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Ritam Dutt

6 accepted papers

2025

SHADES: Towards a Multilingual Assessment of Stereotypes in Large Language Models

NAACL 2025long

Large Language Models (LLMs) reproduce and exacerbate the social biases present in their training data, and resources to quantify this issue are limited. While research has attempted to identify and mitigate such biases, most efforts have been concentrated around English, lagging the rapid advanceme…

Cited by 1SourcePDFScholar
2025

SOCIAL SCAFFOLDS: A Generalization Framework for Social Understanding Tasks

EMNLP 2025

Effective human communication in social settings is contingent on recognizing subtle cues, such as intents or implications. Without such cues, NLP models risk missing social signals, instead relying on surface patterns. We introduce SOCIAL SCAFFOLDS, an automated framework for facilitating generaliz

2024

Leveraging Machine-Generated Rationales to Facilitate Social Meaning Detection in Conversations

ACL 2024long

We present a generalizable classification approach that leverages Large Language Models (LLMs) to facilitate the detection of implicitly encoded social meaning in conversations. We design a multi-faceted prompt to extract a textual explanation of the reasoning that connects visible cues to underlyin…

2023

Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model

EMNLP 2023long main

Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relatively few systematic inquiries into the linguistic capabilities of the latest generation of LLMs, and those studies that do…

Cited by 0SourceScholar
2023

Linguistic representations for fewer-shot relation extraction across domains

ACL 2023long

Recent work has demonstrated the positive impact of incorporating linguistic representations as additional context and scaffolds on the in-domain performance of several NLP tasks. We extend this work by exploring the impact of linguistic representations on cross-domain performance in a few-shot tran…

2022

PerKGQA: Question Answering over Personalized Knowledge Graphs

NAACL 2022findings

Previous studies on question answering over knowledge graphs have typically operated over a single knowledge graph (KG). This KG is assumed to be known a priori and is lever- aged similarly for all users’ queries during inference. However, such an assumption is not applicable to real-world settings,…