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Grounding Language to Non-Markovian Tasks with No Supervision of Task Specifications

https://doi.org/10.15607/rss.2020.xvi.016

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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On a Decision Method in Restricted Second Order Arithmetic

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Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning

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A learning based approach to control synthesis of Markov decision processes for linear temporal logic specifications

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Learning to Parse Natural Language to Grounded Reward Functions with Weak Supervision

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Reinforcement learning with temporal logic rewards

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Learning Dependency-Based Compositional Semantics

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Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions

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Weakly Supervised Training of Semantic Parsers

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Sequence-to-Sequence Language Grounding of Non-Markovian Task Specifications

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Planning with State Abstractions for Non-Markovian Task Specifications

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Learning to Interpret Natural Language Navigation Instructions from Observations

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Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences

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Planning with Abstract Markov Decision Processes

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Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language

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Semantic Parsing on Freebase from Question-Answer Pairs

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Alignment-Based Compositional Semantics for Instruction Following

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Mapping Instructions and Visual Observations to Actions with Reinforcement Learning

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From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood

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Weakly Supervised Semantic Parsing with Abstract Examples

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Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation

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Reinforcement learning for mapping instructions to actions

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Neural Machine Translation by Jointly Learning to Align and Translate

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Sequence to Sequence Learning with Neural Networks

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Adam: A Method for Stochastic Optimization

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Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

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Environment-Independent Task Specifications via GLTL

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Speaker-Follower Models for Vision-and-Language Navigation

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Teaching Multiple Tasks to an RL Agent using LTL

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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The Return of Formal Requirements Engineering in the Era of Large Language Models

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Using Language to Generate State Abstractions for Long-Range Planning in Outdoor Environments

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Data-Efficient Learning of Natural Language to Linear Temporal Logic Translators for Robot Task Specification

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Cook2LTL: Translating Cooking Recipes to LTL Formulae using Large Language Models

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AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers

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Skill Transfer for Temporal Task Specification

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Plug in the Safety Chip: Enforcing Constraints for LLM-driven Robot Agents

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Lang2LTL-2: Grounding Spatiotemporal Navigation Commands Using Large Language and Vision-Language Models

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VerifyLLM: LLM-Based Pre-Execution Task Plan Verification for Robots

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LLM-Enabled Low-Altitude UAV Natural Language Navigation via Signal Temporal Logic Specification Translation and Repair

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Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

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Task and Motion Planning for Execution in the Real

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Property-Based Testing for Validating User Privacy-Related Functionalities in Social Media Apps

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NL2TL: Transforming Natural Languages to Temporal Logics using Large Language Models

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Self-Supervised Skill Learning for Semi-Supervised Long-Horizon Instruction Following

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Robots that can see : Learning visually guided behavior

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