6 papers
PTP: Previous-Token Prediction based LLM Inversion for Near-Exact Prompt Reconstruction
Pirzada Suhail, Nagasai Saketh Naidu, Atanu R Sinha +1
Large language models (LLMs) generate text by auto-regressively sampling the next token. This inherently leads to a many-to-many mapping between prompts and responses, complicating…
Sequential Causal Discovery with Noisy Language Model Priors
Prakhar Verma, David Arbour, Sunav Choudhary +3
Causal discovery from observational data typically assumes access to complete data and availability of perfect domain experts. In practice, data often arrive in batches, are subjec…
Handling Missing Responses under Cluster Dependence with Applications to Language Model Evaluation
Zhenghao Zeng, David Arbour, Avi Feller +3
Human annotations play a crucial role in evaluating the performance of GenAI models. Two common challenges in practice, however, are missing annotations (the response variable of i…
Subjective Behaviors and Preferences in LLM: Language of Browsing
Sai Sundaresan, Harshita Chopra, Atanu R. Sinha +4
A Large Language Model (LLM) offers versatility across domains and tasks, purportedly benefiting users with a wide variety of behaviors and preferences. We question this perception…
Agentic Enterprise: AI-Centric User to User-Centric AI
Arpit Narechania, Alex Endert, Atanu R Sinha
After a very long winter, the Artificial Intelligence (AI) spring is here. Or, so it seems over the last three years. AI has the potential to impact many areas of human life - pers…
Guidance Source Matters: How Guidance from AI, Expert, or a Group of Analysts Impacts Visual Data Preparation and Analysis
Arpit Narechania, Alex Endert, Atanu R Sinha
The progress in generative AI has fueled AI-powered tools like co-pilots and assistants to provision better guidance, particularly during data analysis. However, research on guidan…