1.3k citations · 2.6k across the 24 of their papers we have counts for
26 papers
Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling
Longyue Wang, Zefeng Du, Donghuai Liu +7
Modeling discourse -- the linguistic phenomena that go beyond individual sentences, is a fundamental yet challenging aspect of natural language processing (NLP). However, existing…
Speech-to-Text Adapter and Speech-to-Entity Retriever Augmented LLMs for Speech Understanding
Mingqiu Wang, Izhak Shafran, Hagen Soltau +4
Large Language Models (LLMs) have been applied in the speech domain, often incurring a performance drop due to misaligned between speech and language representations. To bridge thi…
Towards Understanding What Code Language Models Learned
Toufique Ahmed, Dian Yu, Chengxuan Huang +3
Pre-trained language models are effective in a variety of natural language tasks, but it has been argued their capabilities fall short of fully learning meaning or understanding la…
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Shunyu Yao, Dian Yu, Jeffrey Zhao +4
Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making proce…
Document-Level Machine Translation with Large Language Models
Longyue Wang, Chenyang Lyu, Tianbo Ji +4
Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level…
NarraSum: A Large-Scale Dataset for Abstractive Narrative Summarization
Chao Zhao, Faeze Brahman, Kaiqiang Song +3
Narrative summarization aims to produce a distilled version of a narrative to describe its most salient events and characters. Summarizing a narrative is challenging as it requires…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Knowledge-grounded Dialog State Tracking
Dian Yu, Mingqiu Wang, Yuan Cao +3
Knowledge (including structured knowledge such as schema and ontology, and unstructured knowledge such as web corpus) is a critical part of dialog understanding, especially for uns…
ReAct: Synergizing Reasoning and Acting in Language Models
Shunyu Yao, Jeffrey Zhao, Dian Yu +4
While large language models (LLMs) have demonstrated impressive capabilities across tasks in language understanding and interactive decision making, their abilities for reasoning (…
Using Chatbots to Teach Languages
Yu Li, Chun-Yen Chen, Dian Yu +6
This paper reports on progress towards building an online language learning tool to provide learners with conversational experience by using dialog systems as conversation practice…
Unsupervised Slot Schema Induction for Task-oriented Dialog
Dian Yu, Mingqiu Wang, Yuan Cao +3
Carefully-designed schemas describing how to collect and annotate dialog corpora are a prerequisite towards building task-oriented dialog systems. In practical applications, manual…
Learning-by-Narrating: Narrative Pre-Training for Zero-Shot Dialogue Comprehension
Chao Zhao, Wenlin Yao, Dian Yu +3
Comprehending a dialogue requires a model to capture diverse kinds of key information in the utterances, which are either scattered around or implicitly implied in different turns…
Description-Driven Task-Oriented Dialog Modeling
Jeffrey Zhao, Raghav Gupta, Yuan Cao +6
Task-oriented dialogue (TOD) systems are required to identify key information from conversations for the completion of given tasks. Such information is conventionally specified in…
Automatically Exposing Problems with Neural Dialog Models
Dian Yu, Kenji Sagae
Neural dialog models are known to suffer from problems such as generating unsafe and inconsistent responses. Even though these problems are crucial and prevalent, they are mostly m…
Language Embeddings for Typology and Cross-lingual Transfer Learning
Dian Yu, Taiqi He, Kenji Sagae
Cross-lingual language tasks typically require a substantial amount of annotated data or parallel translation data. We explore whether language representations that capture relatio…
Few-shot Intent Classification and Slot Filling with Retrieved Examples
Dian Yu, Luheng He, Yuan Zhang +3
Few-shot learning arises in important practical scenarios, such as when a natural language understanding system needs to learn new semantic labels for an emerging, resource-scarce…
Attribute Alignment: Controlling Text Generation from Pre-trained Language Models
Dian Yu, Zhou Yu, Kenji Sagae
Large language models benefit from training with a large amount of unlabeled text, which gives them increasingly fluent and diverse generation capabilities. However, using these mo…
Gunrock 2.0: A User Adaptive Social Conversational System
Kaihui Liang, Austin Chau, Yu Li +8
Gunrock 2.0 is built on top of Gunrock with an emphasis on user adaptation. Gunrock 2.0 combines various neural natural language understanding modules, including named entity detec…
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge
Kai Sun, Dian Yu, Jianshu Chen +2
In this paper, we aim to extract commonsense knowledge to improve machine reading comprehension. We propose to represent relations implicitly by situating structured knowledge in a…
A Efficient Multimodal Framework for Large Scale Emotion Recognition by Fusing Music and Electrodermal Activity Signals
Guanghao Yin, Shouqian Sun, Dian Yu +2
Considerable attention has been paid for physiological signal-based emotion recognition in field of affective computing. For the reliability and user friendly acquisition, Electrod…
Exploration Based Language Learning for Text-Based Games
Andrea Madotto, Mahdi Namazifar, Joost Huizinga +7
This work presents an exploration and imitation-learning-based agent capable of state-of-the-art performance in playing text-based computer games. Text-based computer games describ…
Filling Conversation Ellipsis for Better Social Dialog Understanding
Xiyuan Zhang, Chengxi Li, Dian Yu +2
The phenomenon of ellipsis is prevalent in social conversations. Ellipsis increases the difficulty of a series of downstream language understanding tasks, such as dialog act predic…
Gunrock: A Social Bot for Complex and Engaging Long Conversations
Dian Yu, Michelle Cohn, Yi Mang Yang +12
Gunrock is the winner of the 2018 Amazon Alexa Prize, as evaluated by coherence and engagement from both real users and Amazon-selected expert conversationalists. We focus on under…
Dependency Parsing for Spoken Dialog Systems
Sam Davidson, Dian Yu, Zhou Yu
Dependency parsing of conversational input can play an important role in language understanding for dialog systems by identifying the relationships between entities extracted from…