7 citations · 10 across the 8 of their papers we have counts for
8 papers
Evaluating Risks in Weak-to-Strong Alignment: A Bias-Variance Perspective
Hamid Osooli, Kareema Batool, Rick Gentry +3
Weak-to-strong alignment offers a promising route to scalable supervision, but it can fail when a strong model becomes confidently wrong on examples that lie in the weak model's bl…
CREATE: Testing LLMs for Associative Creativity
Manya Wadhwa, Tiasa Singha Roy, Harvey Lederman +2
A key component of creativity is associative reasoning: the ability to draw novel yet meaningful connections between concepts. We introduce CREATE, a benchmark designed to evaluate…
Interpreting and Mitigating Unwanted Uncertainty in LLMs
Tiasa Singha Roy, Ayush Rajesh Jhaveri, Ilias Triantafyllopoulos
Despite their impressive capabilities, Large Language Models (LLMs) exhibit unwanted uncertainty, a phenomenon where a model changes a previously correct answer into an incorrect o…
Can LLMs Math? -- Exploring the Pitfalls in Mathematical Reasoning
Tiasa Singha Roy, Aditeya Baral, Ayush Rajesh Jhaveri +1
Large language models (LLMs) demonstrate considerable potential in various natural language tasks but face significant challenges in mathematical reasoning, particularly in executi…
RankAug: Augmented data ranking for text classification
Tiasa Singha Roy, Priyam Basu
Research on data generation and augmentation has been focused majorly on enhancing generation models, leaving a notable gap in the exploration and refinement of methods for evaluat…
Interpretability of Fine-grained Classification of Sadness and Depression
Tiasa Singha Roy, Priyam Basu, Aman Priyanshu +1
While sadness is a human emotion that people experience at certain times throughout their lives, inflicting them with emotional disappointment and pain, depression is a longer term…
Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
Priyam Basu, Tiasa Singha Roy, Rakshit Naidu +1
Privacy is important considering the financial Domain as such data is highly confidential and sensitive. Natural Language Processing (NLP) techniques can be applied for text classi…
Benchmarking Differential Privacy and Federated Learning for BERT Models
Priyam Basu, Tiasa Singha Roy, Rakshit Naidu +3
Natural Language Processing (NLP) techniques can be applied to help with the diagnosis of medical conditions such as depression, using a collection of a person's utterances. Depres…