Karthik Narasimhan

Revelio: ML-Generated Debugging Queries for Distributed Systems

A major difficulty in debugging distributed systems lies in manually det...
06/28/2021 ∙ by Pradeep Dogga, et al. ∙ 0 ∙ share

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Self-Attention Networks Can Process Bounded Hierarchical Languages

Despite their impressive performance in NLP, self-attention networks wer...
05/24/2021 ∙ by Shunyu Yao, et al. ∙ 12 ∙ share

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Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents

Text-based games simulate worlds and interact with players using natural...
03/25/2021 ∙ by Shunyu Yao, et al. ∙ 0 ∙ share

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Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning

In this paper, we consider the problem of leveraging textual description...
01/19/2021 ∙ by H. J. Austin Wang, et al. ∙ 0 ∙ share

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Connecting Context-specific Adaptation in Humans to Meta-learning

Cognitive control, the ability of a system to adapt to the demands of a ...
11/27/2020 ∙ by Rachit Dubey, et al. ∙ 0 ∙ share

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Generating Strategic Dialogue for Negotiation with Theory of Mind

We propose a framework to integrate the concept of Theory of Mind (ToM) ...
10/20/2020 ∙ by Runzhe Yang, et al. ∙ 0 ∙ share

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Safe Reinforcement Learning with Natural Language Constraints

In this paper, we tackle the problem of learning control policies for ta...
10/11/2020 ∙ by Tsung-Yen Yang, et al. ∙ 27 ∙ share

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Projection-Based Constrained Policy Optimization

We consider the problem of learning control policies that optimize a rew...
10/07/2020 ∙ by Tsung-Yen Yang, et al. ∙ 0 ∙ share

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Keep CALM and Explore: Language Models for Action Generation in Text-based Games

Text-based games present a unique challenge for autonomous agents to ope...
10/06/2020 ∙ by Shunyu Yao, et al. ∙ 0 ∙ share

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Guiding Attention for Self-Supervised Learning with Transformers

In this paper, we propose a simple and effective technique to allow for ...
10/06/2020 ∙ by Ameet Deshpande, et al. ∙ 0 ∙ share

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Learning Rewards from Linguistic Feedback

We explore unconstrained natural language feedback as a learning signal ...
09/30/2020 ∙ by Theodore R. Sumers, et al. ∙ 0 ∙ share

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Towards Unique and Informative Captioning of Images

Despite considerable progress, state of the art image captioning models ...
09/08/2020 ∙ by Zeyu Wang, et al. ∙ 7 ∙ share

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Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation

The ability to perform effective planning is crucial for building an ins...
07/11/2020 ∙ by Zhiwei Deng, et al. ∙ 11 ∙ share

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Accelerating Safe Reinforcement Learning with Constraint-mismatched Policies

We consider the problem of reinforcement learning when provided with a b...
06/20/2020 ∙ by Tsung-Yen Yang, et al. ∙ 0 ∙ share

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Universal Adversarial Attacks with Natural Triggers for Text Classification

Recent work has demonstrated the vulnerability of modern text classifier...
05/01/2020 ∙ by Liwei Song, et al. ∙ 0 ∙ share

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Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation

In the Vision-and-Language Navigation (VLN) task, an agent with egocentr...
03/31/2020 ∙ by Felix Yu, et al. ∙ 0 ∙ share

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A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation

We introduce a new algorithm for multi-objective reinforcement learning ...
08/21/2019 ∙ by Runzhe Yang, et al. ∙ 0 ∙ share

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Calibration, Entropy Rates, and Memory in Language Models

Building accurate language models that capture meaningful long-term depe...
06/11/2019 ∙ by Mark Braverman, et al. ∙ 1 ∙ share

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Task-Agnostic Dynamics Priors for Deep Reinforcement Learning

While model-based deep reinforcement learning (RL) holds great promise f...
05/13/2019 ∙ by Yilun Du, et al. ∙ 0 ∙ share

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Deep Transfer in Reinforcement Learning by Language Grounding

In this paper, we explore the utilization of natural language to drive t...
08/01/2017 ∙ by Karthik Narasimhan, et al. ∙ 0 ∙ share

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Representation Learning for Grounded Spatial Reasoning

The interpretation of spatial references is highly contextual, requiring...
07/13/2017 ∙ by Michael Janner, et al. ∙ 0 ∙ share

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Unsupervised Learning of Morphological Forests

This paper focuses on unsupervised modeling of morphological families, c...
02/22/2017 ∙ by Jiaming Luo, et al. ∙ 0 ∙ share

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Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge

This paper explores the task of translating natural language queries int...
08/09/2016 ∙ by Nicholas Locascio, et al. ∙ 0 ∙ share

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sk_p: a neural program corrector for MOOCs

We present a novel technique for automatic program correction in MOOCs, ...
07/11/2016 ∙ by Yewen Pu, et al. ∙ 0 ∙ share

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Nonparametric Spherical Topic Modeling with Word Embeddings

Traditional topic models do not account for semantic regularities in lan...
04/01/2016 ∙ by Kayhan Batmanghelich, et al. ∙ 0 ∙ share

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Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning

Most successful information extraction systems operate with access to a ...
03/25/2016 ∙ by Karthik Narasimhan, et al. ∙ 0 ∙ share

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Language Understanding for Text-based Games Using Deep Reinforcement Learning

In this paper, we consider the task of learning control policies for tex...
06/30/2015 ∙ by Karthik Narasimhan, et al. ∙ 0 ∙ share

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An Unsupervised Method for Uncovering Morphological Chains

Most state-of-the-art systems today produce morphological analysis based...
03/08/2015 ∙ by Karthik Narasimhan, et al. ∙ 0 ∙ share

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JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes

Markov jump processes (MJPs) are used to model a wide range of phenomena...
03/01/2015 ∙ by Jonathan H. Huggins, et al. ∙ 0 ∙ share

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Karthik Narasimhan

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