activity
20172023
most citedCM3: A Causal Masked Multimodal Model of the Internet

42 citations · 98 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CV2023

Efficient End-to-End Visual Document Understanding with Rationale Distillation

Wang Zhu, Alekh Agarwal, Mandar Joshi +3

Understanding visually situated language requires interpreting complex layouts of textual and visual elements. Pre-processing tools, such as optical character recognition (OCR), ca…

cs.CL2022★ 42 cited

CM3: A Causal Masked Multimodal Model of the Internet

Armen Aghajanyan, Bernie Huang, Candace Ross +8

We introduce CM3, a family of causally masked generative models trained over a large corpus of structured multi-modal documents that can contain both text and image tokens. Our new…

cs.CL2021

Realistic Evaluation Principles for Cross-document Coreference Resolution

Arie Cattan, Alon Eirew, Gabriel Stanovsky +2

We point out that common evaluation practices for cross-document coreference resolution have been unrealistically permissive in their assumed settings, yielding inflated results. W…

cs.CL2021★ 1 cited

Cross-document Coreference Resolution over Predicted Mentions

Arie Cattan, Alon Eirew, Gabriel Stanovsky +2

Coreference resolution has been mostly investigated within a single document scope, showing impressive progress in recent years based on end-to-end models. However, the more challe…

cs.CL2021

FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary

Terra Blevins, Mandar Joshi, Luke Zettlemoyer

Current models for Word Sense Disambiguation (WSD) struggle to disambiguate rare senses, despite reaching human performance on global WSD metrics. This stems from a lack of data fo…

cs.CL2020★ 26 cited

Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling

Arie Cattan, Alon Eirew, Gabriel Stanovsky +2

Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation…