Navin Goyal

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All published works

Action	Title	Year	Authors
+ PDF Chat	Exploring Continual Fine-Tuning for Enhancing Language Ability in Large Language Model	2024	Divyanshu Aggarwal Sankarshan Damle Navin Goyal Satya Lokam Sunayana Sitaram
+ PDF Chat	InversionView: A General-Purpose Method for Reading Information from Neural Activations	2024	Xinting Huang Madhur Panwar Navin Goyal Michael Hahn
+ PDF Chat	Learning Syntax Without Planting Trees: Understanding When and Why Transformers Generalize Hierarchically	2024	Kabir Ahuja Vidhisha Balachandran Madhur Panwar Tianxing He Noah A. Smith Navin Goyal Yulia Tsvetkov
+	Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology	2023	Mohamed H. Shahin Aline Barth Jagdeep T. Podichetty Qi Liu Navin Goyal Jin Y. Jin Danièle Ouellet
+	A Theory of Emergent In-Context Learning as Implicit Structure Induction	2023	Michael G. Hahn Navin Goyal
+	In-Context Learning through the Bayesian Prism	2023	Kabir Ahuja Madhur Panwar Navin Goyal
+	Guiding Language Models of Code with Global Context using Monitors	2023	Lakshya A Agrawal Aditya Kanade Navin Goyal Shuvendu K. Lahiri Sriram K. Rajamani
+	Revisiting the Compositional Generalization Abilities of Neural Sequence Models	2022	Arkil Patel Satwik Bhattamishra Phil Blunsom Navin Goyal
+	Revisiting the Compositional Generalization Abilities of Neural Sequence Models	2022	Arkil Patel Satwik Bhattamishra Phil Blunsom Navin Goyal
+	When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks	2022	Ankur Sikarwar Arkil Patel Navin Goyal
+	Towards a Mathematics Formalisation Assistant using Large Language Models	2022	Ayush Agrawal Siddhartha Gadgil Navin Goyal Ashvni Narayanan Anand Rao Tadipatri
+ PDF Chat	When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks	2022	Ankur Sikarwar Arkil Patel Navin Goyal
+	Learning and Generalization in Overparameterized Normalizing Flows.	2021	Kulin Shah Amit Deshpande Navin Goyal
+	Learning and Generalization in RNNs	2021	Abhishek Panigrahi Navin Goyal
+	Analyzing the Nuances of Transformers’ Polynomial Simplification Abilities	2021	Vishesh Agarwal Somak Aditya Navin Goyal
+	Do Transformers Understand Polynomial Simplification	2021	Vishesh Agarwal Somak Aditya Navin Goyal
+	Are NLP Models really able to Solve Simple Math Word Problems	2021	Arkil Patel Satwik Bhattamishra Navin Goyal
+	Analyzing the Nuances of Transformers' Polynomial Simplification Abilities	2021	Vishesh Agarwal Somak Aditya Navin Goyal
+ PDF Chat	Are NLP Models really able to Solve Simple Math Word Problems?	2021	Arkil Patel Satwik Bhattamishra Navin Goyal
+	Learning and Generalization in Overparameterized Normalizing Flows	2021	Kulin Shah Amit Deshpande Navin Goyal
+	Are NLP Models really able to Solve Simple Math Word Problems?	2021	Arkil Patel Satwik Bhattamishra Navin Goyal
+	Learning and Generalization in RNNs	2021	Abhishek Panigrahi Navin Goyal
+	On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Ability of Self-Attention Networks to Recognize Counter Languages.	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Ability and Limitations of Transformers to Recognize Formal Languages	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Computational Power of Transformers and its Implications in Sequence Modeling	2020	Satwik Bhattamishra Arkil Patel Navin Goyal
+ PDF Chat	Broader Implications of Modeling and Simulation (M&S) Tools in Pharmacotherapeutic Decisions: A Cautionary Optimism	2020	Ayyappa Chaturvedula Brittany N. Palasik Hae Jin Cho Navin Goyal
