113 citations · 220 across the 29 of their papers we have counts for
30 papers
Joint Active User Detection, Channel Estimation, and Data Detection for Massive Grant-Free Transmission in Cell-Free Systems
Gangle Sun, Mengyao Cao, Wenjin Wang +2
Cell-free communication has the potential to significantly improve grant-free transmission in massive machine-type communication, wherein multiple access points jointly serve a lar…
Thresh: A Unified, Customizable and Deployable Platform for Fine-Grained Text Evaluation
David Heineman, Yao Dou, Wei Xu
Fine-grained, span-level human evaluation has emerged as a reliable and robust method for evaluating text generation tasks such as summarization, simplification, machine translatio…
Improved Instruction Ordering in Recipe-Grounded Conversation
Duong Minh Le, Ruohao Guo, Wei Xu +1
In this paper, we study the task of instructional dialogue and focus on the cooking domain. Analyzing the generated output of the GPT-J model, we reveal that the primary challenge…
Revisiting non-English Text Simplification: A Unified Multilingual Benchmark
Michael J. Ryan, Tarek Naous, Wei Xu
Recent advancements in high-quality, large-scale English resources have pushed the frontier of English Automatic Text Simplification (ATS) research. However, less work has been don…
Teaching the Pre-trained Model to Generate Simple Texts for Text Simplification
Renliang Sun, Wei Xu, Xiaojun Wan
Randomly masking text spans in ordinary texts in the pre-training stage hardly allows models to acquire the ability to generate simple texts. It can hurt the performance of pre-tra…
Semantic-aware Digital Twin for Metaverse: A Comprehensive Review
Senthil Kumar Jagatheesaperumal, Zhaohui Yang, Qianqian Yang +4
To facilitate the deployment of digital twins in Metaverse, the paradigm with semantic awareness has been proposed as a means for enabling accurate and task-oriented information ex…
Meta-Tuning LLMs to Leverage Lexical Knowledge for Generalizable Language Style Understanding
Ruohao Guo, Wei Xu, Alan Ritter
Language style is often used by writers to convey their intentions, identities, and mastery of language. In this paper, we show that current large language models struggle to captu…
ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability Assessment
Tarek Naous, Michael J. Ryan, Anton Lavrouk +2
We present a comprehensive evaluation of large language models for multilingual readability assessment. Existing evaluation resources lack domain and language diversity, limiting t…
Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA
David Heineman, Yao Dou, Mounica Maddela +1
Large language models (e.g., GPT-4) are uniquely capable of producing highly rated text simplification, yet current human evaluation methods fail to provide a clear understanding o…
Multilingual Simplification of Medical Texts
Sebastian Joseph, Kathryn Kazanas, Keziah Reina +4
Automated text simplification aims to produce simple versions of complex texts. This task is especially useful in the medical domain, where the latest medical findings are typicall…
Distill or Annotate? Cost-Efficient Fine-Tuning of Compact Models
Junmo Kang, Wei Xu, Alan Ritter
Fine-tuning large models is highly effective, however, inference can be expensive and produces carbon emissions. Knowledge distillation has been shown to be a practical solution to…
LENS: A Learnable Evaluation Metric for Text Simplification
Mounica Maddela, Yao Dou, David Heineman +1
Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation. However, existing human eval…
Human-in-the-loop Evaluation for Early Misinformation Detection: A Case Study of COVID-19 Treatments
Ethan Mendes, Yang Chen, Wei Xu +1
We present a human-in-the-loop evaluation framework for fact-checking novel misinformation claims and identifying social media messages that support them. Our approach extracts che…
Improving Large-scale Paraphrase Acquisition and Generation
Yao Dou, Chao Jiang, Wei Xu
This paper addresses the quality issues in existing Twitter-based paraphrase datasets, and discusses the necessity of using two separate definitions of paraphrase for identificatio…
Frustratingly Easy Label Projection for Cross-lingual Transfer
Yang Chen, Chao Jiang, Alan Ritter +1
Translating training data into many languages has emerged as a practical solution for improving cross-lingual transfer. For tasks that involve span-level annotations, such as infor…
arXivEdits: Understanding the Human Revision Process in Scientific Writing
Chao Jiang, Wei Xu, Samuel Stevens
Scientific publications are the primary means to communicate research discoveries, where the writing quality is of crucial importance. However, prior work studying the human editin…
Stanceosaurus: Classifying Stance Towards Multilingual Misinformation
Jonathan Zheng, Ashutosh Baheti, Tarek Naous +2
We present Stanceosaurus, a new corpus of 28,033 tweets in English, Hindi, and Arabic annotated with stance towards 251 misinformation claims. As far as we are aware, it is the lar…
NFGen: Automatic Non-linear Function Evaluation Code Generator for General-purpose MPC Platforms
Xiaoyu Fan, Kun Chen, Guosai Wang +3
Due to the absence of a library for non-linear function evaluation, so-called general-purpose secure multi-party computation (MPC) are not as ''general'' as MPC programmers expect.…
Regret Bounds for Risk-Sensitive Reinforcement Learning
O. Bastani, Y. J. Ma, E. Shen +1
In safety-critical applications of reinforcement learning such as healthcare and robotics, it is often desirable to optimize risk-sensitive objectives that account for tail outcome…
Deployment of long distance multi-moving robots for underground pipe inspection
Weiyao Lai, Wei Xu, Marc Bernhard
Blueprint of an in-pipe climbing robot that works with sharp transmissions to study complex line relationships. Standard wheeled/happening pipe climbing robots tend to slide when e…
BiSECT: Learning to Split and Rephrase Sentences with Bitexts
Joongwon Kim, Mounica Maddela, Reno Kriz +2
An important task in NLP applications such as sentence simplification is the ability to take a long, complex sentence and split it into shorter sentences, rephrasing as necessary.…
Pre-train or Annotate? Domain Adaptation with a Constrained Budget
Fan Bai, Alan Ritter, Wei Xu
Recent work has demonstrated that pre-training in-domain language models can boost performance when adapting to a new domain. However, the costs associated with pre-training raise…
Pre-training for Ad-hoc Retrieval: Hyperlink is Also You Need
Zhengyi Ma, Zhicheng Dou, Wei Xu +4
Designing pre-training objectives that more closely resemble the downstream tasks for pre-trained language models can lead to better performance at the fine-tuning stage, especiall…
Neural semi-Markov CRF for Monolingual Word Alignment
Wuwei Lan, Chao Jiang, Wei Xu
Monolingual word alignment is important for studying fine-grained editing operations (i.e., deletion, addition, and substitution) in text-to-text generation tasks, such as paraphra…