177 citations · 251 across the 15 of their papers we have counts for
8 papers · 1 filter
A Static Evaluation of Code Completion by Large Language Models
Hantian Ding, Varun Kumar, Yuchen Tian +9
Large language models trained on code have shown great potential to increase productivity of software developers. Several execution-based benchmarks have been proposed to evaluate…
CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad +5
While pre-trained language models (LM) for code have achieved great success in code completion, they generate code conditioned only on the contents within the file, i.e., in-file c…
ContraCLM: Contrastive Learning For Causal Language Model
Nihal Jain, Dejiao Zhang, Wasi Uddin Ahmad +9
Despite exciting progress in causal language models, the expressiveness of the representations is largely limited due to poor discrimination ability. To remedy this issue, we prese…
Knowing Where and What: Unified Word Block Pretraining for Document Understanding
Song Tao, Zijian Wang, Tiantian Fan +2
Due to the complex layouts of documents, it is challenging to extract information for documents. Most previous studies develop multimodal pre-trained models in a self-supervised wa…
DQ-BART: Efficient Sequence-to-Sequence Model via Joint Distillation and Quantization
Zheng Li, Zijian Wang, Ming Tan +5
Large-scale pre-trained sequence-to-sequence models like BART and T5 achieve state-of-the-art performance on many generative NLP tasks. However, such models pose a great challenge…
Modeling Subjective Assessments of Guilt in Newspaper Crime Narratives
Elisa Kreiss, Zijian Wang, Christopher Potts
Crime reporting is a prevalent form of journalism with the power to shape public perceptions and social policies. How does the language of these reports act on readers? We seek to…
Answering Complex Open-domain Questions Through Iterative Query Generation
Peng Qi, Xiaowen Lin, Leo Mehr +2
It is challenging for current one-step retrieve-and-read question answering (QA) systems to answer questions like "Which novel by the author of 'Armada' will be adapted as a featur…
TalkDown: A Corpus for Condescension Detection in Context
Zijian Wang, Christopher Potts
Condescending language use is caustic; it can bring dialogues to an end and bifurcate communities. Thus, systems for condescension detection could have a large positive impact. A c…