+	Robust Identifiability in Linear Structural Equation Models of Causal Inference	2020	Karthik Abinav Sankararaman Anand Louis Navin Goyal
+	On the Ability and Limitations of Transformers to Recognize Formal Languages	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Computational Power of Transformers and Its Implications in Sequence Modeling	2020	Satwik Bhattamishra Arkil Patel Navin Goyal
+ PDF Chat	On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Ability and Limitations of Transformers to Recognize Formal Languages	2020	Satwik Bhattamishra Kabir Ahuja Navin Goyal
+	On the Computational Power of Transformers and its Implications in Sequence Modeling	2020	Satwik Bhattamishra Arkil Patel Navin Goyal
+	Effect of Activation Functions on the Training of Overparametrized Neural Nets	2019	Abhishek Panigrahi Abhishek Shetty Navin Goyal
+	Model‐Informed Approach to Assess the Treatment Effect Conditional to the Level of Placebo Response	2019	Roberto Goméni Jonathan Rabinowitz Navin Goyal Françoise Bressolle‐Gomeni Maurizio Fava
+	Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature	2019	Navin Goyal Abhishek Shetty
+ PDF Chat	Non-Gaussian component analysis using entropy methods	2019	Navin Goyal Abhishek Shetty
+	Stability of Linear Structural Equation Models of Causal Inference.	2019	Karthik Abinav Sankararaman Anand Louis Navin Goyal
+	Stability of Linear Structural Equation Models of Causal Inference	2019	Karthik Abinav Sankararaman Anand Louis Navin Goyal
+	Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature	2019	Navin Goyal Abhishek Shetty
+	Non-Gaussianity of Stochastic Gradient Noise	2019	Abhishek Panigrahi Raghav Somani Navin Goyal Praneeth Netrapalli
+	Effect of Activation Functions on the Training of Overparametrized Neural Nets	2019	Abhishek Panigrahi Abhishek Shetty Navin Goyal
+	Heavy-Tailed Analogues of the Covariance Matrix for ICA	2017	Joseph Anderson Navin Goyal Anupama Nandi Luis Rademacher
+ PDF Chat	Heavy-Tailed Analogues of the Covariance Matrix for ICA	2017	Joseph Anderson Navin Goyal Anupama Nandi Luis Rademacher
+	Heavy-Tailed Analogues of the Covariance Matrix for ICA	2017	Joseph C. Anderson Navin Goyal Anupama Nandi Luis Rademacher
+ PDF Chat	On Computing Maximal Independent Sets of Hypergraphs in Parallel	2016	Ioana O. Bercea Navin Goyal David G. Harris Aravind Srinivasan
+	Better Analysis of GREEDY Binary Search Tree on Decomposable Sequences	2016	Navin Goyal Manoj Gupta
+	Better Analysis of GREEDY Binary Search Tree on Decomposable Sequences	2016	Navin Goyal Manoj Gupta
+ PDF Chat	Heavy-Tailed Independent Component Analysis	2015	Joseph Anderson Navin Goyal Anupama Nandi Luis Rademacher
+	Heavy-tailed Independent Component Analysis	2015	Joseph Anderson Navin Goyal Anupama Nandi Luis Rademacher
+ PDF Chat	The Role of Drug Exposure in Clinical Development: To What Extent Is Pharmacokinetic Assessment Needed in a Drug Development Programme?	2015	Navin Goyal
+ PDF Chat	A Novel Methodology to Estimate the Treatment Effect in Presence of Highly Variable Placebo Response	2015	Roberto Goméni Navin Goyal Françoise Bressolle Maurizio Fava
+	Heavy-tailed Independent Component Analysis	2015	Joseph C. Anderson Navin Goyal Anupama Nandi Luis Rademacher
+ PDF Chat	Query Complexity of Sampling and Small Geometric Partitions	2014	Navin Goyal Luis Rademacher Santosh Vempala
+ PDF Chat	On computing maximal independent sets of hypergraphs in parallel	2014	Ioana O. Bercea Navin Goyal David G. Harris Aravind Srinivasan
+ PDF Chat	Fourier PCA and robust tensor decomposition	2014	Navin Goyal Santosh Vempala Ying Xiao
+	On Computing Maximal Independent Sets of Hypergraphs in Parallel	2014	Ioana O. Bercea Navin Goyal David G. Harris Aravind Srinivasan
