DeepSRGM - Sequence Classification and Ranking in Indian Classical Music Via Deep Learning. - Sathwik Tejaswi Madhusudhan; Girish Chowdhary 001 (ISMIR, 2019)

Enhancing Alignment using Curriculum Learning & Ranked Preferences. - Pulkit Pattnaik; Rishabh Maheshwary; Kelechi Ogueji; Vikas Yadav; Sathwik Tejaswi Madhusudhan (EMNLP (Findings), 2024)

DeepSRGM - Sequence Classification and Ranking in Indian Classical Music with Deep Learning. - Sathwik Tejaswi Madhusudhan; Girish Chowdhary 001 (CoRR, 2024)

Curry-DPO: Enhancing Alignment using Curriculum Learning & Ranked Preferences. - Pulkit Pattnaik; Rishabh Maheshwary; Kelechi Ogueji; Vikas Yadav; Sathwik Tejaswi Madhusudhan (CoRR, 2024)

Layer-Wise Quantization: A Pragmatic and Effective Method for Quantizing LLMs Beyond Integer Bit-Levels. - Razvan-Gabriel Dumitru; Vikas Yadav; Rishabh Maheshwary; Paul-Ioan Clotan; Sathwik Tejaswi Madhusudhan; Mihai Surdeanu (CoRR, 2024)

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks. - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (CoRR, 2024)

SynthCypher: A Fully Synthetic Data Generation Framework for Text-to-Cypher Querying in Knowledge Graphs. - Aman Tiwari; Shiva Krishna Reddy Malay; Vikas Yadav; Masoud Hashemi; Sathwik Tejaswi Madhusudhan (CoRR, 2024)

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 (ACL (Findings), 2025)

Do LLMs Know When to NOT Answer? Investigating Abstention Abilities of Large Language Models. - Nishanth Madhusudhan; Sathwik Tejaswi Madhusudhan; Vikas Yadav; Masoud Hashemi (COLING, 2025)

M2Lingual: Enhancing Multilingual, Multi-Turn Instruction Alignment in Large Language Models. - Rishabh Maheshwary; Vikas Yadav; Hoang Nguyen; Khyati Mahajan; Sathwik Tejaswi Madhusudhan (NAACL (Long Papers), 2025)

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework. - Aman Tiwari; Shiva Krishna Reddy Malay; Vikas Yadav; Masoud Hashemi; Sathwik Tejaswi Madhusudhan (NAACL (Short Papers), 2025)

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding. - Ahmed Masry; Juan A. Rodríguez; Tianyu Zhang; Suyuchen Wang; Chao Wang; Aarash Feizi; Akshay Kalkunte Suresh; Abhay Puri; Xiangru Jian; Pierre-André Noël; Sathwik Tejaswi Madhusudhan; Marco Pedersoli; et al. (CoRR, 2025)

Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models. - Meghana Arakkal Rajeev; Rajkumar Ramamurthy; Prapti Trivedi; Vikas Yadav; Oluwanifemi Bamgbose; Sathwik Tejaswi Madhusudhan; James Zou 001; Nazneen Rajani (CoRR, 2025)

Revitalizing Saturated Benchmarks: A Weighted Metric Approach for Differentiating Large Language Model Performance. - Bryan Etzine; Masoud Hashemi; Nishanth Madhusudhan; Sagar Davasam; Roshnee Sharma; Sathwik Tejaswi Madhusudhan; Vikas Yadav (CoRR, 2025)

DNA Bench: When Silence is Smarter - Benchmarking Over-Reasoning in Reasoning LLMs. - Masoud Hashemi; Oluwanifemi Bamgbose; Sathwik Tejaswi Madhusudhan; Jishnu Sethumadhavan Nair; Aman Tiwari; Vikas Yadav (CoRR, 2025)

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 (CoRR, 2025)

BigCharts-R1: Enhanced Chart Reasoning with Visual Reinforcement Finetuning. - Ahmed Masry; Abhay Puri; Masoud Hashemi; Juan A. Rodríguez; Megh Thakkar; Khyati Mahajan; Vikas Yadav; Sathwik Tejaswi Madhusudhan; Alexandre Piché; Dzmitry Bahdanau; Christopher Pal; David Vázquez 001; et al. (CoRR, 2025)

Apriel-Nemotron-15B-Thinker. - Shruthan Radhakrishna; Soham Parikh; Gopal Sarda; Anil Turkkan; Quaizar Vohra; Raymond Li; Dhruv Jhamb; Kelechi Ogueji; Aanjaneya Shukla; Oluwanifemi Bamgbose; Toby Liang; Luke Kumar; et al. (CoRR, 2025)