Rishabh Maheshwary

Rishabh Maheshwary

Research Scientist @ ServiceNow

I am Rishabh, currently part of the research group at ServiceNow, where I focus on LLM post-training through data curation, fine-tuning, reinforcement learning, and model evaluations.

My recent work includes Apriel-15B model series, research on multilingual alignment and benchmarking, curriculum learning for preference modeling, and improving agentic capabilities.

Previously, I was an AI Resident at Facebook AI Research, where I worked with Marcus Rohrbach on text detection and multimodal vision-and-language understanding.

Prior to that, I completed my Master's at IIIT Hyderabad, focusing on robustness and generalization of language models.

More details can be found on my google scholar page and cover letter.

Research

Apriel-15B

Apriel-15B series

Core Contributor | Training & Evals

ServiceNow Research
M-RewardBench

M-RewardBench: Evaluating Reward Models for Multilingual

Srishti Gureja*, Lester James V. Miranda*, Shayekh Bin Islam*, Rishabh Maheshwary*, Drishti Sharma, Gusti Winata, Nathan Lambert, Sebastian Ruder, Sara Hooker, Marzieh Fadaee

ACL 2025
Dynamic Notes

Variable Layerwise Quantization: A Simple and Effective Approach to Quantize LLMs

Razvan-Gabriel Dumitru, Vikas Yadav, Rishabh Maheshwary, Paul Ioan Clotan, Sathwik Tejaswi Madhusudhan, Mihai Surdeanu

Findings of ACL 2025
Dynamic Notes

Augmenting LLM Reasoning with Dynamic Notes Writing for Complex QA

Rishabh Maheshwary, Masoud Hashemi, Khyati Mahajan, Shiva Krishna Reddy Malay, Sai Rajeswar, Sathwik Tejaswi Madhusudhan, Spandana Gella, Vikas Yadav

Under Review • ARR
Curriculum DPO

Enhancing Alignment using Curriculum Learning & Ranked Preferences

Pulkit Pattnaik*, Rishabh Maheshwary*, Kelechi Ogueji, Vikas Yadav, Sathwik Tejaswi Madhusudhan

EMNLP 2024
M2Lingual

M2Lingual: Enhancing Multilingual, Multi-Turn Instruction Alignment in Large Language Models

Rishabh Maheshwary, Vikas Yadav, Hoang Nguyen, Khyati Mahajan, Sathwik Tejaswi Madhusudhan

NAACL 2025
VQA

Improving Selective Visual Question Answering by Learning from Your Peers

Corentin Dancette, Spencer Whitehead, Rishabh Maheshwary, Ramakrishna Vedantam, Stefan Scherer, Xinlei Chen, Matthieu Cord, Marcus Rohrbach

CVPR 2023
VQA

End-to-end text detection

Rishabh Maheshwary, Spencer Whitehead, Ronghang hu, Marcus Rohrbach

Data Augmentation

Practice Makes a Solver Perfect: Data Augmentation for Math Word Problem Solvers

Vivek Kumar, Rishabh Maheshwary, Vikram Pudi

NAACL 2022 • Oral
Black Box

A Strong Baseline for Query Efficient Attacks in a Black Box Setting

Rishabh Maheshwary*, Saket Maheshwary*, Vikram Pudi

EMNLP 2021
MWP

Adversarial Examples for Evaluating Math Word Problem Solvers

Vivek Kumar*, Rishabh Maheshwary*, Vikram Pudi

EMNLP 2021 • Findings
Hard Label

Generating natural language attacks in a hard label black box setting

Rishabh Maheshwary, Saket Maheshwary, Vikram Pudi

AAAI 2021
Context Attack

A context aware approach for generating natural language attacks

Rishabh Maheshwary, Saket Maheshwary, Vikram Pudi

AAAI 2021 • Student Poster
Thesis

Evaluating the Robustness of Deep learning Models for NLP

Masters Thesis • IIIT Hyderabad

2022