+ PDF Chat	None	2014	Tobias Brunsch Navin Goyal Luis Rademacher Heiko Roeglin
+	On Computing Maximal Independent Sets of Hypergraphs in Parallel	2014	Ioana O. Bercea Navin Goyal David G. Harris Aravind Srinivasan
+ PDF Chat	Annotations for Sparse Data Streams	2013	Amit Chakrabarti Graham Cormode Navin Goyal Justin Thaler
+	The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures	2013	Joseph Anderson Mikhail Belkin Navin Goyal Luis Rademacher James Voss
+	A latent variable approach in simultaneous modeling of longitudinal and dropout data in schizophrenia trials	2013	Navin Goyal Roberto Goméni
+ PDF Chat	Deterministic Algorithms for the Lovász Local Lemma	2013	Karthekeyan Chandrasekaran Navin Goyal Bernhard Haeupler
+	Adaptive Randomization Study Design in Clinical Trials for Psychiatric Disorders	2013	Navin Goyal
+	Fourier PCA and Robust Tensor Decomposition	2013	Navin Goyal Santosh Vempala Ying Xiao
+	Dynamic vs Oblivious Routing in Network Design	2013	Navin Goyal Neil Olver F. Bruce Shepherd
+	The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures	2013	Joseph C. Anderson Mikhail Belkin Navin Goyal Luis Rademacher James F. Voss
+	Annotations for Sparse Data Streams	2013	Amit Chakrabarti Graham Cormode Navin Goyal Justin Thaler
+	Efficient learning of simplices	2012	Joseph Anderson Navin Goyal Luis Rademacher
+	Further Optimal Regret Bounds for Thompson Sampling	2012	Shipra Agrawal Navin Goyal
+	Thompson Sampling for Contextual Bandits with Linear Payoffs	2012	Shipra Agrawal Navin Goyal
+	Further Optimal Regret Bounds for Thompson Sampling	2012	Shipra Agrawal Navin Goyal
+	Efficient learning of simplices	2012	Joseph C. Anderson Navin Goyal Luis Rademacher
+	Thompson Sampling for Contextual Bandits with Linear Payoffs	2012	Shipra Agrawal Navin Goyal
+	A Novel Metric to Assess the Clinical Utility of a Drug in the Presence of Efficacy and Dropout Information	2011	Navin Goyal Roberto Goméni
+	Analysis of Thompson Sampling for the multi-armed bandit problem	2011	Shipra Agrawal Navin Goyal
+	On Dynamic Optimality for Binary Search Trees	2011	Navin Goyal Manoj Gupta
+	Analysis of Thompson Sampling for the multi-armed bandit problem	2011	Shipra Agrawal Navin Goyal
+	Lower Bounds for the Average and Smoothed Number of Pareto Optima	2011	Navin Goyal Luis Rademacher
+ PDF Chat	Dynamic vs. Oblivious Routing in Network Design	2010	Navin Goyal Neil Olver F. Bruce Shepherd
+	Deterministic algorithms for the Lovász Local Lemma	2010	Karthekeyan Chandrasekaran Navin Goyal Bernhard Haeupler
+ PDF Chat	Deterministic Algorithms for the Lovász Local Lemma	2010	Karthekeyan Chandrasekaran Navin Goyal Bernhard Haeupler
+	Satisfiability Thresholds for k-CNF Formula with Bounded Variable Intersections	2010	Karthekeyan Chandrasekaran Navin Goyal Bernhard Haeupler
+	Deterministic Algorithms for the Lovasz Local Lemma	2009	Karthekeyan Chandrasekaran Navin Goyal Bernhard Haeupler
+	Learning convex bodies is hard	2009	Navin Goyal Luis Rademacher
+	Expanders via random spanning trees	2009	Navin Goyal Luis Rademacher Santosh Vempala
+ PDF Chat	Expanders via Random Spanning Trees	2009	Navin Goyal Luis Rademacher Santosh Vempala
+ PDF Chat	Dynamic vs. Oblivious Routing in Network Design	2009	Navin Goyal Neil Olver F. Bruce Shepherd
+	Learning convex bodies is hard	2009	Luis Rademacher Navin Goyal
+	Deterministic Algorithms for the Lovasz Local Lemma	2009	Karthekeyan Chandrasekaran Navin Goyal Bernhard Haeupler
+	Expanders via Random Spanning Trees	2008	Navin Goyal Luis Rademacher Santosh Vempala
