13 citations · 42 across the 24 of their papers we have counts for
5 papers · 1 filter
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis
Pranav Narayanan Venkit, Mukund Srinath, Sanjana Gautam +4
We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets. Our i…
CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Bias
Vipul Gupta, Pranav Narayanan Venkit, Hugo Laurençon +2
As language models (LMs) become increasingly powerful and widely used, it is important to quantify them for sociodemographic bias with potential for harm. Prior measures of bias ar…
Semantic Consistency for Assuring Reliability of Large Language Models
Harsh Raj, Vipul Gupta, Domenic Rosati +1
Large Language Models (LLMs) exhibit remarkable fluency and competence across various natural language tasks. However, recent research has highlighted their sensitivity to variatio…
Sociodemographic Bias in Language Models: A Survey and Forward Path
Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson +1
Sociodemographic bias in language models (LMs) has the potential for harm when deployed in real-world settings. This paper presents a comprehensive survey of the past decade of res…
Do we need entire training data for adversarial training?
Vipul Gupta, Apurva Narayan
Deep Neural Networks (DNNs) are being used to solve a wide range of problems in many domains including safety-critical domains like self-driving cars and medical imagery. DNNs suff…