activity
20232026
most citedCoPrompter: User-Centric Evaluation of LLM Instruction Alignment for Improved Prompt Engineering

3 citations · 3 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CV2026

DesignSense: A Human Preference Dataset and Reward Modeling Framework for Graphic Layout Generation

Varun Gopal, Rishabh Jain, Aradhya Mathur +6

Graphic layouts serve as an important and engaging medium for visual communication across different channels. While recent layout generation models have demonstrated impressive cap…

cs.CV2025

AFRAgent : An Adaptive Feature Renormalization Based High Resolution Aware GUI agent

Neeraj Anand, Rishabh Jain, Sohan Patnaik +2

There is a growing demand for mobile user interface (UI) automation, driven by its broad applications across industries. With the advent of visual language models (VLMs), GUI autom…

cs.CV2025

Towards Efficient Exemplar Based Image Editing with Multimodal VLMs

Avadhoot Jadhav, Ashutosh Srivastava, Abhinav Java +4

Text-to-Image Diffusion models have enabled a wide array of image editing applications. However, capturing all types of edits through text alone can be challenging and cumbersome.…

cs.CL2025

Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning

Sohan Patnaik, Milan Aggarwal, Sumit Bhatia +1

LLMssuch as GPT-4 have shown a remarkable ability to solve complex questions by generating step-by-step rationales. Prior works have utilized this capability to improve smaller and…

cs.CV2025

EOPose : Exemplar-based object reposing using Generalized Pose Correspondences

Sarthak Mehrotra, Rishabh Jain, Mayur Hemani +2

Reposing objects in images has a myriad of applications, especially for e-commerce where several variants of product images need to be produced quickly. In this work, we leverage t…

cs.CL2025

It Helps to Take a Second Opinion: Teaching Smaller LLMs to Deliberate Mutually via Selective Rationale Optimisation

Sohan Patnaik, Milan Aggarwal, Sumit Bhatia +1

Very large language models (LLMs) such as GPT-4 have shown the ability to handle complex tasks by generating and self-refining step-by-step rationales. Smaller language models (SLM…

cs.CV2025

AesthetiQ: Enhancing Graphic Layout Design via Aesthetic-Aware Preference Alignment of Multi-modal Large Language Models

Sohan Patnaik, Rishabh Jain, Balaji Krishnamurthy +1

Visual layouts are essential in graphic design fields such as advertising, posters, and web interfaces. The application of generative models for content-aware layout generation has…

cs.HC2024★ 3 cited

CoPrompter: User-Centric Evaluation of LLM Instruction Alignment for Improved Prompt Engineering

Ishika Joshi, Simra Shahid, Shreeya Venneti +5

Ensuring large language models' (LLMs) responses align with prompt instructions is crucial for application development. Based on our formative study with industry professionals, th…

cs.CV2024

ReEdit: Multimodal Exemplar-Based Image Editing with Diffusion Models

Ashutosh Srivastava, Tarun Ram Menta, Abhinav Java +4

Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic images. While the de facto method for perfor…

cs.CL2024

CABINET: Content Relevance based Noise Reduction for Table Question Answering

Sohan Patnaik, Heril Changwal, Milan Aggarwal +3

Table understanding capability of Large Language Models (LLMs) has been extensively studied through the task of question-answering (QA) over tables. Typically, only a small part of…

cs.CL2023

All Should Be Equal in the Eyes of Language Models: Counterfactually Aware Fair Text Generation

Pragyan Banerjee, Abhinav Java, Surgan Jandial +4

Fairness in Language Models (LMs) remains a longstanding challenge, given the inherent biases in training data that can be perpetuated by models and affect the downstream tasks. Re…