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Sougata Saha

11 accepted papers

2026

Measuring Meta-Cultural Competency: A Spectral Framework for LLM Knowledge Structures

Sougata Saha, Madhur Jindal, Saurabh Kumar Pandey, Mahardika Ihsani, Alham Fikri Aji, Monojit Choudhury
ICML 2026poster

Most existing cultural evaluation frameworks for large language models (LLMs) focus on matching model outputs to ground-truth answers, primarily measuring factual cultural awareness. This overlooks whether models internalize broader cultural structure and pluralism. We introduce a spectral-analysis-…

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2025

CULTURALLY YOURS: A Reading Assistant for Cross-Cultural Content

Saurabh Kumar Pandey, Harshit Budhiraja, Sougata Saha, Monojit Choudhury
COLING 2025system demonstrations

Users from diverse cultural backgrounds frequently face challenges in understanding content from various online sources that are written by people from a different culture. This paper presents CULTURALLY YOURS (CY), a first-of-its-kind cultural reading assistant tool designed to identify culture-spe…

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2025

Meta-Cultural Competence: Climbing the Right Hill of Cultural Awareness

Sougata Saha, Saurabh Kumar Pandey, Monojit Choudhury
NAACL 2025long

Numerous recent studies have shown that Large Language Models (LLMs) are biased towards a Western and Anglo-centric worldview, which compromises their usefulness in non-Western cultural settings. However, “culture” is a complex, multifaceted topic, and its awareness, representation, and modeling in…

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2025

Reading between the Lines: Can LLMs Identify Cross-Cultural Communication Gaps?

Sougata Saha, Saurabh Kumar Pandey, Harshit Gupta, Monojit Choudhury
NAACL 2025long

In a rapidly globalizing and digital world, content such as book and product reviews created by people from diverse cultures are read and consumed by others from different corners of the world. In this paper, we investigate the extent and patterns of gaps in understandability of book reviews due to…

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2025

User Behavior Prediction as a Generic, Robust, Scalable, and Low-Cost Evaluation Strategy for Estimating Generalization in LLMs

Sougata Saha, Monojit Choudhury
ACL 2025finding

Measuring the generalization ability of Large Language Models (LLMs) is challenging due to data contamination. As models grow and computation becomes cheaper, ensuring tasks and test cases are unseen during training phases will become nearly impossible. We argue that knowledge-retrieval and reasonin…

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2025

Women, Infamous, and Exotic Beings: A Comparative Study of Honorific Usages in Wikipedia and LLMs for Bengali and Hindi

Sourabrata Mukherjee, Atharva Mehta, Sougata Saha, Akhil Arora, Monojit Choudhury
EMNLP 2025

The obligatory use of third-person honorifics is a distinctive feature of several South Asian languages, encoding nuanced socio-pragmatic cues such as power, age, gender, fame, and social distance.In this work, (i) We present the first large-scale study of third-person honorific pronoun and verb usa

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2024

Integrating Argumentation and Hate-Speech-based Techniques for Countering Misinformation

Sougata Saha, Rohini Srihari
EMNLP 2024main

The proliferation of online misinformation presents a significant challenge, requiring scalable strategies for effective mitigation. While detection methods exist, current reactive approaches, like content flagging and banning, are short-term and insufficient. Additionally, advancements like large l…

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2022

Dialo-AP: A Dependency Parsing Based Argument Parser for Dialogues

Sougata Saha, Souvik Das, Rohini K. Srihari
COLING 2022main

While neural approaches to argument mining (AM) have advanced considerably, most of the recent work has been limited to parsing monologues. With an urgent interest in the use of conversational agents for broader societal applications, there is a need to advance the state-of-the-art in argument parse…

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2022

Diving Deep into Modes of Fact Hallucinations in Dialogue Systems

Souvik Das, Sougata Saha, Rohini Srihari
EMNLP 2022finding

Knowledge Graph(KG) grounded conversations often use large pre-trained models and usually suffer from fact hallucination. Frequently entities with no references in knowledge sources and conversation history are introduced into responses, thus hindering the flow of the conversation—existing work atte…

Cited by 33Source ↗PDF ↗code ↗Scholar ↗
2022

Using Multi-Encoder Fusion Strategies to Improve Personalized Response Selection

Souvik Das, Sougata Saha, Rohini K. Srihari
COLING 2022main

Personalized response selection systems are generally grounded on persona. However, a correlation exists between persona and empathy, which these systems do not explore well. Also, when a contradictory or off-topic response is selected, faithfulness to the conversation context plunges. This paper at…

Cited by 5Source ↗PDF ↗code ↗Scholar ↗