311 citations · 1.1k across the 79 of their papers we have counts for
22 papers · 1 filter
Deep learning for size-agnostic inverse design of random-network 3D printed mechanical metamaterials
Helda Pahlavani, Kostas Tsifoutis-Kazolis, Prerak Mody +3
Practical applications of mechanical metamaterials often involve solving inverse problems where the objective is to find the (multiple) microarchitectures that give rise to a given…
Rephrasing the Reference for Non-Autoregressive Machine Translation
Chenze Shao, Jinchao Zhang, Jie Zhou +1
Non-autoregressive neural machine translation (NAT) models suffer from the multi-modality problem that there may exist multiple possible translations of a source sentence, so the r…
AutoCAD: Automatically Generating Counterfactuals for Mitigating Shortcut Learning
Jiaxin Wen, Yeshuang Zhu, Jinchao Zhang +2
Recent studies have shown the impressive efficacy of counterfactually augmented data (CAD) for reducing NLU models' reliance on spurious features and improving their generalizabili…
MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction
Xiaozhi Wang, Yulin Chen, Ning Ding +9
The diverse relationships among real-world events, including coreference, temporal, causal, and subevent relations, are fundamental to understanding natural languages. However, two…
Demystify Transformers & Convolutions in Modern Image Deep Networks
Xiaowei Hu, Min Shi, Weiyun Wang +9
Vision transformers have gained popularity recently, leading to the development of new vision backbones with improved features and consistent performance gains. However, these adva…
Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues
Jiao Ou, Jinchao Zhang, Yang Feng +1
The construction of open-domain dialogue systems requires high-quality dialogue datasets. The dialogue data admits a wide variety of responses for a given dialogue history, especia…
Exploring Mode Connectivity for Pre-trained Language Models
Yujia Qin, Cheng Qian, Jing Yi +6
Recent years have witnessed the prevalent application of pre-trained language models (PLMs) in NLP. From the perspective of parameter space, PLMs provide generic initialization, st…
Different Tunes Played with Equal Skill: Exploring a Unified Optimization Subspace for Delta Tuning
Jing Yi, Weize Chen, Yujia Qin +6
Delta tuning (DET, also known as parameter-efficient tuning) is deemed as the new paradigm for using pre-trained language models (PLMs). Up to now, various DETs with distinct desig…
ROSE: Robust Selective Fine-tuning for Pre-trained Language Models
Lan Jiang, Hao Zhou, Yankai Lin +3
Even though the large-scale language models have achieved excellent performances, they suffer from various adversarial attacks. A large body of defense methods has been proposed. H…
From Mimicking to Integrating: Knowledge Integration for Pre-Trained Language Models
Lei Li, Yankai Lin, Xuancheng Ren +4
Investigating better ways to reuse the released pre-trained language models (PLMs) can significantly reduce the computational cost and the potential environmental side-effects. Thi…
Mixture of Attention Heads: Selecting Attention Heads Per Token
Xiaofeng Zhang, Yikang Shen, Zeyu Huang +3
Mixture-of-Experts (MoE) networks have been proposed as an efficient way to scale up model capacity and implement conditional computing. However, the study of MoE components mostly…
Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models
Zichun Yu, Tianyu Gao, Zhengyan Zhang +4
Prompting, which casts downstream applications as language modeling tasks, has shown to be sample efficient compared to standard fine-tuning with pre-trained models. However, one p…
Selecting Stickers in Open-Domain Dialogue through Multitask Learning
Zhexin Zhang, Yeshuang Zhu, Zhengcong Fei +2
With the increasing popularity of online chatting, stickers are becoming important in our online communication. Selecting appropriate stickers in open-domain dialogue requires a co…
Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense
Bowen Peng, Bo Peng, Jie Zhou +2
Deep Neural Networks (DNNs) based Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems have shown to be highly vulnerable to adversarial perturbations that are…
Manual-Guided Dialogue for Flexible Conversational Agents
Ryuichi Takanobu, Hao Zhou, Yankai Lin +3
How to build and use dialogue data efficiently, and how to deploy models in different domains at scale can be two critical issues in building a task-oriented dialogue system. In th…
Fat Pointers for Temporal Memory Safety of C
Jie Zhou, John Criswell, Michael Hicks
Temporal memory safety bugs, especially use-after-free and double free bugs, pose a major security threat to C programs. Real-world exploits utilizing these bugs enable attackers t…
Deep learning for the rare-event rational design of 3D printed multi-material mechanical metamaterials
H. Pahlavani, M. Amani, M. Cruz Saldívar +3
Emerging multi-material 3D printing techniques have paved the way for the rational design of metamaterials with not only complex geometries but also arbitrary distributions of mult…
CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation
Pei Ke, Hao Zhou, Yankai Lin +4
Existing reference-free metrics have obvious limitations for evaluating controlled text generation models. Unsupervised metrics can only provide a task-agnostic evaluation result w…
ELLE: Efficient Lifelong Pre-training for Emerging Data
Yujia Qin, Jiajie Zhang, Yankai Lin +4
Current pre-trained language models (PLM) are typically trained with static data, ignoring that in real-world scenarios, streaming data of various sources may continuously grow. Th…
Mental Health Assessment for the Chatbots
Yong Shan, Jinchao Zhang, Zekang Li +2
Previous researches on dialogue system assessment usually focus on the quality evaluation (e.g. fluency, relevance, etc) of responses generated by the chatbots, which are local and…
Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution
Bin Xia, Yapeng Tian, Yucheng Hang +3
Reference-based super-resolution (RefSR) has made significant progress in producing realistic textures using an external reference (Ref) image. However, existing RefSR methods obta…
Efficient Non-Local Contrastive Attention for Image Super-Resolution
Bin Xia, Yucheng Hang, Yapeng Tian +3
Non-Local Attention (NLA) brings significant improvement for Single Image Super-Resolution (SISR) by leveraging intrinsic feature correlation in natural images. However, NLA gives…