2 citations · 4 across the 14 of their papers we have counts for
15 papers
DiffGate: Difficulty-Gated Teacher Guidance for On-Policy Distillation
Karn Tiwari, Varnith Chordia, Prathosh A P
On-policy distillation (OPD) has emerged as a widely used paradigm for post-training large language models, reducing the train--test mismatch of conventional distillation by superv…
Vagdhenu: A Vrutta (Meter) Aware Shloka-to-Chant (TTS) System for Sanskrit
Prathosh A P
We present Vagdhenu, a vrutta (meter) aware shloka-to-chant system for Sanskrit: a text-to-speech system that maps a metrical verse to its chanted parayana recitation at high fidel…
Spectral Query-Key Product Weight Steering for Training-Free VLM Hallucination Mitigation
Karn Tiwari, Varnith Chordia, Prathosh A P
Vision-language models (VLMs) often generate fluent but visually unsupported descriptions, especially by mentioning objects absent from the image. We propose QK Product Steering, a…
Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising
Aditya Hemant Shahane, Anuj Kumar Sirohi, Tanmoy Chakraborty +2
Fine-tuned autoregressive models for graph-to-sequence generation (G2S) often struggle with factual grounding and edit sensitivity. To tackle these issues, we propose a non-autoreg…
Learning Equivariant Functions via Quadratic Forms
Pavan Karjol, Vivek V Kashyap, Rohan Kashyap +1
In this study, we introduce a method for learning group (known or unknown) equivariant functions by learning the associated quadratic form corresponding to the group from…
Interpretable Discovery of One-parameter Subgroups: A Modular Framework for Elliptical, Hyperbolic, and Parabolic Symmetries
Pavan Karjol, Vivek V Kashyap, Rohan Kashyap +1
We propose a modular, data-driven framework for jointly learning unknown functional mappings and discovering the underlying one-parameter symmetry subgroup governing the data. Unli…
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan +1
Neural operators have emerged as powerful data-driven frameworks for solving Partial Differential Equations (PDEs), offering significant speedups over numerical methods. However, e…
CoNOAir: A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities
Sanchit Bedi, Karn Tiwari, Prathosh A. P. +2
Carbon Monoxide (CO) is a dominant pollutant in urban areas due to the energy generation from fossil fuels for industry, automobile, and domestic requirements. Forecasting the evol…
GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis
Ashish Goswami, Satyam Kumar Modi, Santhosh Rishi Deshineni +3
Text-to-image (T2I) generation has seen significant progress with diffusion models, enabling generation of photo-realistic images from text prompts. Despite this progress, existing…
Neural Compound-Word (Sandhi) Generation and Splitting in Sanskrit Language
Sushant Dave, Arun Kumar Singh, Prathosh A. P. +1
This paper describes neural network based approaches to the process of the formation and splitting of word-compounding, respectively known as the Sandhi and Vichchhed, in Sanskrit…
A Benchmark Corpus and Neural Approach for Sanskrit Derivative Nouns Analysis
Arun Kumar Singh, Sushant Dave, Prathosh A. P. +2
This paper presents first benchmark corpus of Sanskrit Pratyaya (suffix) and inflectional words (padas) formed due to suffixes along with neural network based approaches to process…
MaskAAE: Latent space optimization for Adversarial Auto-Encoders
Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran +3
The field of neural generative models is dominated by the highly successful Generative Adversarial Networks (GANs) despite their challenges, such as training instability and mode c…
Guided Weak Supervision for Action Recognition with Scarce Data to Assess Skills of Children with Autism
Prashant Pandey, Prathosh AP, Manu Kohli +1
Diagnostic and intervention methodologies for skill assessment of autism typically requires a clinician repetitively initiating several stimuli and recording the child's response.…
Variational Inference with Latent Space Quantization for Adversarial Resilience
Vinay Kyatham, Mayank Mishra, Tarun Kumar Yadav +2
Despite their tremendous success in modelling high-dimensional data manifolds, deep neural networks suffer from the threat of adversarial attacks - Existence of perceptually valid…
Detection of Glottal Closure Instants from Raw Speech using Convolutional Neural Networks
Mohit Goyal, Varun Srivastava, Prathosh A. P
Glottal Closure Instants (GCIs) correspond to the temporal locations of significant excitation to the vocal tract occurring during the production of voiced speech. GCI detection fr…