4 citations · 6 across the 13 of their papers we have counts for
6 papers · 1 filter
Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models
Meghana Rajeev, Rajkumar Ramamurthy, Prapti Trivedi +5
We investigate the robustness of reasoning models trained for step-by-step problem solving by introducing query-agnostic adversarial triggers - short, irrelevant text that, when ap…
Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?
Shaina Raza, Oluwanifemi Bamgbose, Shardul Ghuge +3
Large Language Models (LLMs) have advanced various Natural Language Processing (NLP) tasks, such as text generation and translation, among others. However, these models often gener…
FakeWatch: A Framework for Detecting Fake News to Ensure Credible Elections
Shaina Raza, Tahniat Khan, Veronica Chatrath +3
In today's technologically driven world, the rapid spread of fake news, particularly during critical events like elections, poses a growing threat to the integrity of information.…
FakeWatch ElectionShield: A Benchmarking Framework to Detect Fake News for Credible US Elections
Tahniat Khan, Mizanur Rahman, Veronica Chatrath +2
In today's technologically driven world, the spread of fake news, particularly during crucial events such as elections, presents an increasing challenge to the integrity of informa…
She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models
Veronica Chatrath, Oluwanifemi Bamgbose, Shaina Raza
As the use of large language models (LLMs) increases within society, as does the risk of their misuse. Appropriate safeguards must be in place to ensure LLM outputs uphold the ethi…
Unlocking Bias Detection: Leveraging Transformer-Based Models for Content Analysis
Shaina Raza, Oluwanifemi Bamgbose, Veronica Chatrath +3
Bias detection in text is crucial for combating the spread of negative stereotypes, misinformation, and biased decision-making. Traditional language models frequently face challeng…