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09/20/2023
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
Generative Large Language Models (LLMs) have achieved remarkable advance...
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07/21/2023
Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization
Offline reinforcement learning (RL) has received considerable attention ...
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07/06/2023
Offline Reinforcement Learning with Imbalanced Datasets
The prevalent use of benchmarks in current offline reinforcement learnin...
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05/25/2023
PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning
Offline-to-online reinforcement learning (RL), by combining the benefits...
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05/23/2023
Condensing Multilingual Knowledge with Lightweight Language-Specific Modules
Incorporating language-specific (LS) modules is a proven method to boost...
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05/03/2023
Towards Being Parameter-Efficient: A Stratified Sparsely Activated Transformer with Dynamic Capacity
Mixture-of-experts (MoE) models that employ sparse activation have demon...
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03/28/2023
Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization
Most offline reinforcement learning (RL) methods suffer from the trade-o...
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02/10/2023
Language-Aware Multilingual Machine Translation with Self-Supervised Learning
Multilingual machine translation (MMT) benefits from cross-lingual trans...
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02/03/2023
Mind the Gap: Offline Policy Optimization for Imperfect Rewards
Reward function is essential in reinforcement learning (RL), serving as ...
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01/28/2023
SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning
Offline safe RL is of great practical relevance for deploying agents in ...
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10/15/2022
A Policy-Guided Imitation Approach for Offline Reinforcement Learning
Offline reinforcement learning (RL) methods can generally be categorized...
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07/20/2022
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations
We study the problem of offline Imitation Learning (IL) where an agent a...
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07/01/2022
Discriminator-Guided Model-Based Offline Imitation Learning
Offline imitation learning (IL) is a powerful method to solve decision-m...
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05/23/2022
The Importance of Being Parameters: An Intra-Distillation Method for Serious Gains
Recent model pruning methods have demonstrated the ability to remove red...
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05/23/2022
Distance-Sensitive Offline Reinforcement Learning
In offline reinforcement learning (RL), one detrimental issue to policy ...
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04/29/2022
Por Qué Não Utiliser Alla Språk? Mixed Training with Gradient Optimization in Few-Shot Cross-Lingual Transfer
The current state-of-the-art for few-shot cross-lingual transfer learnin...
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12/06/2021
VAE based Text Style Transfer with Pivot Words Enhancement Learning
Text Style Transfer (TST) aims to alter the underlying style of the sour...
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10/22/2021
Adaptive Bridge between Training and Inference for Dialogue
Although exposure bias has been widely studied in some NLP tasks, it fac...
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10/14/2021
Offline Reinforcement Learning with Soft Behavior Regularization
Most prior approaches to offline reinforcement learning (RL) utilize beh...
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09/14/2021
Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction
Zero-shot cross-lingual information extraction (IE) describes the constr...
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09/09/2021
BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation
The success of bidirectional encoders using masked language models, such...
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07/19/2021
Cross-Lingual BERT Contextual Embedding Space Mapping with Isotropic and Isometric Conditions
Typically, a linearly orthogonal transformation mapping is learned by al...
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07/19/2021
Constraints Penalized Q-Learning for Safe Offline Reinforcement Learning
We study the problem of safe offline reinforcement learning (RL), the go...
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05/16/2021
Model-Based Offline Planning with Trajectory Pruning
Offline reinforcement learning (RL) enables learning policies using pre-...
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03/03/2021
Zero-Shot Cross-Lingual Dependency Parsing through Contextual Embedding Transformation
Linear embedding transformation has been shown to be effective for zero-...
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03/03/2021
Gradual Fine-Tuning for Low-Resource Domain Adaptation
Fine-tuning is known to improve NLP models by adapting an initial model ...
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02/23/2021
DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning
Thermal power generation plays a dominant role in the world's electricit...
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11/26/2020
Copy-and-Patch Binary Code Generation
Runtime compilation of runtime-constructed code is becoming standard pra...
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07/04/2018
