ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1809.04113
  4. Cited By
Detecting egregious responses in neural sequence-to-sequence models

Detecting egregious responses in neural sequence-to-sequence models

11 September 2018
Tianxing He
James R. Glass
    AAML
ArXivPDFHTML

Papers citing "Detecting egregious responses in neural sequence-to-sequence models"

10 / 10 papers shown
Title
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation
Tianxing He
Jingyu Zhang
Tianle Wang
Sachin Kumar
Kyunghyun Cho
James R. Glass
Yulia Tsvetkov
29
44
0
20 Dec 2022
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain
  Chatbots
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
Waiman Si
Michael Backes
Jeremy Blackburn
Emiliano De Cristofaro
Gianluca Stringhini
Savvas Zannettou
Yang Zhang
26
58
0
07 Sep 2022
Automatically Exposing Problems with Neural Dialog Models
Automatically Exposing Problems with Neural Dialog Models
Dian Yu
Kenji Sagae
23
9
0
14 Sep 2021
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue
  Models
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue Models
Haochen Liu
Zhiwei Wang
Tyler Derr
Jiliang Tang
AAML
9
15
0
27 May 2020
Analyzing the Forgetting Problem in the Pretrain-Finetuning of Dialogue
  Response Models
Analyzing the Forgetting Problem in the Pretrain-Finetuning of Dialogue Response Models
Tianxing He
Jun Liu
Kyunghyun Cho
Myle Ott
Bing-Quan Liu
James R. Glass
Fuchun Peng
CLL
19
9
0
16 Oct 2019
Say What I Want: Towards the Dark Side of Neural Dialogue Models
Say What I Want: Towards the Dark Side of Neural Dialogue Models
Haochen Liu
Tyler Derr
Zitao Liu
Jiliang Tang
17
16
0
13 Sep 2019
Universal Adversarial Triggers for Attacking and Analyzing NLP
Universal Adversarial Triggers for Attacking and Analyzing NLP
Eric Wallace
Shi Feng
Nikhil Kandpal
Matt Gardner
Sameer Singh
AAML
SILM
29
835
0
20 Aug 2019
Negative Training for Neural Dialogue Response Generation
Negative Training for Neural Dialogue Response Generation
Tianxing He
James R. Glass
20
59
0
06 Mar 2019
Adversarial Attacks on Deep Learning Models in Natural Language
  Processing: A Survey
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
W. Zhang
Quan Z. Sheng
A. Alhazmi
Chenliang Li
AAML
16
57
0
21 Jan 2019
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
216
7,923
0
17 Aug 2015
1