+	The Graham-Knowlton Problem Revisited	2006	Navin Goyal Sachin Lodha S. Muthukrishnan
+ PDF Chat	An Efficient Approximation Algorithm for Point Pattern Matching Under Noise	2006	Vicky Choi Navin Goyal
+	A parallel search game	2005	Navin Goyal Michael Saks
+	An Efficient Approximation Algorithm for Point Pattern Matching Under Noise	2005	Vicky Choi Navin Goyal

Common Coauthors

Coauthor	Papers Together
Luis Rademacher	18
Satwik Bhattamishra	15
Arkil Patel	10
Kabir Ahuja	9
Bernhard Haeupler	6
Shipra Agrawal	6
Anupama Nandi	6
Karthekeyan Chandrasekaran	6
Joseph Anderson	6
Santosh Vempala	6
Abhishek Shetty	4
Joseph C. Anderson	4
Ioana O. Bercea	4
Roberto Goméni	4
Aravind Srinivasan	4
David G. Harris	4
Neil Olver	3
Vishesh Agarwal	3
Somak Aditya	3
Madhur Panwar	3
Anand Louis	3
Abhishek Panigrahi	3
F. Bruce Shepherd	3
Karthik Abinav Sankararaman	3
Phil Blunsom	2
Graham Cormode	2
Maurizio Fava	2
Amit Chakrabarti	2
Justin Thaler	2
Ankur Sikarwar	2
Abhishek Panigrahi	2
Manoj Gupta	2
Vicky Choi	2
Mikhail Belkin	2
Amit Deshpande	2
Ying Xiao	1
Qi Liu	1
Manoj Gupta	1
Xinting Huang	1
Ying Xiao	1
Aditya Kanade	1
Kulin Shah	1
Heiko Roeglin	1
Françoise Bressolle	1
Mohamed H. Shahin	1
Jagdeep T. Podichetty	1
Satya Lokam	1
Sunayana Sitaram	1
Praneeth Netrapalli	1
Anand Rao Tadipatri	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	8
+	On the computational power of RNNs	2019	Samuel A. Korsky Robert C. Berwick	7
+	On the Practical Computational Power of Finite Precision RNNs for Language Recognition	2018	Gail Garfinkel Weiss Yoav Goldberg Eran Yahav	7
+	Evaluating the Ability of LSTMs to Learn Context-Free Grammars	2018	Luzi Sennhauser Robert C. Berwick	6
+ PDF Chat	A random polynomial-time algorithm for approximating the volume of convex bodies	1991	Martin Dyer Alan Frieze Ravi Kannan	5
+	Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned	2019	Elena Voita David Talbot Fédor Moiseev Rico Sennrich Ivan Titov	4
+	ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES	1933	W. R THOMPSON	4
+ PDF Chat	DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding	2018	Tao Shen Tianyi Zhou Guodong Long Jing Jiang Shirui Pan Chengqi Zhang	4
+ PDF Chat	A Formal Hierarchy of RNN Architectures	2020	William Merrill Gail Garfinkel Weiss Yoav Goldberg Roy Schwartz Noah A. Smith Eran Yahav	4
+	Covariance estimation for distributions with ${2+\varepsilon}$ moments	2013	Nikhil Srivastava Roman Vershynin	4
+	LSTM Networks Can Perform Dynamic Counting	2019	Mirac Süzgün Yonatan Belinkov Stuart M. Shieber Sebastian Gehrmann	4
+	RoBERTa: A Robustly Optimized BERT Pretraining Approach	2019	Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy Mike Lewis Luke Zettlemoyer Veselin Stoyanov	4
+ PDF Chat	A constructive proof of the general lovász local lemma	2010	Robin A. Moser Gábor Tardos	4
+	Attention Is All You Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	4
+	Transformer-XL: Attentive Language Models beyond a Fixed-Length Context	2019	Zihang Dai Zhilin Yang Yiming Yang Jaime Carbonell Quoc V. Le Ruslan Salakhutdinov	4
+	Assessing the Ability of Self-Attention Networks to Learn Word Order	2019	Baosong Yang Longyue Wang Derek F. Wong Lidia S. Chao Zhaopeng Tu	4
+	Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel	2019	Yao-Hung Hubert Tsai Shaojie Bai Makoto Yamada Louis–Philippe Morency Ruslan Salakhutdinov	4
+	On the Computational Power of RNNs	2019	Samuel A. Korsky Robert C. Berwick	3
+	Concentration and moment inequalities for polynomials of independent random variables	2012	Warren Schudy Maxim Sviridenko	3
+ PDF Chat	Isoperimetric problems for convex bodies and a localization lemma	1995	Ravi Kannan László Lovász Miklós Simonovits	3
