3 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Differentiable Adversarial Attacks for Marked Temporal Point Processes
Pritish Chakraborty, Vinayak Gupta, Rahul R +2
Marked temporal point processes (MTPPs) have been shown to be extremely effective in modeling continuous time event sequences (CTESs). In this work, we present adversarial attacks…
Are Language Models Actually Useful for Time Series Forecasting?
Mingtian Tan, Mike A. Merrill, Vinayak Gupta +2
Large language models (LLMs) are being applied to time series forecasting. But are language models actually useful for time series? In a series of ablation studies on three recent…
SPML: A DSL for Defending Language Models Against Prompt Attacks
Reshabh K Sharma, Vinayak Gupta, Dan Grossman
Large language models (LLMs) have profoundly transformed natural language applications, with a growing reliance on instruction-based definitions for designing chatbots. However, po…
Retrieving Continuous Time Event Sequences using Neural Temporal Point Processes with Learnable Hashing
Vinayak Gupta, Srikanta Bedathur, Abir De
Temporal sequences have become pervasive in various real-world applications. Consequently, the volume of data generated in the form of continuous time-event sequence(s) or CTES(s)…