Search Results for author: Xiang Zhou

Found 37 papers, 17 papers with code

ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness

1 code implementation21 Apr 2023 Archiki Prasad, Swarnadeep Saha, Xiang Zhou, Mohit Bansal

Multi-step reasoning ability is fundamental to many natural language tasks, yet it is unclear what constitutes a good reasoning chain and how to evaluate them.

Informativeness Natural Language Inference

Scene Style Text Editing

no code implementations20 Apr 2023 Tonghua Su, Fuxiang Yang, Xiang Zhou, Donglin Di, Zhongjie Wang, Songze Li

Specifically, QuadNet consists of four parts, namely background inpainting, style encoder, content encoder, and fusion generator.

Learning to Scale Temperature in Masked Self-Attention for Image Inpainting

no code implementations13 Feb 2023 Xiang Zhou, Yuan Zeng, Yi Gong

Recent advances in deep generative adversarial networks (GAN) and self-attention mechanism have led to significant improvements in the challenging task of inpainting large missing regions in an image.

Image Inpainting Patch Matching

Mutual Exclusivity Training and Primitive Augmentation to Induce Compositionality

1 code implementation28 Nov 2022 Yichen Jiang, Xiang Zhou, Mohit Bansal

Recent datasets expose the lack of the systematic generalization ability in standard sequence-to-sequence models.

Data Augmentation Inductive Bias +1

Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network

no code implementations9 Sep 2022 Jiayue Han, Zhiqiang Cai, Zhiyou Wu, Xiang Zhou

Thus, we propose the Residual-Quantile Adjustment (RQA) method for a better weight choice for each training sample.

Masked Part-Of-Speech Model: Does Modeling Long Context Help Unsupervised POS-tagging?

1 code implementation NAACL 2022 Xiang Zhou, Shiyue Zhang, Mohit Bansal

MPoSM can model arbitrary tag dependency and perform POS induction through the objective of masked POS reconstruction.


Improving the Adversarial Robustness of NLP Models by Information Bottleneck

1 code implementation Findings (ACL) 2022 Cenyuan Zhang, Xiang Zhou, Yixin Wan, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh

Existing studies have demonstrated that adversarial examples can be directly attributed to the presence of non-robust features, which are highly predictive, but can be easily manipulated by adversaries to fool NLP models.

Adversarial Robustness SST-2

GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models

1 code implementation14 Mar 2022 Archiki Prasad, Peter Hase, Xiang Zhou, Mohit Bansal

Providing natural language instructions in prompts is a useful new paradigm for improving task performance of large language models in a zero-shot setting.

Learn Quasi-stationary Distributions of Finite State Markov Chain

no code implementations19 Nov 2021 Zhiqiang Cai, Ling Lin, Xiang Zhou

We propose a reinforcement learning (RL) approach to compute the expression of quasi-stationary distribution.

reinforcement-learning Reinforcement Learning (RL)

Active Learning for Saddle Point Calculation

no code implementations10 Aug 2021 Shuting Gu, Hongqiao Wang, Xiang Zhou

To reduce the number of expensive computations of the true gradients, we propose an active learning framework consisting of a statistical surrogate model, Gaussian process regression (GPR) for the energy function, and a single-walker dynamics method, gentle accent dynamics (GAD), for the saddle-type transition states.

Active Learning Experimental Design +1

Sublinear Regret for Learning POMDPs

no code implementations8 Jul 2021 Yi Xiong, Ningyuan Chen, Xuefeng Gao, Xiang Zhou

We study the model-based undiscounted reinforcement learning for partially observable Markov decision processes (POMDPs).

reinforcement-learning Reinforcement Learning (RL)

Hidden Biases in Unreliable News Detection Datasets

no code implementations EACL 2021 Xiang Zhou, Heba Elfardy, Christos Christodoulopoulos, Thomas Butler, Mohit Bansal

Using the observations and experimental results, we provide practical suggestions on how to create more reliable datasets for the unreliable news detection task.

Fact Checking Selection bias

Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning

1 code implementation Findings (ACL) 2022 Xiang Zhou, Yixin Nie, Mohit Bansal

We introduce distributed NLI, a new NLU task with a goal to predict the distribution of human judgements for natural language inference.

Natural Language Inference

What Can We Learn from Collective Human Opinions on Natural Language Inference Data?

1 code implementation EMNLP 2020 Yixin Nie, Xiang Zhou, Mohit Bansal

Analysis reveals that: (1) high human disagreement exists in a noticeable amount of examples in these datasets; (2) the state-of-the-art models lack the ability to recover the distribution over human labels; (3) models achieve near-perfect accuracy on the subset of data with a high level of human agreement, whereas they can barely beat a random guess on the data with low levels of human agreement, which compose most of the common errors made by state-of-the-art models on the evaluation sets.

