 09/06/2023

GPT Can Solve Mathematical Problems Without a Calculator

Previous studies have typically assumed that large language models are u...

0 Zhen Yang, et al. ∙

research

∙ 09/04/2023

Relay Diffusion: Unifying diffusion process across resolutions for image synthesis

Diffusion models achieved great success in image synthesis, but still fa...

0 Jiayan Teng, et al. ∙

research

∙ 08/28/2023

LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding

Although large language models (LLMs) demonstrate impressive performance...

0 Yushi Bai, et al. ∙

research

∙ 08/09/2023

Robust Object Modeling for Visual Tracking

Object modeling has become a core part of recent tracking frameworks. Cu...

0 Yidong Cai, et al. ∙

research

∙ 08/07/2023

AgentBench: Evaluating LLMs as Agents

Large Language Models (LLMs) are becoming increasingly smart and autonom...

0 Xiao Liu, et al. ∙

research

∙ 07/31/2023

Lightweight Super-Resolution Head for Human Pose Estimation

Heatmap-based methods have become the mainstream method for pose estimat...

0 Haonan Wang, et al. ∙

research

∙ 06/27/2023

MAE-GEBD:Winning the CVPR'2023 LOVEU-GEBD Challenge

The Generic Event Boundary Detection (GEBD) task aims to build a model f...

0 Yuanxi Sun, et al. ∙

research

∙ 06/15/2023

KoLA: Carefully Benchmarking World Knowledge of Large Language Models

The unprecedented performance of large language models (LLMs) necessitat...

0 Jifan Yu, et al. ∙

research

∙ 06/13/2023

WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences

We present WebGLM, a web-enhanced question-answering system based on the...

0 Xiao Liu, et al. ∙

research

∙ 06/11/2023

GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model

Currently, the reduction in the parameter scale of large-scale pre-train...

0 Shicheng Tan, et al. ∙

research

∙ 06/11/2023

Are Intermediate Layers and Labels Really Necessary? A General Language Model Distillation Method

The large scale of pre-trained language models poses a challenge for the...

0 Shicheng Tan, et al. ∙

research

∙ 06/06/2023

BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs

In-Batch contrastive learning is a state-of-the-art self-supervised meth...

0 Zhen Yang, et al. ∙

research

∙ 05/31/2023

Confidential Signal Cancellation Phenomenon in Interference Alignment Networks: Cause and Cure

This paper investigates physical layer security (PLS) in wireless interf...

0 Lin Hu, et al. ∙

research

∙ 05/28/2023

Optimizing Airbnb Search Journey with Multi-task Learning

At Airbnb, an online marketplace for stays and experiences, guests often...

0 Chun How Tan, et al. ∙

research

∙ 05/24/2023

Revisiting Parallel Context Windows: A Frustratingly Simple Alternative and Chain-of-Thought Deterioration

We identify two crucial limitations in the evaluation of recent parallel...

0 Kejuan Yang, et al. ∙

research

∙ 04/26/2023

Video Frame Interpolation with Densely Queried Bilateral Correlation

Video Frame Interpolation (VFI) aims to synthesize non-existent intermed...

0 Chang Zhou, et al. ∙

research

∙ 04/12/2023

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

We present ImageReward – the first general-purpose text-to-image human p...

5 Jiazheng Xu, et al. ∙

research

∙ 04/10/2023

GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner

Graph self-supervised learning (SSL), including contrastive and generati...

0 Zhenyu Hou, et al. ∙

research

∙ 04/05/2023

MoocRadar: A Fine-grained and Multi-aspect Knowledge Repository for Improving Cognitive Student Modeling in MOOCs

Student modeling, the task of inferring a student's learning characteris...

0 Jifan Yu, et al. ∙

research

∙ 03/26/2023

GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation

Despite the recent emergence of video captioning models, how to generate...

0 Ji Qi, et al. ∙

research

∙ 01/31/2023

Scaling laws for single-agent reinforcement learning

Recent work has shown that, in generative modeling, cross-entropy loss i...

0 Jacob Hilton, et al. ∙

research

∙ 11/30/2022

From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-Resolution

Image super-resolution (SR) serves as a fundamental tool for the process...

0 Jie Liu, et al. ∙

research

∙ 11/21/2022

AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments

Under the Autonomous Mobile Clinics (AMCs) initiative, we are developing...

0 Tim Tianyi Yang, et al. ∙

research

∙ 10/30/2022

Parameter-Efficient Tuning Makes a Good Classification Head

In recent years, pretrained models revolutionized the paradigm of natura...

