79 citations · 447 across the 119 of their papers we have counts for
27 papers · 1 filter
EmoReg: Directional Latent Vector Modeling for Emotional Intensity Regularization in Diffusion-based Voice Conversion
Ashishkumar Gudmalwar, Ishan D. Biyani, Nirmesh Shah +2
The Emotional Voice Conversion (EVC) aims to convert the discrete emotional state from the source emotion to the target for a given speech utterance while preserving linguistic con…
Multilingual Mathematical Reasoning: Advancing Open-Source LLMs in Hindi and English
Avinash Anand, Kritarth Prasad, Chhavi Kirtani +4
Large Language Models (LLMs) excel in linguistic tasks but struggle with mathematical reasoning, particularly in non English languages like Hindi. This research aims to enhance the…
Su-RoBERTa: A Semi-supervised Approach to Predicting Suicide Risk through Social Media using Base Language Models
Chayan Tank, Shaina Mehta, Sarthak Pol +4
In recent times, more and more people are posting about their mental states across various social media platforms. Leveraging this data, AI-based systems can be developed that help…
Enhancing LLMs for Physics Problem-Solving using Reinforcement Learning with Human-AI Feedback
Avinash Anand, Kritarth Prasad, Chhavi Kirtani +6
Large Language Models (LLMs) have demonstrated strong capabilities in text-based tasks but struggle with the complex reasoning required for physics problems, particularly in advanc…
Knowledge Graphs are all you need: Leveraging KGs in Physics Question Answering
Krishnasai Addala, Kabir Dev Paul Baghel, Dhruv Jain +5
This study explores the effectiveness of using knowledge graphs generated by large language models to decompose high school-level physics questions into sub-questions. We introduce…
Steps are all you need: Rethinking STEM Education with Prompt Engineering
Krishnasai Addala, Kabir Dev Paul Baghel, Navya Gupta +4
Few shot and Chain-of-Thought prompting have shown promise when applied to Physics Question Answering Tasks, but are limited by the lack of mathematical ability inherent to LLMs, a…
Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring
Avinash Anand, Raj Jaiswal, Abhishek Dharmadhikari +6
This paper presents GPSM4K, a comprehensive geometry multimodal dataset tailored to augment the problem-solving capabilities of Large Vision Language Models (LVLMs). GPSM4K encompa…
Improving Physics Reasoning in Large Language Models Using Mixture of Refinement Agents
Raj Jaiswal, Dhruv Jain, Harsh Parimal Popat +4
Large Language Models (LLMs) demonstrate remarkable capabilities in various reasoning tasks. However, they encounter significant challenges when it comes to scientific reasoning, p…
JOOCI: a Framework for Learning Comprehensive Speech Representations
Hemant Yadav, Rajiv Ratn Shah, Sunayana Sitaram
Information in speech can be categorized into two groups: Content (what is being said, such as linguistics) and Other (how it is expressed such as information about speaker and par…
RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge Graphs
Mayank Kharbanda, Rajiv Ratn Shah, Raghava Mutharaju
Multi-hop query answering over a Knowledge Graph (KG) involves traversing one or more hops from the start node to answer a query. Path-based and logic-based methods are state-of-th…
Multilingual Non-Factoid Question Answering with Answer Paragraph Selection
Ritwik Mishra, Sreeram Vennam, Rajiv Ratn Shah +1
Most existing Question Answering Datasets (QuADs) primarily focus on factoid-based short-context Question Answering (QA) in high-resource languages. However, the scope of such data…
Speech Representation Learning Revisited: The Necessity of Separate Learnable Parameters and Robust Data Augmentation
Hemant Yadav, Sunayana Sitaram, Rajiv Ratn Shah
Speech modeling methods learn one embedding for a fixed segment of speech, typically in between 10-25 ms. The information present in speech can be divided into two categories: "wha…
Depression Detection and Analysis using Large Language Models on Textual and Audio-Visual Modalities
Chayan Tank, Sarthak Pol, Vinayak Katoch +3
Depression has proven to be a significant public health issue, profoundly affecting the psychological well-being of individuals. If it remains undiagnosed, depression can lead to s…
Keystroke Dynamics Against Academic Dishonesty in the Age of LLMs
Debnath Kundu, Atharva Mehta, Rajesh Kumar +4
The transition to online examinations and assignments raises significant concerns about academic integrity. Traditional plagiarism detection systems often struggle to identify inst…
DubWise: Video-Guided Speech Duration Control in Multimodal LLM-based Text-to-Speech for Dubbing
Neha Sahipjohn, Ashishkumar Gudmalwar, Nirmesh Shah +2
Audio-visual alignment after dubbing is a challenging research problem. To this end, we propose a novel method, DubWise Multi-modal Large Language Model (LLM)-based Text-to-Speech…
VECL-TTS: Voice identity and Emotional style controllable Cross-Lingual Text-to-Speech
Ashishkumar Gudmalwar, Nirmesh Shah, Sai Akarsh +2
Despite the significant advancements in Text-to-Speech (TTS) systems, their full utilization in automatic dubbing remains limited. This task necessitates the extraction of voice id…
MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations
Hemant Yadav, Sunayana Sitaram, Rajiv Ratn Shah
In recent years, self-supervised pre-training methods have gained significant traction in learning high-level information from raw speech. Among these methods, HuBERT has demonstra…
Teaching Human Behavior Improves Content Understanding Abilities Of LLMs
Somesh Singh, Harini S, Yaman K Singla +4
Communication is defined as "Who says what to whom with what effect". A message from a communicator generates downstream receiver effects, also known as behavior. Receiver behavior…
Context-Enhanced Language Models for Generating Multi-Paper Citations
Avinash Anand, Kritarth Prasad, Ujjwal Goel +4
Citation text plays a pivotal role in elucidating the connection between scientific documents, demanding an in-depth comprehension of the cited paper. Constructing citations is oft…
Mathify: Evaluating Large Language Models on Mathematical Problem Solving Tasks
Avinash Anand, Mohit Gupta, Kritarth Prasad +5
The rapid progress in the field of natural language processing (NLP) systems and the expansion of large language models (LLMs) have opened up numerous opportunities in the field of…
TC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content
Avinash Anand, Raj Jaiswal, Pijush Bhuyan +5
The automatic recognition of tabular data in document images presents a significant challenge due to the diverse range of table styles and complex structures. Tables offer valuable…
RanLayNet: A Dataset for Document Layout Detection used for Domain Adaptation and Generalization
Avinash Anand, Raj Jaiswal, Mohit Gupta +7
Large ground-truth datasets and recent advances in deep learning techniques have been useful for layout detection. However, because of the restricted layout diversity of these data…
KG-CTG: Citation Generation through Knowledge Graph-guided Large Language Models
Avinash Anand, Mohit Gupta, Kritarth Prasad +4
Citation Text Generation (CTG) is a task in natural language processing (NLP) that aims to produce text that accurately cites or references a cited document within a source documen…
MM-PhyQA: Multimodal Physics Question-Answering With Multi-Image CoT Prompting
Avinash Anand, Janak Kapuriya, Apoorv Singh +5
While Large Language Models (LLMs) can achieve human-level performance in various tasks, they continue to face challenges when it comes to effectively tackling multi-step physics r…