Search Results for author: Shubham Agarwal

Found 13 papers, 6 papers with code

The ReproGen Shared Task on Reproducibility of Human Evaluations in NLG: Overview and Results

no code implementations INLG (ACL) 2021 Anya Belz, Anastasia Shimorina, Shubham Agarwal, Ehud Reiter

The NLP field has recently seen a substantial increase in work related to reproducibility of results, and more generally in recognition of the importance of having shared definitions and practices relating to evaluation.

Going for GOAL: A Resource for Grounded Football Commentaries

1 code implementation8 Nov 2022 Alessandro Suglia, José Lopes, Emanuele Bastianelli, Andrea Vanzo, Shubham Agarwal, Malvina Nikandrou, Lu Yu, Ioannis Konstas, Verena Rieser

As the course of a game is unpredictable, so are commentaries, which makes them a unique resource to investigate dynamic language grounding.

Moment Retrieval Retrieval

To show or not to show: Redacting sensitive text from videos of electronic displays

no code implementations19 Aug 2022 Abhishek Mukhopadhyay, Shubham Agarwal, Patrick Dylan Zwick, Pradipta Biswas

With the increasing prevalence of video recordings there is a growing need for tools that can maintain the privacy of those recorded.

Optical Character Recognition

A Systematic Review of Reproducibility Research in Natural Language Processing

1 code implementation EACL 2021 Anya Belz, Shubham Agarwal, Anastasia Shimorina, Ehud Reiter

Against the background of what has been termed a reproducibility crisis in science, the NLP field is becoming increasingly interested in, and conscientious about, the reproducibility of its results.

History for Visual Dialog: Do we really need it?

2 code implementations ACL 2020 Shubham Agarwal, Trung Bui, Joon-Young Lee, Ioannis Konstas, Verena Rieser

Visual Dialog involves "understanding" the dialog history (what has been discussed previously) and the current question (what is asked), in addition to grounding information in the image, to generate the correct response.

Visual Dialog

Ensemble based discriminative models for Visual Dialog Challenge 2018

no code implementations15 Jan 2020 Shubham Agarwal, Raghav Goyal

This manuscript describes our approach for the Visual Dialog Challenge 2018.

Visual Dialog

Planning for Goal-Oriented Dialogue Systems

no code implementations17 Oct 2019 Christian Muise, Tathagata Chakraborti, Shubham Agarwal, Ondrej Bajgar, Arunima Chaudhary, Luis A. Lastras-Montano, Josef Ondrej, Miroslav Vodolan, Charlie Wiecha

Generating complex multi-turn goal-oriented dialogue agents is a difficult problem that has seen a considerable focus from many leaders in the tech industry, including IBM, Google, Amazon, and Microsoft.

Goal-Oriented Dialogue Systems slot-filling +1

A Knowledge-Grounded Multimodal Search-Based Conversational Agent

1 code implementation WS 2018 Shubham Agarwal, Ondrej Dusek, Ioannis Konstas, Verena Rieser

Multimodal search-based dialogue is a challenging new task: It extends visually grounded question answering systems into multi-turn conversations with access to an external database.

Question Answering Response Generation

A surprisingly effective out-of-the-box char2char model on the E2E NLG Challenge dataset

1 code implementation WS 2017 Shubham Agarwal, Marc Dymetman

We train a char2char model on the E2E NLG Challenge data, by exploiting {``}out-of-the-box{''} the recently released tfseq2seq framework, using some of the standard options offered by this tool.

Data-to-Text Generation

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