Julian McAuley

research

∙ 06/03/2022

Infinite Recommendation Networks: A Data-Centric Approach

We leverage the Neural Tangent Kernel and its equivalence to training in...

Noveen Sachdeva, et al. ∙

research

∙ 05/05/2022

Assistive Recipe Editing through Critiquing

There has recently been growing interest in the automatic generation of ...

Diego Antognini, et al. ∙

research

∙ 04/28/2022

Instilling Type Knowledge in Language Models via Multi-Task QA

Understanding human language often necessitates understanding entities a...

Shuyang Li, et al. ∙

research

∙ 04/13/2022

Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification

Prompt-based learning (i.e., prompting) is an emerging paradigm for expl...

Han Wang, et al. ∙

research

∙ 04/05/2022

FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes

Deepfakes and manipulated media are becoming a prominent threat due to t...

Paarth Neekhara, et al. ∙

research

∙ 04/04/2022

Coarse-to-Fine Sparse Sequential Recommendation

Sequential recommendation aims to model dynamic user behavior from histo...

Jiacheng Li, et al. ∙

research

∙ 03/22/2022

Achieving Conversational Goals with Unsupervised Post-hoc Knowledge Injection

A limitation of current neural dialog models is that they tend to suffer...

Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 03/11/2022

LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval

In this paper, we propose LaPraDoR, a pretrained dual-tower dense retrie...

Canwen Xu, et al. ∙

research

∙ 03/06/2022

Leashing the Inner Demons: Self-Detoxification for Language Models

Language models (LMs) can reproduce (or amplify) toxic language seen dur...

Canwen Xu, et al. ∙

research

∙ 02/27/2022

UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining

High-quality phrase representations are essential to finding topics and ...

Jiacheng Li, et al. ∙

research

∙ 02/15/2022

A Survey on Model Compression for Natural Language Processing

With recent developments in new architectures like Transformer and pretr...

Canwen Xu, et al. ∙

research

∙ 02/15/2022

A Survey on Dynamic Neural Networks for Natural Language Processing

Effectively scaling large Transformer models is a main driver of recent ...

Canwen Xu, et al. ∙

research

∙ 02/12/2022

Deep Performer: Score-to-Audio Music Performance Synthesis

Music performance synthesis aims to synthesize a musical score into a na...

Hao-Wen Dong, et al. ∙

research

∙ 02/06/2022

A Review of Modern Fashion Recommender Systems

The textile and apparel industries have grown tremendously over the last...

Yashar Deldjoo, et al. ∙

research

∙ 02/05/2022

Intent Contrastive Learning for Sequential Recommendation

Users' interactions with items are driven by various intents (e.g., prep...

Yongjun Chen, et al. ∙

research

∙ 01/13/2022

On Sampling Collaborative Filtering Datasets

We study the practical consequences of dataset sampling strategies on th...

Noveen Sachdeva, et al. ∙

research

∙ 12/09/2021

Self-Supervised Bot Play for Conversational Recommendation with Justifications

Conversational recommender systems offer the promise of interactive, eng...

Shuyang Li, et al. ∙

research

∙ 12/01/2021

Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning

Current approaches to Zero-Shot Learning (ZSL) struggle to learn general...

Zhe Liu, et al. ∙

research

∙ 11/03/2021

An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning

Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observe...

Yun Li, et al. ∙

research

∙ 10/21/2021

Locality-Sensitive Experience Replay for Online Recommendation

Online recommendation requires handling rapidly changing user preference...

Xiaocong Chen, et al. ∙

research

∙ 09/25/2021

Weakly Supervised Contrastive Learning for Chest X-Ray Report Generation

Radiology report generation aims at generating descriptive text from rad...

An Yan, et al. ∙

research

∙ 09/24/2021

Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decoding

Written language carries explicit and implicit biases that can distract ...

Zexue He, et al. ∙

research

∙ 09/23/2021

Modeling Dynamic Attributes for Next Basket Recommendation

Traditional approaches to next item and next basket recommendation typic...

Yongjun Chen, et al. ∙

research

∙ 09/08/2021

A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions

In light of the emergence of deep reinforcement learning (DRL) in recomm...

Xiaocong Chen, et al. ∙

research

∙ 09/07/2021

Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression

Recent studies on compression of pretrained language models (e.g., BERT)...

Canwen Xu, et al. ∙

research

∙ 09/01/2021

Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction

We investigate whether model extraction can be used to "steal" the weigh...

