Navin Goyal
23 papers · 2012–2025 · 11 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π£ Hot Topic Early Bird π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (12) π Conference Polyglot (11)
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Renaissance Researcher
(8)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
ποΈ
Keyword Collector
(104)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(23)
π₯
Unstoppable
(7)
β
The Questioner
Conferences
COLT (4)
EMNLP (4)
NIPS (3)
AISTATS (2)
ICLR (2)
ICML (2)
UAI (2)
ACL (1)
COLING (1)
CONLL (1)
NAACL (1)
Top co-authors
Research topics
Keywords
transformer model
(3)
thompson sampling
(3)
bayesian inference
(3)
positional encoding
(3)
sequence modeling
(3)
regret bound
(3)
independent component analysis
(2)
causal inference
(2)
turing completeness
(2)
language model
(2)
attention mechanism
(2)
recurrent neural network
(2)
multi-armed bandit
(2)
tensor decomposition
(2)
neural network optimization
(2)
compositional generalization
(2)
parameter estimation
(2)
linear structural equation model
(2)
convex optimization
(1)
online learning
(1)
Papers
CurLL: A Developmental Framework to Evaluate Continual Learning in Language Models
EMNLP 2025
InversionView: A General-Purpose Method for Reading Information from Neural Activations
NIPS 2024
In-Context Learning through the Bayesian Prism
ICLR 2024
Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context
NIPS 2023
Robust identifiability in linear structural equation models of causal inference
UAI 2022
Revisiting the Compositional Generalization Abilities of Neural Sequence Models
ACL 2022
When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks
EMNLP 2022
Learning and Generalization in Overparameterized Normalizing Flows
AISTATS 2022
Learning and Generalization in RNNs
NIPS 2021
Are NLP Models really able to Solve Simple Math Word Problems?
NAACL 2021
Effect of Activation Functions on the Training of Overparametrized Neural Nets
ICLR 2020
On the Computational Power of Transformers and Its Implications in Sequence Modeling
CONLL 2020
On the Ability and Limitations of Transformers to Recognize Formal Languages
EMNLP 2020
On the Computational Power of Transformers and Its Implications in Sequence Modeling
EMNLP 2020
On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages
COLING 2020
Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature
COLT 2019
Stability of Linear Structural Equation Models of Causal Inference
UAI 2019
Non-negative Matrix Factorization under Heavy Noise
ICML 2016
The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures
COLT 2014
Efficient Learning of Simplices
COLT 2013
Thompson Sampling for Contextual Bandits with Linear Payoffs
ICML 2013
Further Optimal Regret Bounds for Thompson Sampling
AISTATS 2013
Analysis of Thompson Sampling for the Multi-armed Bandit Problem
COLT 2012