Search Results for author: Arash Einolghozati

Found 14 papers, 3 papers with code

Small But Funny: A Feedback-Driven Approach to Humor Distillation

no code implementations28 Feb 2024 Sahithya Ravi, Patrick Huber, Akshat Shrivastava, Aditya Sagar, Ahmed Aly, Vered Shwartz, Arash Einolghozati

The emergence of Large Language Models (LLMs) has brought to light promising language generation capabilities, particularly in performing tasks like complex reasoning and creative writing.

Text Generation

Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences

no code implementations19 Dec 2022 Asish Ghoshal, Arash Einolghozati, Ankit Arun, Haoran Li, Lili Yu, Vera Gor, Yashar Mehdad, Scott Wen-tau Yih, Asli Celikyilmaz

Lack of factual correctness is an issue that still plagues state-of-the-art summarization systems despite their impressive progress on generating seemingly fluent summaries.

Abstractive Text Summarization

A Study on the Efficiency and Generalization of Light Hybrid Retrievers

no code implementations4 Oct 2022 Man Luo, Shashank Jain, Anchit Gupta, Arash Einolghozati, Barlas Oguz, Debojeet Chatterjee, Xilun Chen, Chitta Baral, Peyman Heidari

Driven by this question, we leverage an indexing-efficient dense retriever (i. e. DrBoost) and introduce a LITE retriever that further reduces the memory of DrBoost.

Adversarial Attack Contrastive Learning +1

EASE: Extractive-Abstractive Summarization with Explanations

no code implementations14 May 2021 Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta, Marjan Ghazvininejad

Current abstractive summarization systems outperform their extractive counterparts, but their widespread adoption is inhibited by the inherent lack of interpretability.

Abstractive Text Summarization Document Summarization +1

El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing

no code implementations EACL 2021 Arash Einolghozati, Abhinav Arora, Lorena Sainz-Maza Lecanda, Anuj Kumar, Sonal Gupta

Being able to parse code-switched (CS) utterances, such as Spanish+English or Hindi+English, is essential to democratize task-oriented semantic parsing systems for certain locales.

Data Augmentation Semantic Parsing

Improving Robustness of Task Oriented Dialog Systems

no code implementations12 Nov 2019 Arash Einolghozati, Sonal Gupta, Mrinal Mohit, Rushin Shah

However, evaluating a model's robustness to these changes is harder for language since words are discrete and an automated change (e. g. adding `noise') to a query sometimes changes the meaning and thus labels of a query.

Adversarial Attack Data Augmentation +4

Improving Semantic Parsing for Task Oriented Dialog

no code implementations15 Feb 2019 Arash Einolghozati, Panupong Pasupat, Sonal Gupta, Rushin Shah, Mrinal Mohit, Mike Lewis, Luke Zettlemoyer

Semantic parsing using hierarchical representations has recently been proposed for task oriented dialog with promising results [Gupta et al 2018].

Language Modelling Re-Ranking +1

CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web

no code implementations12 Apr 2018 Colin Lockard, Xin Luna Dong, Arash Einolghozati, Prashant Shiralkar

In this paper we present a new method for automatic extraction from semi-structured websites based on distant supervision.

Relation Relation Extraction

soc2seq: Social Embedding meets Conversation Model

1 code implementation17 Feb 2017 Parminder Bhatia, Marsal Gavalda, Arash Einolghozati

While liking or upvoting a post on a mobile app is easy to do, replying with a written note is much more difficult, due to both the cognitive load of coming up with a meaningful response as well as the mechanics of entering the text.

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