Natural Language Inference

Deep Reinforcement Learning for On-line Dialogue State Tracking

no code implementations22 Sep 2020 Zhi Chen, Lu Chen, Xiang Zhou, Kai Yu

To the best of our knowledge, this is the first effort to optimize the DST module within DRL framework for on-line task-oriented spoken dialogue systems.

Dialogue Management Dialogue State Tracking +4

Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn Dialogue

1 code implementation14 Sep 2020 Longxiang Liu, Zhuosheng Zhang, Hai Zhao, Xi Zhou, Xiang Zhou

A multi-turn dialogue is composed of multiple utterances from two or more different speaker roles.


Composing Answer from Multi-spans for Reading Comprehension

no code implementations14 Sep 2020 Zhuosheng Zhang, Yiqing Zhang, Hai Zhao, Xi Zhou, Xiang Zhou

This paper presents a novel method to generate answers for non-extraction machine reading comprehension (MRC) tasks whose answers cannot be simply extracted as one span from the given passages.

Machine Reading Comprehension

Towards Robustifying NLI Models Against Lexical Dataset Biases

1 code implementation ACL 2020 Xiang Zhou, Mohit Bansal

While deep learning models are making fast progress on the task of Natural Language Inference, recent studies have also shown that these models achieve high accuracy by exploiting several dataset biases, and without deep understanding of the language semantics.

Data Augmentation Natural Language Inference

The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions

1 code implementation EMNLP 2020 Xiang Zhou, Yixin Nie, Hao Tan, Mohit Bansal

For the first question, we conduct a thorough empirical study over analysis sets and find that in addition to the unstable final performance, the instability exists all along the training curve.

Model Selection Natural Language Inference +1

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM

no code implementations7 Mar 2020 Xiang Zhou, Huizhuo Yuan, Chris Junchi Li, Qingyun Sun

In this work, we put different variants of stochastic ADMM into a unified form, which includes standard, linearized and gradient-based ADMM with relaxation, and study their dynamics via a continuous-time model approach.

Regime Switching Bandits

no code implementations NeurIPS 2021 Xiang Zhou, Yi Xiong, Ningyuan Chen, Xuefeng Gao

We study a multi-armed bandit problem where the rewards exhibit regime switching.

Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution

1 code implementation25 Nov 2019 Yitong Yan, Chuangchuang Liu, Changyou Chen, Xianfang Sun, Longcun Jin, Xiang Zhou

Firstly, instead of producing a single score to discriminate images between real and fake, we propose a variant, called Fine-grained Attention Generative Adversarial Network for image super-resolution (FASRGAN), to discriminate each pixel between real and fake.

Image Super-Resolution Object Recognition

Semantics-aware BERT for Language Understanding

1 code implementation5 Sep 2019 Zhuosheng Zhang, Yuwei Wu, Hai Zhao, Zuchao Li, Shuailiang Zhang, Xi Zhou, Xiang Zhou

The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machine reading comprehension and natural language inference tasks.

Language Modelling Machine Reading Comprehension +5

DCMN+: Dual Co-Matching Network for Multi-choice Reading Comprehension

2 code implementations30 Aug 2019 Shuailiang Zhang, Hai Zhao, Yuwei Wu, Zhuosheng Zhang, Xi Zhou, Xiang Zhou

Multi-choice reading comprehension is a challenging task to select an answer from a set of candidate options when given passage and question.

Reading Comprehension

Scalable Algorithms for Learning High-Dimensional Linear Mixed Models

1 code implementation12 Mar 2018 Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee

We provide theoretical guarantees for our learning algorithms, demonstrating the robustness of parameter estimation.

Vocal Bursts Intensity Prediction

Affordable On-line Dialogue Policy Learning

no code implementations EMNLP 2017 Cheng Chang, Runzhe Yang, Lu Chen, Xiang Zhou, Kai Yu

The key to building an evolvable dialogue system in real-world scenarios is to ensure an affordable on-line dialogue policy learning, which requires the on-line learning process to be safe, efficient and economical.

Dialogue Management

On-line Dialogue Policy Learning with Companion Teaching

no code implementations EACL 2017 Lu Chen, Runzhe Yang, Cheng Chang, Zihao Ye, Xiang Zhou, Kai Yu

On-line dialogue policy learning is the key for building evolvable conversational agent in real world scenarios.

Dialogue Management

Bayesian Approximate Kernel Regression with Variable Selection

1 code implementation5 Aug 2015 Lorin Crawford, Kris C. Wood, Xiang Zhou, Sayan Mukherjee

State-of-the-art methods for genomic selection and association mapping are based on kernel regression and linear models, respectively.

Binary Classification regression +1

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