0 Zhuoyi Yang, et al. ∙

research

∙ 10/05/2022

GLM-130B: An Open Bilingual Pre-trained Model

We introduce GLM-130B, a bilingual (English and Chinese) pre-trained lan...

8 Aohan Zeng, et al. ∙

research

∙ 08/16/2022

Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries

Knowledge graph (KG) embeddings have been a mainstream approach for reas...

0 Xiao Liu, et al. ∙

research

∙ 07/18/2022

Towards a General Pre-training Framework for Adaptive Learning in MOOCs

Adaptive learning aims to stimulate and meet the needs of individual lea...

0 Qingyang Zhong, et al. ∙

research

∙ 07/14/2022

Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers

Prompt tuning attempts to update few task-specific parameters in pre-tra...

0 Weng Lam Tam, et al. ∙

research

∙ 06/23/2022

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos

Pretraining on noisy, internet-scale datasets has been heavily studied a...

0 Bowen Baker, et al. ∙

research

∙ 06/22/2022

GACT: Activation Compressed Training for General Architectures

Training large neural network (NN) models requires extensive memory reso...

0 Xiaoxuan Liu, et al. ∙

research

∙ 06/17/2022

Masked Autoencoders for Generic Event Boundary Detection CVPR'2022 Kinetics-GEBD Challenge

Generic Event Boundary Detection (GEBD) tasks aim at detecting generic, ...

0 Rui He, et al. ∙

research

∙ 05/29/2022

CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Large-scale pretrained transformers have created milestones in text (GPT...

0 Wenyi Hong, et al. ∙

research

∙ 05/28/2022

Rethinking the Setting of Semi-supervised Learning on Graphs

We argue that the present setting of semisupervised learning on graphs m...

6 Ziang Li, et al. ∙

research

∙ 05/22/2022

GraphMAE: Self-Supervised Masked Graph Autoencoders

Self-supervised learning (SSL) has been extensively explored in recent y...

0 Zhenyu Hou, et al. ∙

research

∙ 05/21/2022

DeepStruct: Pretraining of Language Models for Structure Prediction

We introduce a method for improving the structural understanding abiliti...

0 Chenguang Wang, et al. ∙

research

∙ 04/28/2022

CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers

The development of the transformer-based text-to-image models are impede...

0 Ming Ding, et al. ∙

research

∙ 04/18/2022

Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution

Runtime and memory consumption are two important aspects for efficient i...

0 Zongcai Du, et al. ∙

research

∙ 03/22/2022

WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models

Compared with the domain-specific model, the vision-language pre-trainin...

0 Sha Yuan, et al. ∙

research

∙ 03/17/2022

EVA2.0: Investigating Open-Domain Chinese Dialogue Systems with Large-Scale Pre-Training

Large-scale pre-training has shown remarkable performance in building op...

0 Yuxian Gu, et al. ∙

research

∙ 03/12/2022

GRAND+: Scalable Graph Random Neural Networks

Graph neural networks (GNNs) have been widely adopted for semi-supervise...

0 Wenzheng Feng, et al. ∙

research

∙ 03/08/2022

Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks

Massive open online courses (MOOCs), which provide a large-scale interac...

0 Jibing Gong, et al. ∙

research

∙ 03/02/2022

SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs

Entity alignment, aiming to identify equivalent entities across differen...

0 Xiao Liu, et al. ∙

research

∙ 01/14/2022

Training Free Graph Neural Networks for Graph Matching

We present TFGM (Training Free Graph Matching), a framework to boost the...

12 Zhiyuan Liu, et al. ∙

research

∙ 12/30/2021

Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks

Heterogeneous graph neural networks (HGNNs) have been blossoming in rece...

16 Qingsong Lv, et al. ∙

research

∙ 12/08/2021

Improving the Training of Graph Neural Networks with Consistency Regularization

Graph neural networks (GNNs) have achieved notable success in the semi-s...

0 Chenhui Zhang, et al. ∙

research

∙ 11/27/2021

AdaDM: Enabling Normalization for Image Super-Resolution

Normalization like Batch Normalization (BN) is a milestone technique to ...

31 Jie Liu, et al. ∙

research

∙ 11/21/2021

Network representation learning: A macro and micro view

Graph is a universe data structure that is widely used to organize data ...

0 Xueyi Liu, et al. ∙

research

∙ 11/08/2021

Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning

Adversarial attacks on graphs have posed a major threat to the robustnes...

0 Qinkai Zheng, et al. ∙

research

∙ 10/25/2021

NetMF+: Network Embedding Based on Fast and Effective Single-Pass Randomized Matrix Factorization

In this work, we propose NetMF+, a fast, memory-efficient, scalable, and...

0 Yuyang Xie, et al. ∙

Jie Tang

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