Search Results for author:
Found 16 papers, 9 papers with code
Document Structure in Long Document Transformers
Long documents often exhibit structure with hierarchically organized elements of different functions, such as section headers and paragraphs.
CARE: Collaborative AI-Assisted Reading Environment
Recent years have seen impressive progress in AI-assisted writing, yet the developments in AI-assisted reading are lacking.
CiteBench: A benchmark for Scientific Citation Text Generation
To address this challenge, we propose CiteBench: a benchmark for citation text generation that unifies multiple diverse datasets and enables standardized evaluation of citation text generation models across task designs and domains.
NLPeer: A Unified Resource for the Computational Study of Peer Review
Peer review constitutes a core component of scholarly publishing; yet it demands substantial expertise and training, and is susceptible to errors and biases.
An Inclusive Notion of Text
Natural language processing (NLP) researchers develop models of grammar, meaning and communication based on written text.
Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review
While existing NLP studies focus on the analysis of individual texts, editorial assistance often requires modeling interactions between pairs of texts -- yet general frameworks and datasets to support this scenario are missing.
Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyond
The shift towards publicly available text sources has enabled language processing at unprecedented scale, yet leaves under-serviced the domains where public and openly licensed data is scarce.
Assisting Decision Making in Scholarly Peer Review: A Preference Learning Perspective
Peer review is the primary means of quality control in academia; as an outcome of a peer review process, program and area chairs make acceptance decisions for each paper based on the review reports and scores they received.
A Matter of Framing: The Impact of Linguistic Formalism on Probing Results
Deep pre-trained contextualized encoders like BERT (Delvin et al., 2019) demonstrate remarkable performance on a range of downstream tasks.
Does My Rebuttal Matter? Insights from a Major NLP Conference
We then focus on the role of the rebuttal phase, and propose a novel task to predict after-rebuttal (i. e., final) scores from initial reviews and author responses.
LINSPECTOR: Multilingual Probing Tasks for Word Representations
We present a reusable methodology for creation and evaluation of such tests in a multilingual setting.
Corpus-Driven Thematic Hierarchy Induction
Thematic role hierarchy is a widely used linguistic tool to describe interactions between semantic roles and their syntactic realizations.
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical Resources
We examine the effect of lemmatization and POS typing on word embedding performance in a novel resource-based evaluation scenario, as well as on standard similarity benchmarks.
EELECTION at SemEval-2017 Task 10: Ensemble of nEural Learners for kEyphrase ClassificaTION
From these approaches, we created an ensemble of differently hyper-parameterized systems, achieving a micro-F1-score of 0. 63 on the test data.
Out-of-domain FrameNet Semantic Role Labeling
We create a novel test set for FrameNet SRL based on user-generated web text and find that the major bottleneck for out-of-domain FrameNet SRL is the frame identification step.
Assessing SRL Frameworks with Automatic Training Data Expansion
We present the first experiment-based study that explicitly contrasts the three major semantic role labeling frameworks.
