USHER: An Intelligent Tour Companion. - Shubham Toshniwal; Parikshit Sharma; Saurabh Srivastava; Richa Sehgal (IUI Companion, 2015)

VibRein: An Engaging and Assistive Mobile Learning Companion for Students with Intellectual Disabilities. - Shubham Toshniwal; Prasenjit Dey; Nitendra Rajput; Saurabh Srivastava (OZCHI, 2015)

Jointly learning to align and convert graphemes to phonemes with neural attention models. - Shubham Toshniwal; Karen Livescu (SLT, 2016)

Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition. - Shubham Toshniwal; Hao Tang 002; Liang Lu 001; Karen Livescu (INTERSPEECH, 2017)

Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing. - Trang Tran 001; Shubham Toshniwal; Mohit Bansal; Kevin Gimpel; Karen Livescu; Mari Ostendorf (CoRR, 2017)

Multilingual Speech Recognition with a Single End-to-End Model. - Shubham Toshniwal; Tara N. Sainath; Ron J. Weiss; Bo Li 028; Pedro J. Moreno 001; Eugene Weinstein; Kanishka Rao (ICASSP, 2018)

Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information. - Trang Tran 001; Shubham Toshniwal; Mohit Bansal; Kevin Gimpel; Karen Livescu; Mari Ostendorf (NAACL-HLT, 2018)

A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition. - Shubham Toshniwal; Anjuli Kannan; Chung-Cheng Chiu; Yonghui Wu; Tara N. Sainath; Karen Livescu (SLT, 2018)

Hierarchical Multitask Learning for CTC-based Speech Recognition. - Kalpesh Krishna; Shubham Toshniwal; Karen Livescu (CoRR, 2018)

Pre-Trained Text Embeddings for Enhanced Text-to-Speech Synthesis. - Tomoki Hayashi; Shinji Watanabe 001; Tomoki Toda; Kazuya Takeda; Shubham Toshniwal; Karen Livescu (INTERSPEECH, 2019)

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling. - Jonathan Shen; Patrick Nguyen; Yonghui Wu; Zhifeng Chen; Mia Xu Chen; Ye Jia; Anjuli Kannan; Tara N. Sainath; Yuan Cao 007; Chung-Cheng Chiu; Yanzhang He; Jan Chorowski; et al. (CoRR, 2019)

PeTra: A Sparsely Supervised Memory Model for People Tracking. - Shubham Toshniwal; Allyson Ettinger; Kevin Gimpel; Karen Livescu (ACL, 2020)

Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks. - Shubham Toshniwal; Sam Wiseman; Allyson Ettinger; Karen Livescu; Kevin Gimpel (EMNLP (1), 2020)

A Cross-Task Analysis of Text Span Representations. - Shubham Toshniwal; Haoyue Shi 001; Bowen Shi; Lingyu Gao; Karen Livescu; Kevin Gimpel (RepL4NLP@ACL, 2020)

Learning Chess Blindfolded: Evaluating Language Models on State Tracking. - Shubham Toshniwal; Sam Wiseman; Karen Livescu; Kevin Gimpel (CoRR, 2021)

On Generalization in Coreference Resolution. - Shubham Toshniwal; Patrick Xia 002; Sam Wiseman; Karen Livescu; Kevin Gimpel (CoRR, 2021)

Chess as a Testbed for Language Model State Tracking. - Shubham Toshniwal; Sam Wiseman; Karen Livescu; Kevin Gimpel (AAAI, 2022)

Baked-in State Probing. - Shubham Toshniwal; Sam Wiseman; Karen Livescu; Kevin Gimpel (EMNLP (Findings), 2022)

Efficient and Interpretable Neural Models for Entity Tracking. - Shubham Toshniwal (CoRR, 2022)

Robustness of Named-Entity Replacements for In-Context Learning. - Saeed Goodarzi; Nikhil Kagita; Dennis Minn; Shufan Wang; Roberto Dessì; Shubham Toshniwal; Adina Williams; Jack Lanchantin; Koustuv Sinha (EMNLP (Findings), 2023)

Adapting Pretrained Text-to-Text Models for Long Text Sequences. - Wenhan Xiong; Anchit Gupta; Shubham Toshniwal; Yashar Mehdad; Scott Yih (EMNLP (Findings), 2023)

Learning to Reason and Memorize with Self-Notes. - Jack Lanchantin; Shubham Toshniwal; Jason Weston; Arthur Szlam; Sainbayar Sukhbaatar (NeurIPS, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Major Entity Identification: A Generalizable Alternative to Coreference Resolution. - Kawshik Sundar; Shubham Toshniwal; Makarand Tapaswi; Vineet Gandhi (EMNLP, 2024)

OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset. - Shubham Toshniwal; Ivan Moshkov; Sean Narenthiran; Daria Gitman; Fei Jia; Igor Gitman (NeurIPS, 2024)

Code Pretraining Improves Entity Tracking Abilities of Language Models. - Najoung Kim; Sebastian Schuster; Shubham Toshniwal (CoRR, 2024)

Nemotron-4 340B Technical Report. - Bo Adler; Niket Agarwal; Ashwath Aithal; Dong H. Anh; Pallab Bhattacharya; Annika Brundyn; Jared Casper; Bryan Catanzaro; Sharon Clay; Jonathan M. Cohen; Sirshak Das; Ayush Dattagupta; et al. (CoRR, 2024)

Major Entity Identification: A Generalizable Alternative to Coreference Resolution. - Kawshik Manikantan; Shubham Toshniwal; Makarand Tapaswi; Vineet Gandhi (CoRR, 2024)

IdentifyMe: A Challenging Long-Context Mention Resolution Benchmark. - Kawshik Manikantan; Makarand Tapaswi; Vineet Gandhi; Shubham Toshniwal (CoRR, 2024)

OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data. - Shubham Toshniwal; Wei Du; Ivan Moshkov; Branislav Kisacanin; Alexan Ayrapetyan; Igor Gitman (ICLR, 2025)

IdentifyMe: A Challenging Long-Context Mention Resolution Benchmark for LLMs. - Kawshik Manikantan; Makarand Tapaswi; Vineet Gandhi; Shubham Toshniwal (NAACL (Short Papers), 2025)

AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset. - Ivan Moshkov; Darragh Hanley; Ivan Sorokin; Shubham Toshniwal; Christof Henkel; Benedikt Schifferer; Wei Du; Igor Gitman (CoRR, 2025)

Llama-Nemotron: Efficient Reasoning Models. - Akhiad Bercovich; Itay Levy; Izik Golan; Mohammad Dabbah; Ran El-Yaniv; Omri Puny; Ido Galil; Zach Moshe; Tomer Ronen; Najeeb Nabwani; Ido Shahaf; Oren Tropp; et al. (CoRR, 2025)

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation. - Wei Du; Branislav Kisacanin; George Armstrong; Shubham Toshniwal; Ivan Moshkov; Alexan Ayrapetyan; Sadegh Mahdavi; Dan Zhao; Shizhe Diao; Dragan Masulovic; Marius Stanean; Advaith Avadhanam; et al. (CoRR, 2025)

GenSelect: A Generative Approach to Best-of-N. - Shubham Toshniwal; Ivan Sorokin; Aleksander Ficek; Ivan Moshkov; Igor Gitman (CoRR, 2025)