| 2026 | ACL | Exploring Two-Phase Continual Instruction Fine-tuning for Multilingual Adaptation in Large Language Models. | Divyanshu Aggarwal, Sankarshan Damle, Navin Goyal, Satya Lokam, Sunayana Sitaram |
| 2024 | ICLR | In-Context Learning through the Bayesian Prism. | Madhur Panwar, Kabir Ahuja, Navin Goyal |
| 2022 | ACL | Revisiting the Compositional Generalization Abilities of Neural Sequence Models. | Arkil Patel, Satwik Bhattamishra, Phil Blunsom, Navin Goyal |
| 2022 | AISTATS | Learning and Generalization in Overparameterized Normalizing Flows. | Kulin Shah, Amit Deshpande, Navin Goyal |
| 2022 | EMNLP | When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks. | Ankur Sikarwar, Arkil Patel, Navin Goyal |
| 2022 | UAI | Robust identifiability in linear structural equation models of causal inference. | Karthik Abinav Sankararaman, Anand Louis, Navin Goyal |
| 2021 | NAACL | Are NLP Models really able to Solve Simple Math Word Problems? | Arkil Patel, Satwik Bhattamishra, Navin Goyal |
| 2020 | COLING | On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages. | Satwik Bhattamishra, Kabir Ahuja, Navin Goyal |
| 2020 | CoNLL | On the Computational Power of Transformers and Its Implications in Sequence Modeling. | Satwik Bhattamishra, Arkil Patel, Navin Goyal |
| 2020 | EMNLP | On the Ability and Limitations of Transformers to Recognize Formal Languages. | Satwik Bhattamishra, Kabir Ahuja, Navin Goyal |
| 2020 | ICLR | Effect of Activation Functions on the Training of Overparametrized Neural Nets. | Abhishek Panigrahi, Abhishek Shetty, Navin Goyal |
| 2019 | COLT | Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature. | Navin Goyal, Abhishek Shetty |
| 2019 | STOC | Non-Gaussian component analysis using entropy methods. | Navin Goyal, Abhishek Shetty |
| 2019 | UAI | Stability of Linear Structural Equation Models of Causal Inference. | Karthik Abinav Sankararaman, Anand Louis, Navin Goyal |
| 2018 | ICLR | Depth separation and weight-width trade-offs for sigmoidal neural networks. | Amit Deshpande, Navin Goyal, Sushrut Karmalkar |
| 2017 | AAAI | Heavy-Tailed Analogues of the Covariance Matrix for ICA. | Joseph Anderson, Navin Goyal, Anupama Nandi, Luis Rademacher |
| 2016 | ICML | Non-negative Matrix Factorization under Heavy Noise. | Chiranjib Bhattacharyya, Navin Goyal, Ravindran Kannan, Jagdeep Pani |
| 2015 | FOCS | Heavy-Tailed Independent Component Analysis. | Joseph Anderson, Navin Goyal, Anupama Nandi, Luis Rademacher |
| 2014 | COLT | The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures. | Joseph Anderson, Mikhail Belkin, Navin Goyal, Luis Rademacher, James R. Voss |
| 2014 | SODA | Annotations for Sparse Data Streams. | Amit Chakrabarti, Graham Cormode, Navin Goyal, Justin Thaler |
| 2014 | STOC | Fourier PCA and robust tensor decomposition. | Navin Goyal, Santosh S. Vempala, Ying Xiao |
| 2014 | SPAA | On computing maximal independent sets of hypergraphs in parallel. | Ioana Oriana Bercea, Navin Goyal, David G. Harris, Aravind Srinivasan |
| 2013 | AISTATS | Further Optimal Regret Bounds for Thompson Sampling. | Shipra Agrawal, Navin Goyal |
| 2013 | COLT | Efficient Learning of Simplices. | Joseph Anderson, Navin Goyal, Luis Rademacher |
| 2013 | ICML | Thompson Sampling for Contextual Bandits with Linear Payoffs. | Shipra Agrawal, Navin Goyal |
| 2013 | WWW | Ad impression forecasting for sponsored search. | Abhirup Nath, Shibnath Mukherjee, Prateek Jain, Navin Goyal, Srivatsan Laxman |
| 2010 | SODA | Deterministic Algorithms for the Lovsz Local Lemma. | Karthekeyan Chandrasekaran, Navin Goyal, Bernhard Haeupler |
| 2009 | COLT | Learning Convex Bodies is Hard. | Luis Rademacher, Navin Goyal |
| 2009 | ESA | Dynamic vs. Oblivious Routing in Network Design. | Navin Goyal, Neil Olver, F. Bruce Shepherd |
| 2009 | SODA | Expanders via random spanning trees. | Navin Goyal, Luis Rademacher, Santosh S. Vempala |
| 2008 | STOC | The vpn conjecture is true. | Navin Goyal, Neil Olver, F. Bruce Shepherd |
| 2008 | WSDM | Disorder inequality: a combinatorial approach to nearest neighbor search. | Navin Goyal, Yury Lifshits, Hinrich Schtze |
| 2006 | FOCS | Lower bounds for circuits with MOD_m gates. | Arkadev Chattopadhyay, Navin Goyal, Pavel Pudlk, Denis Thrien |
| 2006 | LATIN | An Efficient Approximation Algorithm for Point Pattern Matching Under Noise. | Vicky Choi, Navin Goyal |
| 2005 | FOCS | Lower Bounds for the Noisy Broadcast Problem. | Navin Goyal, Guy Kindler, Michael E. Saks |
| 2005 | SODA | Rounds vs queries trade-off in noisy computation. | Navin Goyal, Michael E. Saks |
| 2004 | CPM | A Combinatorial Shape Matching Algorithm for Rigid Protein Docking. | Vicky Choi, Navin Goyal |
| 2003 | INFOCOM | Optimal Bandwidth Reservation Schedule in Cellular Network. | Samrat Ganguly, B. R. Badrinath, Navin Goyal |