6 citations · 24 across the 14 of their papers we have counts for
6 papers · 1 filter
Multitask Learning Can Improve Worst-Group Outcomes
Atharva Kulkarni, Lucio Dery, Amrith Setlur +3
In order to create machine learning systems that serve a variety of users well, it is vital to not only achieve high average performance but also ensure equitable outcomes across d…
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model
Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban +10
Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relative…
Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment
Atharva Kulkarni, Sarah Masud, Vikram Goyal +1
Social media is awash with hateful content, much of which is often veiled with linguistic and topical diversity. The benchmark datasets used for hate speech detection do not accoun…
SciFix: Outperforming GPT3 on Scientific Factual Error Correction
Dhananjay Ashok, Atharva Kulkarni, Hai Pham +1
Due to the prohibitively high cost of creating error correction datasets, most Factual Claim Correction methods rely on a powerful verification model to guide the correction proces…
Learning and Reasoning Multifaceted and Longitudinal Data for Poverty Estimates and Livelihood Capabilities of Lagged Regions in Rural India
Atharva Kulkarni, Raya Das, Ravi S. Srivastava +1
Poverty is a multifaceted phenomenon linked to the lack of capabilities of households to earn a sustainable livelihood, increasingly being assessed using multidimensional indicator…
Characterizing the Entities in Harmful Memes: Who is the Hero, the Villain, the Victim?
Shivam Sharma, Atharva Kulkarni, Tharun Suresh +4
Memes can sway people's opinions over social media as they combine visual and textual information in an easy-to-consume manner. Since memes instantly turn viral, it becomes crucial…