30 citations · 59 across the 12 of their papers we have counts for
14 papers
Benchmarking LLM powered Chatbots: Methods and Metrics
Debarag Banerjee, Pooja Singh, Arjun Avadhanam +1
Autonomous conversational agents, i.e. chatbots, are becoming an increasingly common mechanism for enterprises to provide support to customers and partners. In order to rate chatbo…
MaNtLE: Model-agnostic Natural Language Explainer
Rakesh R. Menon, Kerem Zaman, Shashank Srivastava
Understanding the internal reasoning behind the predictions of machine learning systems is increasingly vital, given their rising adoption and acceptance. While previous approaches…
LaSQuE: Improved Zero-Shot Classification from Explanations Through Quantifier Modeling and Curriculum Learning
Sayan Ghosh, Rakesh R Menon, Shashank Srivastava
A hallmark of human intelligence is the ability to learn new concepts purely from language. Several recent approaches have explored training machine learning models via natural lan…
What do Large Language Models Learn beyond Language?
Avinash Madasu, Shashank Srivastava
Large language models (LMs) have rapidly become a mainstay in Natural Language Processing. These models are known to acquire rich linguistic knowledge from training on large amount…
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations
Rakesh R Menon, Sayan Ghosh, Shashank Srivastava
Supervised learning has traditionally focused on inductive learning by observing labeled examples of a task. In contrast, humans have the ability to learn new concepts from languag…
Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning
Sayan Ghosh, Shashank Srivastava
Mapping natural language instructions to programs that computers can process is a fundamental challenge. Existing approaches focus on likelihood-based training or using reinforceme…
Adversarial Scrubbing of Demographic Information for Text Classification
Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li +3
Contextual representations learned by language models can often encode undesirable attributes, like demographic associations of the users, while being trained for an unrelated targ…
ePiC: Employing Proverbs in Context as a Benchmark for Abstract Language Understanding
Sayan Ghosh, Shashank Srivastava
While large language models have shown exciting progress on several NLP benchmarks, evaluating their ability for complex analogical reasoning remains under-explored. Here, we intro…
Improving and Simplifying Pattern Exploiting Training
Derek Tam, Rakesh R Menon, Mohit Bansal +2
Recently, pre-trained language models (LMs) have achieved strong performance when fine-tuned on difficult benchmarks like SuperGLUE. However, performance can suffer when there are…
PRover: Proof Generation for Interpretable Reasoning over Rules
Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava +1
Recent work by Clark et al. (2020) shows that transformers can act as 'soft theorem provers' by answering questions over explicitly provided knowledge in natural language. In our w…
Models for Predicting Transonic Flutter of a Wing-Section with Sloshing in an Embedded Fuel Tank
Shashank Srivastava, Murali Damodaran, Boo Cheong Khoo
The present study focuses on the development, application, and comparison of three computational frameworks of varying fidelities for assessing the effects of fuel sloshing in inte…
Machine Learning Surrogates for Predicting Response of an Aero-Structural-Sloshing System
Shashank Srivastava, Murali Damodaran, Boo Cheong Khoo
This study demonstrates the feasibility of developing machine learning (ML) surrogates based on Recurrent Neural Networks (RNN) for predicting the unsteady aeroelastic response of…
Inferring Interpersonal Relations in Narrative Summaries
Shashank Srivastava, Snigdha Chaturvedi, Tom Mitchell
Characterizing relationships between people is fundamental for the understanding of narratives. In this work, we address the problem of inferring the polarity of relationships betw…
Modeling Dynamic Relationships Between Characters in Literary Novels
Snigdha Chaturvedi, Shashank Srivastava, Hal Daume +1
Studying characters plays a vital role in computationally representing and interpreting narratives. Unlike previous work, which has focused on inferring character roles, we focus o…