26 citations · 49 across the 9 of their papers we have counts for
11 papers
ScaleCall -- Agentic Tool Calling at Scale for Fintech: Challenges, Methods, and Deployment Insights
Richard Osuagwu, Thomas Cook, Maraim Masoud +2
While Large Language Models (LLMs) excel at tool calling, deploying these capabilities in regulated enterprise environments such as fintech presents unique challenges due to on-pre…
Retrieval Augmented Generation (RAG) for Fintech: Agentic Design and Evaluation
Thomas Cook, Richard Osuagwu, Liman Tsatiashvili +4
Retrieval-Augmented Generation (RAG) systems often face limitations in specialized domains such as fintech, where domain-specific ontologies, dense terminology, and acronyms compli…
Parameter Efficient Fine-Tuning for Deep Learning-Based Full-Waveform Inversion
Koustav Ghosal, Abhranta Panigrahi, Arnav Chavan +2
Seismic full waveform inversion (FWI) has seen promising advancements through deep learning. Existing approaches typically focus on task-specific models trained and evaluated in is…
Enhancing Deep Learning based RMT Data Inversion using Gaussian Random Field
Koustav Ghosal, Arun Singh, Samir Malakar +2
Deep learning (DL) methods have emerged as a powerful tool for the inversion of geophysical data. When applied to field data, these models often struggle without additional fine-tu…
Harnessing Business and Media Insights with Large Language Models
Yujia Bao, Ankit Parag Shah, Neeru Narang +30
This paper introduces Fortune Analytics Language Model (FALM). FALM empowers users with direct access to comprehensive business analysis, including market trends, company performan…
Jointformer: Single-Frame Lifting Transformer with Error Prediction and Refinement for 3D Human Pose Estimation
Sebastian Lutz, Richard Blythman, Koustav Ghosal +3
Monocular 3D human pose estimation technologies have the potential to greatly increase the availability of human movement data. The best-performing models for single-image 2D-3D li…
Image Aesthetics Assessment Using Graph Attention Network
Koustav Ghosal, Aljosa Smolic
Aspect ratio and spatial layout are two of the principal factors determining the aesthetic value of a photograph. But, incorporating these into the traditional convolution-based fr…
Frequency Domain Loss Function for Deep Exposure Correction of Dark Images
Ojasvi Yadav, Koustav Ghosal, Sebastian Lutz +1
We address the problem of exposure correction of dark, blurry and noisy images captured in low-light conditions in the wild. Classical image-denoising filters work well in the freq…
STaDA: Style Transfer as Data Augmentation
Xu Zheng, Tejo Chalasani, Koustav Ghosal +2
The success of training deep Convolutional Neural Networks (CNNs) heavily depends on a significant amount of labelled data. Recent research has found that neural style transfer alg…
A Geometry-Sensitive Approach for Photographic Style Classification
Koustav Ghosal, Mukta Prasad, Aljosa Smolic
Photographs are characterized by different compositional attributes like the Rule of Thirds, depth of field, vanishing-lines etc. The presence or absence of one or more of these at…
Aesthetic Image Captioning From Weakly-Labelled Photographs
Koustav Ghosal, Aakanksha Rana, Aljosa Smolic
Aesthetic image captioning (AIC) refers to the multi-modal task of generating critical textual feedbacks for photographs. While in natural image captioning (NIC), deep models are t…