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20112024
most citedUnderstanding the Effective Receptive Field in Deep Convolutional Neural Networks

806 citations · 2.8k across the 28 of their papers we have counts for

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7 papers · 1 filter

cs.CL2023

ICL Markup: Structuring In-Context Learning using Soft-Token Tags

Marc-Etienne Brunet, Ashton Anderson, Richard Zemel

Large pretrained language models (LLMs) can be rapidly adapted to a wide variety of tasks via a text-to-text approach, where the instruction and input are fed to the model in natur…

cs.CL202340 cited

"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation

Anaelia Ovalle, Palash Goyal, Jwala Dhamala +5

Transgender and non-binary (TGNB) individuals disproportionately experience discrimination and exclusion from daily life. Given the recent popularity and adoption of language gener…

cs.CL20225 cited

Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models

Ninareh Mehrabi, Palash Goyal, Apurv Verma +7

Natural language often contains ambiguities that can lead to misinterpretation and miscommunication. While humans can handle ambiguities effectively by asking clarifying questions…

cs.CL20221 cited

Semantically Informed Slang Interpretation

Zhewei Sun, Richard Zemel, Yang Xu

Slang is a predominant form of informal language making flexible and extended use of words that is notoriously hard for natural language processing systems to interpret. Existing a…

cs.CL20221 cited

Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic

António Câmara, Nina Taneja, Tamjeed Azad +2

As natural language processing systems become more widespread, it is necessary to address fairness issues in their implementation and deployment to ensure that their negative impac…

cs.CL2021

A Computational Framework for Slang Generation

Zhewei Sun, Richard Zemel, Yang Xu

Slang is a common type of informal language, but its flexible nature and paucity of data resources present challenges for existing natural language systems. We take an initial step…