Search Results for author: Mukund Sridhar

Found 7 papers, 3 papers with code

Low-Resource Compositional Semantic Parsing with Concept Pretraining

no code implementations24 Jan 2023 Subendhu Rongali, Mukund Sridhar, Haidar Khan, Konstantine Arkoudas, Wael Hamza, Andrew McCallum

In this work, we present an architecture to perform such domain adaptation automatically, with only a small amount of metadata about the new domain and without any new training data (zero-shot) or with very few examples (few-shot).

Domain Adaptation Semantic Parsing

AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model

1 code implementation2 Aug 2022 Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, Rahul Gupta, Wael Hamza, Haidar Khan, Charith Peris, Stephen Rawls, Andy Rosenbaum, Anna Rumshisky, Chandana Satya Prakash, Mukund Sridhar, Fabian Triefenbach, Apurv Verma, Gokhan Tur, Prem Natarajan

In this work, we demonstrate that multilingual large-scale sequence-to-sequence (seq2seq) models, pre-trained on a mixture of denoising and Causal Language Modeling (CLM) tasks, are more efficient few-shot learners than decoder-only models on various tasks.

Causal Language Modeling Common Sense Reasoning +8

Towards Realistic Single-Task Continuous Learning Research for NER

1 code implementation Findings (EMNLP) 2021 Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta

There is an increasing interest in continuous learning (CL), as data privacy is becoming a priority for real-world machine learning applications.


Automatic Discovery of Novel Intents & Domains from Text Utterances

no code implementations22 May 2020 Nikhita Vedula, Rahul Gupta, Aman Alok, Mukund Sridhar

We propose a novel framework, ADVIN, to automatically discover novel domains and intents from large volumes of unlabeled data.

General Classification Natural Language Understanding +1

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