52 citations · 127 across the 12 of their papers we have counts for
14 papers
Rome was built in 1776: A Case Study on Factual Correctness in Knowledge-Grounded Response Generation
Sashank Santhanam, Behnam Hedayatnia, Spandana Gella +4
Recently neural response generation models have leveraged large pre-trained transformer models and knowledge snippets to generate relevant and informative responses. However, this…
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…
Local Knowledge Powered Conversational Agents
Sashank Santhanam, Wei Ping, Raul Puri +3
State-of-the-art conversational agents have advanced significantly in conjunction with the use of large transformer-based language models. However, even with these advancements, co…
Learning to Plan and Realize Separately for Open-Ended Dialogue Systems
Sashank Santhanam, Zhuo Cheng, Brodie Mather +7
Achieving true human-like ability to conduct a conversation remains an elusive goal for open-ended dialogue systems. We posit this is because extant approaches towards natural lang…
The Panacea Threat Intelligence and Active Defense Platform
Adam Dalton, Ehsan Aghaei, Ehab Al-Shaer +13
We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks. We deploy a pipeline of human langu…
Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation
Archna Bhatia, Adam Dalton, Brodie Mather +5
We present a paradigm for extensible lexicon development based on Lexical Conceptual Structure to support social engineering detection and response generation. We leverage the cent…
Studying the Effects of Cognitive Biases in Evaluation of Conversational Agents
Sashank Santhanam, Alireza Karduni, Samira Shaikh
Humans quite frequently interact with conversational agents. The rapid advancement in generative language modeling through neural networks has helped advance the creation of intell…
Natural Language Generation Using Reinforcement Learning with External Rewards
Vidhushini Srinivasan, Sashank Santhanam, Samira Shaikh
We propose an approach towards natural language generation using a bidirectional encoder-decoder which incorporates external rewards through reinforcement learning (RL). We use att…
Emotional Neural Language Generation Grounded in Situational Contexts
Sashank Santhanam, Samira Shaikh
Emotional language generation is one of the keys to human-like artificial intelligence. Humans use different type of emotions depending on the situation of the conversation. Emotio…
Towards Best Experiment Design for Evaluating Dialogue System Output
Sashank Santhanam, Samira Shaikh
To overcome the limitations of automated metrics (e.g. BLEU, METEOR) for evaluating dialogue systems, researchers typically use human judgments to provide convergent evidence. Whil…
I Stand With You: Using Emojis to Study Solidarity in Crisis Events
Sashank Santhanam, Vidhushini Srinivasan, Shaina Glass +1
We study how emojis are used to express solidarity in social media in the context of two major crisis events - a natural disaster, Hurricane Irma in 2017 and terrorist attacks that…
A Survey of Natural Language Generation Techniques with a Focus on Dialogue Systems - Past, Present and Future Directions
Sashank Santhanam, Samira Shaikh
One of the hardest problems in the area of Natural Language Processing and Artificial Intelligence is automatically generating language that is coherent and understandable to human…
Vulnerable to Misinformation? Verifi!
Alireza Karduni, Isaac Cho, Ryan Wesslen +5
We present Verifi2, a visual analytic system to support the investigation of misinformation on social media. On the one hand, social media platforms empower individuals and organiz…
Anchored in a Data Storm: How Anchoring Bias Can Affect User Strategy, Confidence, and Decisions in Visual Analytics
Ryan Wesslen, Sashank Santhanam, Alireza Karduni +3
Cognitive biases have been shown to lead to faulty decision-making. Recent research has demonstrated that the effect of cognitive biases, anchoring bias in particular, transfers to…