Zhenrui Yue, et al. ∙

research

∙ 08/14/2021

Contrastive Self-supervised Sequential Recommendation with Robust Augmentation

Sequential Recommendationdescribes a set of techniques to model dynamic ...

Zhiwei Liu, et al. ∙

research

∙ 08/03/2021

An Empirical Evaluation of End-to-End Polyphonic Optical Music Recognition

Previous work has shown that neural architectures are able to perform op...

Sachinda Edirisooriya, et al. ∙

research

∙ 07/13/2021

Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack Music

Modern keyboards allow a musician to play multiple instruments at the sa...

Hao-Wen Dong, et al. ∙

research

∙ 07/11/2021

SVP-CF: Selection via Proxy for Collaborative Filtering Data

We study the practical consequences of dataset sampling strategies on th...

Noveen Sachdeva, et al. ∙

research

∙ 07/05/2021

Weakly Supervised Named Entity Tagging with Learnable Logical Rules

We study the problem of building entity tagging systems by using a few r...

Jiacheng Li, et al. ∙

research

∙ 06/25/2021

Rationale-Inspired Natural Language Explanations with Commonsense

Explainable machine learning models primarily justify predicted labels u...

Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 06/15/2021

Unsupervised Enrichment of Persona-grounded Dialog with Background Stories

Humans often refer to personal narratives, life experiences, and events ...

Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 06/08/2021

Meta Learning for Knowledge Distillation

We present Meta Learning for Knowledge Distillation (MetaDistil), a simp...

Wangchunshu Zhou, et al. ∙

research

∙ 05/17/2021

SHARE: a System for Hierarchical Assistive Recipe Editing

We introduce SHARE: a System for Hierarchical Assistive Recipe Editing t...

Shuyang Li, et al. ∙

research

∙ 04/14/2021

Ask what's missing and what's useful: Improving Clarification Question Generation using Global Knowledge

The ability to generate clarification questions i.e., questions that ide...

Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 04/06/2021

Blow the Dog Whistle: A Chinese Dataset for Cant Understanding with Common Sense and World Knowledge

Cant is important for understanding advertising, comedies and dog-whistl...

Canwen Xu, et al. ∙

research

∙ 03/04/2021

WaveGuard: Understanding and Mitigating Audio Adversarial Examples

There has been a recent surge in adversarial attacks on deep learning ba...

Shehzeen Hussain, et al. ∙

research

∙ 02/15/2021

Cross-modal Adversarial Reprogramming

With the abundance of large-scale deep learning models, it has become po...

Paarth Neekhara, et al. ∙

research

∙ 01/30/2021

Expressive Neural Voice Cloning

Voice cloning is the task of learning to synthesize the voice of an unse...

Paarth Neekhara, et al. ∙

research

∙ 01/20/2021

Zero-shot Generalization in Dialog State Tracking through Generative Question Answering

Dialog State Tracking (DST), an integral part of modern dialog systems, ...

Shuyang Li, et al. ∙

research

∙ 10/07/2020

Like hiking? You probably enjoy nature: Persona-grounded Dialog with Commonsense Expansions

Existing persona-grounded dialog models often fail to capture simple imp...

Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 10/06/2020

Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays

Automatic medical image report generation has drawn growing attention du...

Jianmo Ni, et al. ∙

research

∙ 08/05/2020

MusPy: A Toolkit for Symbolic Music Generation

In this paper, we present MusPy, an open source Python library for symbo...

Hao-Wen Dong, et al. ∙

research

∙ 06/07/2020

BERT Loses Patience: Fast and Robust Inference with Early Exit

In this paper, we propose Patience-based Early Exit, a straightforward y...

Wangchunshu Zhou, et al. ∙

research

∙ 05/25/2020

How Useful are Reviews for Recommendation? A Critical Review and Potential Improvements

We investigate a growing body of work that seeks to improve recommender ...

Noveen Sachdeva, et al. ∙

research

∙ 05/16/2020

Speech Recognition and Multi-Speaker Diarization of Long Conversations

Speech recognition (ASR) and speaker diarization (SD) models have tradit...

Huanru Henry Mao, et al. ∙

research

∙ 04/07/2020

Interview: A Large-Scale Open-Source Corpus of Media Dialog

Existing conversational datasets consist either of written proxies for d...

Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 03/10/2020

ReZero is All You Need: Fast Convergence at Large Depth

Deep networks have enabled significant performance gains across domains,...

Thomas Bachlechner, et al. ∙

research

∙ 12/04/2019

Addressing Marketing Bias in Product Recommendations

Modern collaborative filtering algorithms seek to provide personalized p...

Mengting Wan, et al. ∙

Julian McAuley

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