Search Results for author: Himanshu Gupta

Found 15 papers, 7 papers with code

Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy

no code implementations13 Sep 2023 Yunfan Li, Himanshu Gupta, Haibin Ling, IV Ramakrishnan, Prateek Prasanna, Georgios Georgakis, Aaron Sasson

Compared with classical open cholecystectomy, laparoscopic cholecystectomy (LC) is associated with significantly shorter recovery period, and hence is the preferred method.

Semantic Segmentation

EDM3: Event Detection as Multi-task Text Generation

1 code implementation25 May 2023 Ujjwala Anantheswaran, Himanshu Gupta, Mihir Parmar, Kuntal Kumar Pal, Chitta Baral

We show that EDM3 helps to learn transferable knowledge that can be leveraged to perform Event Detection and its subtasks concurrently, mitigating the error propagation inherent in pipelined approaches.

Event Detection Text Generation

Instruction Tuned Models are Quick Learners

1 code implementation17 May 2023 Himanshu Gupta, Saurabh Arjun Sawant, Swaroop Mishra, Mutsumi Nakamura, Arindam Mitra, Santosh Mashetty, Chitta Baral

In the MTL setting, an instruction tuned model trained on only 6% of downstream training data achieve SOTA, while using 100% of the training data results in a 3. 69% points improvement (ROUGE-L 74. 68) over the previous SOTA.

Multi-Task Learning Question Rewriting

A Unified Evaluation Framework for Novelty Detection and Accommodation in NLP with an Instantiation in Authorship Attribution

no code implementations8 May 2023 Neeraj Varshney, Himanshu Gupta, Eric Robertson, Bing Liu, Chitta Baral

To initiate a systematic research in this important area of 'dealing with novelties', we introduce 'NoveltyTask', a multi-stage task to evaluate a system's performance on pipelined novelty 'detection' and 'accommodation' tasks.

Novelty Detection

InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis

1 code implementation16 Feb 2023 Kevin Scaria, Himanshu Gupta, Siddharth Goyal, Saurabh Arjun Sawant, Swaroop Mishra, Chitta Baral

In this paper, we present InstructABSA, Aspect Based Sentiment Analysis (ABSA) using the instruction learning paradigm for the ABSA subtasks: Aspect Term Extraction (ATE), Aspect Term Sentiment Classification (ATSC), and Joint Task modeling.

Aspect Extraction Sentiment Classification +1

Detecting Unintended Social Bias in Toxic Language Datasets

no code implementations21 Oct 2022 Nihar Sahoo, Himanshu Gupta, Pushpak Bhattacharyya

However, very little research has been done to detect unintended social bias from these toxic language datasets.

Intention-Aware Navigation in Crowds with Extended-Space POMDP Planning

1 code implementation20 Jun 2022 Himanshu Gupta, Bradley Hayes, Zachary Sunberg

This paper presents a hybrid online Partially Observable Markov Decision Process (POMDP) planning system that addresses the problem of autonomous navigation in the presence of multi-modal uncertainty introduced by other agents in the environment.

Autonomous Navigation Motion Planning

Hollywood Identity Bias Dataset: A Context Oriented Bias Analysis of Movie Dialogues

no code implementations LREC 2022 Sandhya Singh, Prapti Roy, Nihar Sahoo, Niteesh Mallela, Himanshu Gupta, Pushpak Bhattacharyya, Milind Savagaonkar, Nidhi, Roshni Ramnani, Anutosh Maitra, Shubhashis Sengupta

Since AI solutions are data intensive and there exists no domain specific data to address the problem of biases in scripts, we introduce a new dataset of movie scripts that are annotated for identity bias.

Context-NER : Contextual Phrase Generation at Scale

1 code implementation16 Sep 2021 Himanshu Gupta, Shreyas Verma, Santosh Mashetty, Swaroop Mishra

In this paper, we introduce CONTEXT-NER, a task that aims to generate the relevant context for entities in a sentence, where the context is a phrase describing the entity but not necessarily present in the sentence.

ContextNER Language Modelling +7

Empirical Analysis on Effectiveness of NLP Methods for Predicting Code Smell

no code implementations8 Aug 2021 Himanshu Gupta, Abhiram Anand Gulanikar, Lov Kumar, Lalita Bhanu Murthy Neti

A code smell is a surface indicator of an inherent problem in the system, most often due to deviation from standard coding practices on the developers part during the development phase.

Feature Engineering

An Empirical Study on Predictability of Software Code Smell Using Deep Learning Models

no code implementations8 Aug 2021 Himanshu Gupta, Tanmay G. Kulkarni, Lov Kumar, Lalita Bhanu Murthy Neti, Aneesh Krishna

Code Smell, similar to a bad smell, is a surface indication of something tainted but in terms of software writing practices.

feature selection

Prediction of Students performance with Artificial Neural Network using Demographic Traits

no code implementations8 Aug 2021 Adeniyi Jide Kehinde, Abidemi Emmanuel Adeniyi, Roseline Oluwaseun Ogundokun, Himanshu Gupta, Sanjay Misra

The study aims to develop a system to predict student performance with Artificial Neutral Network using the student demographic traits so as to assist the university in selecting candidates (students) with a high prediction of success for admission using previous academic records of students granted admissions which will eventually lead to quality graduates of the institution.

DSC IIT-ISM at SemEval-2020 Task 8: Bi-Fusion Techniques for Deep Meme Emotion Analysis

1 code implementation SEMEVAL 2020 Pradyumna Gupta, Himanshu Gupta, Aman Sinha

Memes have become an ubiquitous social media entity and the processing and analysis of suchmultimodal data is currently an active area of research.

Classification Emotion Recognition +1

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