+	Sequential Neural Networks as Automata	2019	William Merrill	3
+	Gradient Descent Provably Optimizes Over-parameterized Neural Networks	2018	Simon S. Du Xiyu Zhai Barnabás Póczos Aarti Singh	3
+	Smoothed analysis of algorithms	2004	Daniel A. Spielman Shang‐Hua Teng	3
+	Are Transformers universal approximators of sequence-to-sequence functions?	2019	Chulhee Yun Srinadh Bhojanapalli Ankit Singh Rawat Sashank J. Reddi Sanjiv Kumar	3
+ PDF Chat	Tensor Decompositions for Learning Latent Variable Models	2012	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky	3
+	On the Turing Completeness of Modern Neural Network Architectures	2019	Jorge Eduardo Pérez Pérez Javier Marinković Pablo Barceló	3
+	Stability of causal inference	2016	Leonard J. Schulman Piyush Srivastava	3
+	Coloring nonuniform hypergraphs: A new algorithmic approach to the general Lov�sz local lemma	2000	Artur Czumaj Christian Scheideler	3
+ PDF Chat	Learning mixtures of spherical gaussians	2013	Daniel Hsu Sham M. Kakade	3
+	Neural Tangent Kernel: Convergence and Generalization in Neural Networks	2018	Arthur Paul Jacot Franck Gabriel Clément Hongler	3
+ PDF Chat	Model-Based Approach and Signal Detection Theory to Evaluate the Performance of Recruitment Centers in Clinical Trials With Antidepressant Drugs	2008	Emilio Merlo‐Pich Roberto Goméni	3
+	Ramsey's theorem—A new lower bound	1975	Joel Spencer	3
+	A New Population-Enrichment Strategy to Improve Efficiency of Placebo-Controlled Clinical Trials of Antidepressant Drugs	2010	Emilio Merlo‐Pich Robert Alexander Maurizio Fava Roberto Goméni	3
+	Computing maximum likelihood estimates in recursive linear models with correlated errors	2006	Mathias Drton Michael Eichler Thomas S. Richardson	3
+	A fast and simple randomized parallel algorithm for the maximal independent set problem	1986	Noga Alon László Babai Alon Itai	3
+	Random Vectors in the Isotropic Position	1999	Mark Rudelson	3
+ PDF Chat	New Constructive Aspects of the Lovász Local Lemma	2011	Bernhard Haeupler Barna Saha Aravind Srinivasan	3
+ PDF Chat	STATISTICS AND CAUSAL INFERENCE*	1985	Paul W. Holland Clark Glymour Clive W. J. Granger	3
+	Improved Algorithms via Approximations of Probability Distributions	2000	Suresh Chari Pankaj Rohatgi Aravind Srinivasan	3
+	Learning mixtures of arbitrary gaussians	2001	Sanjeev Arora Ravi Kannan	3
+	Structure from Local Optima: Learning Subspace Juntas via Higher Order PCA	2011	Santosh Vempala Ying Xiao	3
+	Simulated annealing in convex bodies and an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:msup><mml:mrow><mml:mi>O</mml:mi></mml:mrow><mml:mrow><mml:mo>*</mml:mo></mml:mrow></mml:msup><mml:mo stretchy="false">(</mml:mo><mml:msup><mml:mrow><mml:mi>n</mml:mi></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math> volume algorithm	2005	László Lovász Santosh Vempala	3
+	Analysis of Thompson Sampling for the multi-armed bandit problem	2011	Shipra Agrawal Navin Goyal	3
+	Linear structural equations with latent variables	1980	Peter M. Bentler David G. Weeks	3
+	Finding Large Independent Sets in Graphs and Hypergraphs	2004	Hadas Shachnai Aravind Srinivasan	3
+	Polynomial Learning of Distribution Families	2010	Mikhail Belkin K. P. Sinha	3
+ PDF Chat	Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders	2015	Sanjeev Arora Rong Ge Ankur Moitra Sushant Sachdeva	3
+ PDF Chat	Effective Approaches to Attention-based Neural Machine Translation	2015	Thang Luong Hieu Pham Christopher D. Manning	2
+	Analysis of Boolean Functions	2014	Ryan O’Donnell	2
+	Pseudo-random Graphs	2006	Michael Krivelevich Benny Sudakov	2