Caglar Gulcehre

Orcid: 0009-0003-4124-1687

According to our database1, Caglar Gulcehre authored at least 74 papers between 2013 and 2024.

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Bibliography

2024
Unpacking SDXL Turbo: Interpreting Text-to-Image Models with Sparse Autoencoders.
CoRR, 2024

Beyond Autoregression: Fast LLMs via Self-Distillation Through Time.
CoRR, 2024

SIKeD: Self-guided Iterative Knowledge Distillation for mathematical reasoning.
CoRR, 2024

The Role of Deep Learning Regularizations on Actors in Offline RL.
CoRR, 2024

In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning.
CoRR, 2024

Investigating Low-Rank Training in Transformer Language Models: Efficiency and Scaling Analysis.
CoRR, 2024

HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context.
CoRR, 2024

Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers.
CoRR, 2024

Promises, Outlooks and Challenges of Diffusion Language Modeling.
CoRR, 2024

Fleet of Agents: Coordinated Problem Solving with Large Language Models using Genetic Particle Filtering.
CoRR, 2024

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO.
CoRR, 2024

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.
CoRR, 2024

Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Simple Hierarchical Planning with Diffusion.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Aligning Large Language Models with Diverse Political Viewpoints.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Self-Recognition in Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
Reinforced Self-Training (ReST) for Language Modeling.
CoRR, 2023

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning.
CoRR, 2023

On the Universality of Linear Recurrences Followed by Nonlinear Projections.
CoRR, 2023

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Resurrecting Recurrent Neural Networks for Long Sequences.
Proceedings of the International Conference on Machine Learning, 2023

2022
An empirical study of implicit regularization in deep offline RL.
Trans. Mach. Learn. Res., 2022

On Instrumental Variable Regression for Deep Offline Policy Evaluation.
J. Mach. Learn. Res., 2022

2021
Regularized Behavior Value Estimation.
CoRR, 2021

Active Offline Policy Selection.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Offline Learning from Demonstrations and Unlabeled Experience.
CoRR, 2020

Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver.
CoRR, 2020

Hyperparameter Selection for Offline Reinforcement Learning.
CoRR, 2020

RL Unplugged: Benchmarks for Offline Reinforcement Learning.
CoRR, 2020

Acme: A Research Framework for Distributed Reinforcement Learning.
CoRR, 2020

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Critic Regularized Regression.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stabilizing Transformers for Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Improving the Gating Mechanism of Recurrent Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Gated Orthogonal Recurrent Units: On Learning to Forget.
Neural Comput., 2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.
Nat., 2019

Improving the Gating Mechanism of Recurrent Neural Networks.
CoRR, 2019

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Hyperbolic Attention Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Sample Efficient Adaptive Text-to-Speech.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes.
Neural Comput., 2018

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL.
CoRR, 2018

Relational inductive biases, deep learning, and graph networks.
CoRR, 2018

2017
On integrating a language model into neural machine translation.
Comput. Speech Lang., 2017

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder.
CoRR, 2017

Memory Augmented Neural Networks with Wormhole Connections.
CoRR, 2017

Machine Comprehension by Text-to-Text Neural Question Generation.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A robust adaptive stochastic gradient method for deep learning.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Mollifying Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Recurrent Batch Normalization.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
EmoNets: Multimodal deep learning approaches for emotion recognition in video.
J. Multimodal User Interfaces, 2016

Policy Distillation.
Proceedings of the 4th International Conference on Learning Representations, 2016

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes.
CoRR, 2016

Theano: A Python framework for fast computation of mathematical expressions.
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CoRR, 2016

Noisy Activation Functions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond.
Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, 2016

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Pointing the Unknown Words.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015
On Using Monolingual Corpora in Neural Machine Translation.
CoRR, 2015

Gated Feedback Recurrent Neural Networks.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
How to Construct Deep Recurrent Neural Networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient.
CoRR, 2014

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.
CoRR, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.
CoRR, 2014

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2013
Knowledge Matters: Importance of Prior Information for Optimization
Proceedings of the 1st International Conference on Learning Representations, 2013

Learned-norm pooling for deep neural networks.
CoRR, 2013



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