81 citations · 136 across the 10 of their papers we have counts for
12 papers
Robust Reward Modeling via Causal Rubrics
Pragya Srivastava, Harman Singh, Rahul Madhavan +9
Reward models (RMs) are fundamental to aligning Large Language Models (LLMs) via human feedback, yet they often suffer from reward hacking. They tend to latch on to superficial or…
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…
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…
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…
Diversity driven Attention Model for Query-based Abstractive Summarization
Preksha Nema, Mitesh Khapra, Anirban Laha +1
Abstractive summarization aims to generate a shorter version of the document covering all the salient points in a compact and coherent fashion. On the other hand, query-based summa…
Joint Learning of Correlated Sequence Labelling Tasks Using Bidirectional Recurrent Neural Networks
Vardaan Pahuja, Anirban Laha, Shachar Mirkin +3
The stream of words produced by Automatic Speech Recognition (ASR) systems is typically devoid of punctuations and formatting. Most natural language processing applications expect…
An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks
Anirban Laha, Vikas Raykar
Several tasks in argumentation mining and debating, question-answering, and natural language inference involve classifying a sequence in the context of another sequence (referred a…
An Efficient Cryptographic Hash Algorithm (BSA)
Subhabrata Mukherjee, Bimal Roy, Anirban Laha
Recent cryptanalytic attacks have exposed the vulnerabilities of some widely used cryptographic hash functions like MD5 and SHA-1. Attacks in the line of differential attacks have…