5 citations · 13 across the 12 of their papers we have counts for
12 papers
ImplicitBBQ: Benchmarking Implicit Bias in Large Language Models through Characteristic Based Cues
Bhaskara Hanuma Vedula, Darshan Anghan, Ishita Goyal +2
Large Language Models increasingly suppress biased outputs when demographic identity is stated explicitly, yet may still exhibit implicit biases when identity is conveyed indirectl…
Fair Distribution of Digital Payments: Balancing Transaction Flows for Regulatory Compliance
Ashlesha Hota, Shashwat Kumar, Daman Deep Singh +3
The concentration of digital payment transactions in just two UPI apps like PhonePe and Google Pay has raised concerns of duopoly in India s digital financial ecosystem. To address…
SMITE: Enhancing Fairness in LLMs through Optimal In-Context Example Selection via Dynamic Validation
Garima Chhikara, Kripabandhu Ghosh, Abhijnan Chakraborty
Large Language Models (LLMs) are widely used for downstream tasks such as tabular classification, where ensuring fairness in their outputs is critical for inclusivity, equal repres…
Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?
Daman Deep Singh, Ramanuj Bhattacharjee, Abhijnan Chakraborty
Hate speech detection across contemporary social media presents unique challenges due to linguistic diversity and the informal nature of online discourse. These challenges are furt…
Sometimes the Model doth Preach: Quantifying Religious Bias in Open LLMs through Demographic Analysis in Asian Nations
Hari Shankar, Vedanta S P, Tejas Cavale +2
Large Language Models (LLMs) are capable of generating opinions and propagating bias unknowingly, originating from unrepresentative and non-diverse data collection. Prior research…
MARRO: Multi-headed Attention for Rhetorical Role Labeling in Legal Documents
Purbid Bambroo, Subinay Adhikary, Paheli Bhattacharya +3
Identification of rhetorical roles like facts, arguments, and final judgments is central to understanding a legal case document and can lend power to other downstream tasks like le…
Through the Prism of Culture: Evaluating LLMs' Understanding of Indian Subcultures and Traditions
Garima Chhikara, Abhishek Kumar, Abhijnan Chakraborty
Large Language Models (LLMs) have shown remarkable advancements but also raise concerns about cultural bias, often reflecting dominant narratives at the expense of under-represente…
LaMSUM: Amplifying Voices Against Harassment through LLM Guided Extractive Summarization of User Incident Reports
Garima Chhikara, Anurag Sharma, V. Gurucharan +2
Citizen reporting platforms help the public and authorities stay informed about sexual harassment incidents. However, the high volume of data shared on these platforms makes review…
Artificial Intelligence (AI) in Legal Data Mining
Aniket Deroy, Naksatra Kumar Bailung, Kripabandhu Ghosh +2
Despite the availability of vast amounts of data, legal data is often unstructured, making it difficult even for law practitioners to ingest and comprehend the same. It is importan…
Can LLMs Help Predict Elections? (Counter)Evidence from the World's Largest Democracy
Pratik Gujral, Kshitij Awaldhi, Navya Jain +2
The study of how social media affects the formation of public opinion and its influence on political results has been a popular field of inquiry. However, current approaches freque…
Few-Shot Fairness: Unveiling LLM's Potential for Fairness-Aware Classification
Garima Chhikara, Anurag Sharma, Bhaskara Hanuma Vedula +3
Large Language Models (LLMs) are increasingly being employed for downstream tasks such as tabular classification, where predictions can directly influence individuals in high-stake…
Towards Fairness in Online Service with k Servers and its Application on Fair Food Delivery
Daman Deep Singh, Amit Kumar, Abhijnan Chakraborty
The k-SERVER problem is one of the most prominent problems in online algorithms with several variants and extensions. However, simplifying assumptions like instantaneous server mov…