12 citations · 28 across the 9 of their papers we have counts for
16 papers
Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature
Katherine Thai, Marzena Karpinska, Kalpesh Krishna +4
Literary translation is a culturally significant task, but it is bottlenecked by the small number of qualified literary translators relative to the many untranslated works publishe…
SLING: Sino Linguistic Evaluation of Large Language Models
Yixiao Song, Kalpesh Krishna, Rajesh Bhatt +1
To understand what kinds of linguistic knowledge are encoded by pretrained Chinese language models (LMs), we introduce the benchmark of Sino LINGuistics (SLING), which consists of…
ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution
Ankita Gupta, Marzena Karpinska, Wenlong Zhao +5
Large-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been c…
RELIC: Retrieving Evidence for Literary Claims
Katherine Thai, Yapei Chang, Kalpesh Krishna +1
Humanities scholars commonly provide evidence for claims that they make about a work of literature (e.g., a novel) in the form of quotations from the work. We collect a large-scale…
Do Long-Range Language Models Actually Use Long-Range Context?
Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke +1
Language models are generally trained on short, truncated input sequences, which limits their ability to use discourse-level information present in long-range context to improve th…
Weakly-Supervised Open-Retrieval Conversational Question Answering
Chen Qu, Liu Yang, Cen Chen +3
Recent studies on Question Answering (QA) and Conversational QA (ConvQA) emphasize the role of retrieval: a system first retrieves evidence from a large collection and then extract…