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08/27/2023
Situated Natural Language Explanations
Natural language is among the most accessible tools for explaining decis...
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07/19/2023
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
Modeling customer shopping intentions is a crucial task for e-commerce, ...
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05/30/2023
Graph Reasoning for Question Answering with Triplet Retrieval
Answering complex questions often requires reasoning over knowledge grap...
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05/19/2023
CCGen: Explainable Complementary Concept Generation in E-Commerce
We propose and study Complementary Concept Generation (CCGen): given a c...
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04/26/2023
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond
This paper presents a comprehensive and practical guide for practitioner...
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02/19/2023
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
Knowledge distillation has been shown to be a powerful model compression...
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10/08/2022
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding
E-commerce query understanding is the process of inferring the shopping ...
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09/15/2022
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites
E-commerce queries are often short and ambiguous. Consequently, query un...
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09/15/2022
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks
Graph neural network (GNN) pre-training methods have been proposed to en...
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06/15/2022
Condensing Graphs via One-Step Gradient Matching
As training deep learning models on large dataset takes a lot of time an...
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05/15/2022
SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models
Recent research showed promising results on combining pretrained languag...
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03/28/2022
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
Predicting missing facts in a knowledge graph (KG) is crucial as modern ...
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02/06/2022
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models
Recent research has shown the existence of significant redundancy in lar...
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09/15/2021
Self-Training with Differentiable Teacher
Self-training achieves enormous success in various semi-supervised and w...
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09/15/2021
ARCH: Efficient Adversarial Regularized Training with Caching
Adversarial regularization can improve model generalization in many natu...
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06/16/2021
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
Weak supervision has shown promising results in many natural language pr...
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05/25/2021
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
The Lottery Ticket Hypothesis suggests that an over-parametrized network...
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04/11/2021
Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach
Adversarial training has been shown to improve the generalization perfor...
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03/20/2021
Token-wise Curriculum Learning for Neural Machine Translation
Existing curriculum learning approaches to Neural Machine Translation (N...
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02/20/2021
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach
Reliable automatic evaluation of dialogue systems under an interactive e...
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10/22/2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Fine-tuned pre-trained language models can suffer from severe miscalibra...
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10/15/2020
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach
Fine-tuned pre-trained language models (LMs) achieve enormous success in...
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06/28/2020
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision
We study the open-domain named entity recognition (NER) problem under di...
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03/21/2020
Deep Reinforcement Learning with Smooth Policy
Deep neural networks have been widely adopted in modern reinforcement le...
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02/21/2020
Transformer Hawkes Process
Modern data acquisition routinely produce massive amounts of event seque...
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11/08/2019
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Transfer learning has fundamentally changed the landscape of natural lan...
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11/07/2019
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing
Many multi-domain neural machine translation (NMT) models achieve knowle...
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10/30/2019
Contextual Text Denoising with Masked Language Models
Recently, with the help of deep learning models, significant advances ha...
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09/04/2019
Meta Learning with Relational Information for Short Sequences
This paper proposes a new meta-learning method -- named HARMLESS (HAwkes...
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08/08/2019
On the Variance of the Adaptive Learning Rate and Beyond
The learning rate warmup heuristic achieves remarkable success in stabil...
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08/05/2019
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
Deep neural networks have revolutionized many real world applications, d...
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05/01/2019
On Scalable and Efficient Computation of Large Scale Optimal Transport
Optimal Transport (OT) naturally arises in many machine learning applica...
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12/28/2018
On Computation and Generalization of GANs with Spectrum Control
Generative Adversarial Networks (GANs), though powerful, is hard to trai...
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11/03/2018
