81 citations · 226 across the 16 of their papers we have counts for
21 papers
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages
Tejas Indulal Dhamecha, Rudra Murthy, Samarth Bharadwaj +2
We explore the impact of leveraging the relatedness of languages that belong to the same family in NLP models using multilingual fine-tuning. We hypothesize and validate that multi…
Topic Transferable Table Question Answering
Saneem Ahmed Chemmengath, Vishwajeet Kumar, Samarth Bharadwaj +5
Weakly-supervised table question-answering(TableQA) models have achieved state-of-art performance by using pre-trained BERT transformer to jointly encoding a question and a table t…
Representation based meta-learning for few-shot spoken intent recognition
Ashish Mittal, Samarth Bharadwaj, Shreya Khare +3
Spoken intent detection has become a popular approach to interface with various smart devices with ease. However, such systems are limited to the preset list of intents-terms or co…
AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry
Yannis Katsis, Saneem Chemmengath, Vishwajeet Kumar +8
Recent advances in transformers have enabled Table Question Answering (Table QA) systems to achieve high accuracy and SOTA results on open domain datasets like WikiTableQuestions a…
Multilingual and code-switching ASR challenges for low resource Indian languages
Anuj Diwan, Rakesh Vaideeswaran, Sanket Shah +19
Recently, there is increasing interest in multilingual automatic speech recognition (ASR) where a speech recognition system caters to multiple low resource languages by taking adva…
Template Controllable keywords-to-text Generation
Abhijit Mishra, Md Faisal Mahbub Chowdhury, Sagar Manohar +2
This paper proposes a novel neural model for the understudied task of generating text from keywords. The model takes as input a set of un-ordered keywords, and part-of-speech (POS)…
Addressing target shift in zero-shot learning using grouped adversarial learning
Saneem Ahmed Chemmengath, Soumava Paul, Samarth Bharadwaj +2
Zero-shot learning (ZSL) algorithms typically work by exploiting attribute correlations to be able to make predictions in unseen classes. However, these correlations do not remain…
Unified Semantic Parsing with Weak Supervision
Priyanka Agrawal, Parag Jain, Ayushi Dalmia +3
Semantic parsing over multiple knowledge bases enables a parser to exploit structural similarities of programs across the multiple domains. However, the fundamental challenge lies…
On Controllable Sparse Alternatives to Softmax
Anirban Laha, Saneem A. Chemmengath, Priyanka Agrawal +3
Converting an n-dimensional vector to a probability distribution over n objects is a commonly used component in many machine learning tasks like multiclass classification, multilab…
Unsupervised Neural Text Simplification
Sai Surya, Abhijit Mishra, Anirban Laha +2
The paper presents a first attempt towards unsupervised neural text simplification that relies only on unlabeled text corpora. The core framework is composed of a shared encoder an…
Scalable Micro-planned Generation of Discourse from Structured Data
Anirban Laha, Parag Jain, Abhijit Mishra +1
We present a framework for generating natural language description from structured data such as tables; the problem comes under the category of data-to-text natural language genera…
Modeling Topical Coherence in Discourse without Supervision
Disha Shrivastava, Abhijit Mishra, Karthik Sankaranarayanan
Coherence of text is an important attribute to be measured for both manually and automatically generated discourse; but well-defined quantitative metrics for it are still elusive.…
Unsupervised Controllable Text Formalization
Parag Jain, Abhijit Mishra, Amar Prakash Azad +1
We propose a novel framework for controllable natural language transformation. Realizing that the requirement of parallel corpus is practically unsustainable for controllable gener…
A Mixed Hierarchical Attention based Encoder-Decoder Approach for Standard Table Summarization
Parag Jain, Anirban Laha, Karthik Sankaranarayanan +3
Structured data summarization involves generation of natural language summaries from structured input data. In this work, we consider summarizing structured data occurring in the f…
Generating Descriptions from Structured Data Using a Bifocal Attention Mechanism and Gated Orthogonalization
Preksha Nema, Shreyas Shetty, Parag Jain +3
In this work, we focus on the task of generating natural language descriptions from a structured table of facts containing fields (such as nationality, occupation, etc) and values…
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra +1
We propose DuoRC, a novel dataset for Reading Comprehension (RC) that motivates several new challenges for neural approaches in language understanding beyond those offered by exist…
Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
Amrita Saha, Vardaan Pahuja, Mitesh M. Khapra +2
While conversing with chatbots, humans typically tend to ask many questions, a significant portion of which can be answered by referring to large-scale knowledge graphs (KG). While…
Story Generation from Sequence of Independent Short Descriptions
Parag Jain, Priyanka Agrawal, Abhijit Mishra +3
Existing Natural Language Generation (NLG) systems are weak AI systems and exhibit limited capabilities when language generation tasks demand higher levels of creativity, originali…
A Machine Learning Approach for Evaluating Creative Artifacts
Disha Shrivastava, Saneem Ahmed CG, Anirban Laha +1
Much work has been done in understanding human creativity and defining measures to evaluate creativity. This is necessary mainly for the reason of having an objective and automatic…
Towards Building Large Scale Multimodal Domain-Aware Conversation Systems
Amrita Saha, Mitesh Khapra, Karthik Sankaranarayanan
While multimodal conversation agents are gaining importance in several domains such as retail, travel etc., deep learning research in this area has been limited primarily due to th…