9 citations · 12 across the 13 of their papers we have counts for
16 papers
Debias It Yourself: Teaching LLMs Cognitive Bias Mitigation Interventions
Chahat Raj, Sina Mansouri, Aylin Caliskan +2
Bias has long been studied in social psychology and cognitive science, where decades of research have produced a body of validated interventions that reduce stereotypical thinking…
MAPLE: Metadata Conditioned LLM Pretraining for Locale-Aware Question Answering
Anjishnu Mukherjee, Ziwei Zhu, Antonios Anastasopoulos
Large language models can memorize competing locale-specific facts yet fail to select among them when the locale changes, defaulting instead to a single globally dominant answer. W…
Graph Enhanced Trajectory Anomaly Detection
Jonathan Kabala Mbuya, Dieter Pfoser, Antonios Anastasopoulos
Trajectory anomaly detection is essential for identifying unusual and unexpected movement patterns in applications ranging from intelligent transportation systems to urban safety a…
TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla
Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri
Despite being the 5th most spoken language, Bangla remains underrepresented in Large Language Models (LLMs), particularly for code generation. This primarily stems from the scarcit…
Talent or Luck? Evaluating Attribution Bias in Large Language Models
Chahat Raj, Mahika Banerjee, Jinhao Pan +3
When a student fails an exam, do we tend to blame their effort or the test's difficulty? Attribution, defined as how reasons are assigned to event outcomes, shapes perceptions, rei…
VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models
Chahat Raj, Bowen Wei, Aylin Caliskan +2
While bias in large language models (LLMs) is well-studied, similar concerns in vision-language models (VLMs) have received comparatively less attention. Existing VLM bias studies…
mHumanEval -- A Multilingual Benchmark to Evaluate Large Language Models for Code Generation
Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri
Recent advancements in large language models (LLMs) have significantly enhanced code generation from natural language prompts. The HumanEval Benchmark, developed by OpenAI, remains…
Trajectory Anomaly Detection with Language Models
Jonathan Mbuya, Dieter Pfoser, Antonios Anastasopoulos
This paper presents a novel approach for trajectory anomaly detection using an autoregressive causal-attention model, termed LM-TAD. This method leverages the similarities between…
Urban Mobility Assessment Using LLMs
Prabin Bhandari, Antonios Anastasopoulos, Dieter Pfoser
Understanding urban mobility patterns and analyzing how people move around cities helps improve the overall quality of life and supports the development of more livable, efficient,…
Breaking Bias, Building Bridges: Evaluation and Mitigation of Social Biases in LLMs via Contact Hypothesis
Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan +2
Large Language Models (LLMs) perpetuate social biases, reflecting prejudices in their training data and reinforcing societal stereotypes and inequalities. Our work explores the pot…
Crossroads of Continents: Automated Artifact Extraction for Cultural Adaptation with Large Multimodal Models
Anjishnu Mukherjee, Ziwei Zhu, Antonios Anastasopoulos
We present a comprehensive three-phase study to examine (1) the cultural understanding of Large Multimodal Models (LMMs) by introducing DalleStreet, a large-scale dataset generated…
BiasDora: Exploring Hidden Biased Associations in Vision-Language Models
Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan +2
Existing works examining Vision-Language Models (VLMs) for social biases predominantly focus on a limited set of documented bias associations, such as gender:profession or race:cri…
EmoMix-3L: A Code-Mixed Dataset for Bangla-English-Hindi Emotion Detection
Nishat Raihan, Dhiman Goswami, Antara Mahmud +2
Code-mixing is a well-studied linguistic phenomenon that occurs when two or more languages are mixed in text or speech. Several studies have been conducted on building datasets and…
Offensive Language Identification in Transliterated and Code-Mixed Bangla
Md Nishat Raihan, Umma Hani Tanmoy, Anika Binte Islam +4
Identifying offensive content in social media is vital for creating safe online communities. Several recent studies have addressed this problem by creating datasets for various lan…
Global Voices, Local Biases: Socio-Cultural Prejudices across Languages
Anjishnu Mukherjee, Chahat Raj, Ziwei Zhu +1
Human biases are ubiquitous but not uniform: disparities exist across linguistic, cultural, and societal borders. As large amounts of recent literature suggest, language models (LM…
Are Large Language Models Geospatially Knowledgeable?
Prabin Bhandari, Antonios Anastasopoulos, Dieter Pfoser
Despite the impressive performance of Large Language Models (LLM) for various natural language processing tasks, little is known about their comprehension of geographic data and re…