research
∙
09/17/2023
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles
Previous research in multi-document news summarization has typically con...
share
research
∙
06/27/2023
Next Steps for Human-Centered Generative AI: A Technical Perspective
Through iterative, cross-disciplinary discussions, we define and propose...
research
∙
05/30/2023
SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages
Text simplification research has mostly focused on sentence-level simpli...
research
∙
05/23/2023
LLMs as Factual Reasoners: Insights from Existing Benchmarks and Beyond
With the recent appearance of LLMs in practical settings, having methods...
research
∙
03/07/2023
Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation
Interpretability and efficiency are two important considerations for the...
research
∙
02/17/2023
Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questions
Modern news aggregators do the hard work of organizing a large news stre...
research
∙
12/20/2022
Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization
In long document controllable summarization, where labeled data is scarc...
research
∙
12/15/2022
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation
Human evaluation is the foundation upon which the evaluation of both sum...
research
∙
11/11/2022
Improving Factual Consistency in Summarization with Compression-Based Post-Editing
State-of-the-art summarization models still struggle to be factually con...
research
∙
11/09/2022
Discord Questions: A Computational Approach To Diversity Analysis in News Coverage
There are many potential benefits to news readers accessing diverse sour...
research
∙
10/23/2022
Conformal Predictor for Improving Zero-shot Text Classification Efficiency
Pre-trained language models (PLMs) have been shown effective for zero-sh...
research
∙
10/23/2022
Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning
Prompt tuning approaches, which learn task-specific soft prompts for a d...
research
∙
07/18/2022
Marvista: A Human-AI Collaborative Reading Tool
We present Marvista – a human-AI collaborative tool that employs a suite...
research
∙
05/13/2022
Near-Negative Distinction: Giving a Second Life to Human Evaluation Datasets
Precisely assessing the progress in natural language generation (NLG) ta...
research
∙
05/03/2022
Quiz Design Task: Helping Teachers Create Quizzes with Automated Question Generation
Question generation (QGen) models are often evaluated with standardized ...
research
∙
02/28/2022
Structure Extraction in Task-Oriented Dialogues with Slot Clustering
Extracting structure information from dialogue data can help us better u...
research
∙
12/16/2021
QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization
Factual consistency is an essential quality of text summarization models...
research
∙
12/14/2021
Exploring Neural Models for Query-Focused Summarization
Query-focused summarization (QFS) aims to produce summaries that answer ...
research
∙
10/15/2021
DialFact: A Benchmark for Fact-Checking in Dialogue
Fact-checking is an essential tool to mitigate the spread of misinformat...
research
∙
10/15/2021
MixQG: Neural Question Generation with Mixed Answer Types
Asking good questions is an essential ability for both human and machine...
research
∙
05/28/2021
Controllable Abstractive Dialogue Summarization with Sketch Supervision
In this paper, we aim to improve abstractive dialogue summarization qual...
research
∙
05/14/2021
QAConv: Question Answering on Informative Conversations
This paper introduces QAConv, a new question answering (QA) dataset that...
research
∙
10/26/2020
Improving Limited Labeled Dialogue State Tracking with Self-Supervision
Existing dialogue state tracking (DST) models require plenty of labeled ...
research
∙
10/26/2020
Probing Task-Oriented Dialogue Representation from Language Models
This paper investigates pre-trained language models to find out which mo...
research
∙
10/25/2020
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Intent detection is one of the core components of goal-oriented dialog s...
research
∙
10/05/2020
Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading
Document interpretation and dialog understanding are the two major chall...
research
∙
09/29/2020
GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
We present GraPPa, an effective pre-training approach for table semantic...
research
∙
05/26/2020
EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading
The goal of conversational machine reading is to answer user questions g...
research
∙
05/02/2020
A Simple Language Model for Task-Oriented Dialogue
Task-oriented dialogue is often decomposed into three tasks: understandi...
research
∙
04/15/2020
ToD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogues
The use of pre-trained language models has emerged as a promising direct...
research
∙
01/07/2020
Attention over Parameters for Dialogue Systems
Dialogue systems require a great deal of different but complementary exp...
research
∙
10/08/2019
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking
Dialog State Tracking (DST) is a core component in task-oriented dialog ...
research
∙
09/18/2019
Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentences
Training code-switched language models is difficult due to lack of data ...
research
∙
09/09/2019
Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement Learning
Sensational headlines are headlines that capture people's attention and ...
research
∙
08/13/2019
Getting To Know You: User Attribute Extraction from Dialogues
User attributes provide rich and useful information for user understandi...
research
∙
05/24/2019
Personalizing Dialogue Agents via Meta-Learning
Existing personalized dialogue models use human designed persona descrip...
research
∙
05/21/2019
Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
Over-dependence on domain ontology and lack of knowledge sharing across ...
research
∙
05/19/2019
Learning to Memorize in Neural Task-Oriented Dialogue Systems
In this thesis, we leverage the neural copy mechanism and memory-augment...
research
∙
01/15/2019
Global-to-local Memory Pointer Networks for Task-Oriented Dialogue
End-to-end task-oriented dialogue is challenging since knowledge bases a...
research
∙
10/30/2018
Towards End-to-end Automatic Code-Switching Speech Recognition
Speech recognition in mixed language has difficulties to adapt end-to-en...
research
∙
10/24/2018
Learn to Code-Switch: Data Augmentation using Copy Mechanism on Language Modeling
Building large-scale datasets for training code-switching language model...
research
∙
09/12/2018
Emo2Vec: Learning Generalized Emotion Representation by Multi-task Training
In this paper, we propose Emo2Vec which encodes emotional semantics into...
research
∙
05/30/2018
Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning
Lack of text data has been the major issue on code-switching language mo...
research
∙
05/30/2018
Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition
We propose an LSTM-based model with hierarchical architecture on named e...
research
∙
04/23/2018
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems
End-to-end task-oriented dialog systems usually suffer from the challeng...
research
∙
05/13/2016