Search Results for author: Anuj Kumar

Found 23 papers, 2 papers with code

Building Adaptive Acceptability Classifiers for Neural NLG

no code implementations EMNLP 2021 Soumya Batra, Shashank Jain, Peyman Heidari, Ankit Arun, Catharine Youngs, Xintong Li, Pinar Donmez, Shawn Mei, Shiunzu Kuo, Vikas Bhardwaj, Anuj Kumar, Michael White

We propose a novel framework to train models to classify acceptability of responses generated by natural language generation (NLG) models, improving upon existing sentence transformation and model-based approaches.

Sentence Synthetic Data Generation +1

A Posteriori Evaluation of a Physics-Constrained Neural Ordinary Differential Equations Approach Coupled with CFD Solver for Modeling Stiff Chemical Kinetics

no code implementations22 Nov 2023 Tadbhagya Kumar, Anuj Kumar, Pinaki Pal

Proof-of-concept studies are performed with physics-constrained neuralODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions.

Multiple Protein Profiler 1.0 (MPP): A webserver for predicting and visualizing physiochemical properties of proteins at the proteome level

no code implementations17 Nov 2023 Gustavo Sganzerla Martinez, Mansi Dutt, Anuj Kumar, David J Kelvin

Determining the physicochemical properties of a protein can reveal important insights in their structure, biological functions, stability, and interactions with other molecules.

AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model

no code implementations27 Sep 2023 Seungwhan Moon, Andrea Madotto, Zhaojiang Lin, Tushar Nagarajan, Matt Smith, Shashank Jain, Chun-Fu Yeh, Prakash Murugesan, Peyman Heidari, Yue Liu, Kavya Srinet, Babak Damavandi, Anuj Kumar

We present Any-Modality Augmented Language Model (AnyMAL), a unified model that reasons over diverse input modality signals (i. e. text, image, video, audio, IMU motion sensor), and generates textual responses.

Language Modelling Video Question Answering

A Framework for Combustion Chemistry Acceleration with DeepONets

no code implementations6 Apr 2023 Anuj Kumar, Tarek Echekki

A combustion chemistry acceleration scheme is developed based on deep operator networks (DeepONets).

Computational Efficiency

Extended Feature Space-Based Automatic Melanoma Detection System

no code implementations10 Sep 2022 Shakti Kumar, Anuj Kumar

In recent years, the detection of melanoma using image processing techniques has become a dominant research field.

Specificity

An Indian Roads Dataset for Supported and Suspended Traffic Lights Detection

no code implementations9 Sep 2022 Sarita Gautam, Anuj Kumar

Autonomous vehicles are growing rapidly, in well-developed nations like America, Europe, and China.

Autonomous Vehicles

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

On the existence, uniqueness, and smoothing of solutions to the generalized SQG equations in critical Sobolev spaces

no code implementations18 Jan 2021 Michael S. Jolly, Anuj Kumar, Vincent R. Martinez

This paper studies the dissipative generalized surface quasi-geostrophic equations in a supercritical regime where the order of the dissipation is small relative to order of the velocity, and the velocities are less regular than the advected scalar by up to one order of derivative.

Analysis of PDEs 76D03, 35Q35, 35Q86, 35K59, 35B65, 34K37

Conversational Semantic Parsing

no code implementations EMNLP 2020 Armen Aghajanyan, Jean Maillard, Akshat Shrivastava, Keith Diedrick, Mike Haeger, Haoran Li, Yashar Mehdad, Ves Stoyanov, Anuj Kumar, Mike Lewis, Sonal Gupta

In this paper, we propose a semantic representation for such task-oriented conversational systems that can represent concepts such as co-reference and context carryover, enabling comprehensive understanding of queries in a session.

dialog state tracking Semantic Parsing

Information Extraction of Clinical Trial Eligibility Criteria

2 code implementations12 Jun 2020 Yitong Tseo, M. I. Salkola, Ahmed Mohamed, Anuj Kumar, Freddy Abnousi

Clinical trials predicate subject eligibility on a diversity of criteria ranging from patient demographics to food allergies.

Clustering Entity Linking +4

Memory Graph Networks for Explainable Memory-grounded Question Answering

no code implementations CONLL 2019 Seungwhan Moon, Pararth Shah, Anuj Kumar, Rajen Subba

We introduce Episodic Memory QA, the task of answering personal user questions grounded on memory graph (MG), where episodic memories and related entity nodes are connected via relational edges.

Question Answering

Memory Grounded Conversational Reasoning

no code implementations IJCNLP 2019 Seungwhan Moon, Pararth Shah, Rajen Subba, Anuj Kumar

To implement such a system, we collect a new corpus of memory grounded conversations, which comprises human-to-human role-playing dialogs given synthetic memory graphs with simulated attributes.

A Tree-to-Sequence Model for Neural NLG in Task-Oriented Dialog

no code implementations WS 2019 Jinfeng Rao, Kartikeya Upasani, Anusha Balakrishnan, Michael White, Anuj Kumar, Rajen Subba

Generating fluent natural language responses from structured semantic representations is a critical step in task-oriented conversational systems.

Sentence

Active Federated Learning

no code implementations27 Sep 2019 Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar

To exploit this we propose Active Federated Learning, where in each round clients are selected not uniformly at random, but with a probability conditioned on the current model and the data on the client to maximize efficiency.

Federated Learning

Federated User Representation Learning

no code implementations ICLR 2020 Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin

Furthermore, we show that user embeddings learned in FL and the centralized setting have a very similar structure, indicating that FURL can learn collaboratively through the shared parameters while preserving user privacy.

Federated Learning Privacy Preserving +1

OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs

no code implementations ACL 2019 Seungwhan Moon, Pararth Shah, Anuj Kumar, Rajen Subba

We study a conversational reasoning model that strategically traverses through a large-scale common fact knowledge graph (KG) to introduce engaging and contextually diverse entities and attributes.

Decoder Knowledge Graphs

Explore-Exploit: A Framework for Interactive and Online Learning

no code implementations1 Dec 2018 Honglei Liu, Anuj Kumar, Wenhai Yang, Benoit Dumoulin

This may require constant exploration of various options that the system may have for the user and obtaining signals of user preferences on those.

Active Learning

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