b'Qian Liu'

research

∙ 03/07/2022

Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models

Recently the prompt-tuning paradigm has attracted significant attention....

Shengnan An, et al. ∙

research

∙ 01/27/2022

Reasoning Like Program Executors

Reasoning over natural language is a long-standing goal for the research...

Xinyu Pi, et al. ∙

research

∙ 01/20/2022

LEMON: Language-Based Environment Manipulation via Execution-Guided Pre-training

Language-based environment manipulation requires agents to manipulate th...

Qi Shi, et al. ∙

research

∙ 12/27/2021

Image Edge Restoring Filter

In computer vision, image processing and computer graphics, image smooth...

Qian Liu, et al. ∙

research

∙ 09/22/2021

Awakening Latent Grounding from Pretrained Language Models for Semantic Parsing

Recent years pretrained language models (PLMs) hit a success on several ...

Qian Liu, et al. ∙

research

∙ 07/16/2021

TAPEX: Table Pre-training via Learning a Neural SQL Executor

Recent years pre-trained language models hit a success on modeling natur...

Qian Liu, et al. ∙

research

∙ 07/14/2021

Learning Algebraic Recombination for Compositional Generalization

Neural sequence models exhibit limited compositional generalization abil...

Chenyao Liu, et al. ∙

research

∙ 04/20/2021

Deep Learning based Efficient Symbol-Level Precoding Design for MU-MISO Systems

The recently emerged symbol-level precoding (SLP) technique has been reg...

Zhu Bo, et al. ∙

research

∙ 11/09/2020

"What Do You Mean by That?" A Parser-Independent Interactive Approach for Enhancing Text-to-SQL

In Natural Language Interfaces to Databases systems, the text-to-SQL tec...

Yuntao Li, et al. ∙

research

∙ 09/28/2020

Incomplete Utterance Rewriting as Semantic Segmentation

Recent years the task of incomplete utterance rewriting has raised a lar...

Qian Liu, et al. ∙

research

∙ 06/18/2020

Compositional Generalization by Learning Analytical Expressions

Compositional generalization is a basic but essential intellective capab...

Qian Liu, et al. ∙

research

∙ 06/02/2020

A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension

Pre-trained models have brought significant improvements to many NLP tas...

Jie Cai, et al. ∙

research

∙ 04/11/2020

You Impress Me: Dialogue Generation via Mutual Persona Perception

Despite the continuing efforts to improve the engagingness and consisten...

Qian Liu, et al. ∙

research

∙ 02/08/2020

CTM: Collaborative Temporal Modeling for Action Recognition

With the rapid development of digital multimedia, video understanding ha...

Qian Liu, et al. ∙

research

∙ 02/07/2020

iqiyi Submission to ActivityNet Challenge 2019 Kinetics-700 challenge: Hierarchical Group-wise Attention

In this report, the method for the iqiyi submission to the task of Activ...

Qian Liu, et al. ∙

research

∙ 02/03/2020

How Far are We from Effective Context Modeling ? An Exploratory Study on Semantic Parsing in Context

Recently semantic parsing in context has received a considerable attenti...

Qian Liu, et al. ∙

research

∙ 12/03/2019

Optimizing the energy consumption of spiking neural networks for neuromorphic applications

In the last few years, spiking neural networks have been demonstrated to...

Martino Sorbaro, et al. ∙

research

∙ 09/19/2019

A Split-and-Recombine Approach for Follow-up Query Analysis

Context-dependent semantic parsing has proven to be an important yet cha...

Qian Liu, et al. ∙

research

∙ 01/24/2019

FANDA: A Novel Approach to Perform Follow-up Query Analysis

Recent work on Natural Language Interfaces to Databases (NLIDB) has attr...

Qian Liu, et al. ∙

research

∙ 12/12/2018

A Hardware-Efficient Hybrid Beamforming Solution for mmWave MIMO Systems

In millimeter wave (mmWave) communication systems, existing hybrid beamf...

Ming Li, et al. ∙

research

∙ 03/31/2017

Noisy Softplus: an activation function that enables SNNs to be trained as ANNs

We extended the work of proposed activation function, Noisy Softplus, to...

Qian Liu, et al. ∙

research

∙ 07/11/2014

Biclustering Via Sparse Clustering

In many situations it is desirable to identify clusters that differ with...

Qian Liu, et al. ∙

Qian Liu

Featured Co-authors

Yu Zhang

Ting Liu

Yan Zhang

Ming Li

PetsTime

Jie Liu

Nanning Zheng

Weizhu Chen

Dongmei Zhang

Qiang Fu

Jian-Guang Lou

Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models

Reasoning Like Program Executors

LEMON: Language-Based Environment Manipulation via Execution-Guided Pre-training

Image Edge Restoring Filter

Awakening Latent Grounding from Pretrained Language Models for Semantic Parsing

TAPEX: Table Pre-training via Learning a Neural SQL Executor

Learning Algebraic Recombination for Compositional Generalization

Deep Learning based Efficient Symbol-Level Precoding Design for MU-MISO Systems

"What Do You Mean by That?" A Parser-Independent Interactive Approach for Enhancing Text-to-SQL

Incomplete Utterance Rewriting as Semantic Segmentation

Compositional Generalization by Learning Analytical Expressions

A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension

You Impress Me: Dialogue Generation via Mutual Persona Perception

CTM: Collaborative Temporal Modeling for Action Recognition

iqiyi Submission to ActivityNet Challenge 2019 Kinetics-700 challenge: Hierarchical Group-wise Attention

How Far are We from Effective Context Modeling ? An Exploratory Study on Semantic Parsing in Context

Optimizing the energy consumption of spiking neural networks for neuromorphic applications

A Split-and-Recombine Approach for Follow-up Query Analysis

FANDA: A Novel Approach to Perform Follow-up Query Analysis

A Hardware-Efficient Hybrid Beamforming Solution for mmWave MIMO Systems

Noisy Softplus: an activation function that enables SNNs to be trained as ANNs

Biclustering Via Sparse Clustering