Julian McAuley

research

∙ 08/28/2023

Reinforcement Learning for Generative AI: A Survey

Deep Generative AI has been a long-standing essential topic in the machi...

0 Yuanjiang Cao, et al. ∙

research

∙ 08/22/2023

On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems

Reinforcement learning serves as a potent tool for modeling dynamic user...

0 Xiaocong Chen, et al. ∙

research

∙ 08/19/2023

Large Language Models as Zero-Shot Conversational Recommenders

In this paper, we present empirical studies on conversational recommenda...

0 Zhankui He, et al. ∙

research

∙ 08/07/2023

Learning Concise and Descriptive Attributes for Visual Recognition

Recent advances in foundation models present new opportunities for inter...

0 An Yan, et al. ∙

research

∙ 07/05/2023

Comparing Apples to Apples: Generating Aspect-Aware Comparative Sentences from User Reviews

It is time-consuming to find the best product among many similar alterna...

0 Jessica Echterhoff, et al. ∙

research

∙ 06/26/2023

LongCoder: A Long-Range Pre-trained Language Model for Code Completion

In this paper, we introduce a new task for code completion that focuses ...

0 Daya Guo, et al. ∙

research

∙ 06/16/2023

CLIPSonic: Text-to-Audio Synthesis with Unlabeled Videos and Pretrained Language-Vision Models

Recent work has studied text-to-audio synthesis using large amounts of p...

0 Hao-Wen Dong, et al. ∙

research

∙ 06/05/2023

RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems

Large Language Models (LLMs) have greatly advanced code auto-completion ...

0 Tianyang Liu, et al. ∙

research

∙ 06/04/2023

Generative Flow Network for Listwise Recommendation

Personalized recommender systems fulfill the daily demands of customers ...

0 Shuchang Liu, et al. ∙

research

∙ 05/23/2023

Text Is All You Need: Learning Language Representations for Sequential Recommendation

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

0 Jiacheng Li, et al. ∙

research

∙ 05/15/2023

Large Language Models are Zero-Shot Rankers for Recommender Systems

Recently, large language models (LLMs) (e.g. GPT-4) have demonstrated im...

0 Yupeng Hou, et al. ∙

research

∙ 05/15/2023

"Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion

Sharing medical reports is essential for patient-centered care. A recent...

0 Zexue He, et al. ∙

research

∙ 04/04/2023

Unsupervised Improvement of Factual Knowledge in Language Models

Masked language modeling (MLM) plays a key role in pretraining large lan...

0 Nafis Sadeq, et al. ∙

research

∙ 04/03/2023

Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data

Chat models, such as ChatGPT, have shown impressive capabilities and hav...

0 Canwen Xu, et al. ∙

research

∙ 03/15/2023

Mirror: A Natural Language Interface for Data Querying, Summarization, and Visualization

We present Mirror, an open-source platform for data exploration and anal...

0 Canwen Xu, et al. ∙

research

∙ 02/06/2023

CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets

Open vocabulary models (e.g. CLIP) have shown strong performance on zero...

0 Zachary Novack, et al. ∙

research

∙ 01/11/2023

Data Distillation: A Survey

The popularity of deep learning has led to the curation of a vast number...

0 Noveen Sachdeva, et al. ∙

research

∙ 12/19/2022

Synthetic Pre-Training Tasks for Neural Machine Translation

Pre-training is an effective technique for ensuring robust performance o...

0 Zexue He, et al. ∙

research

∙ 12/14/2022

CLIPSep: Learning Text-queried Sound Separation with Noisy Unlabeled Videos

Recent years have seen progress beyond domain-specific sound separation ...

6 Hao-Wen Dong, et al. ∙

research

∙ 10/22/2022

Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders

Recently, the generality of natural language text has been leveraged to ...

0 Yupeng Hou, et al. ∙

research

∙ 10/21/2022

InforMask: Unsupervised Informative Masking for Language Model Pretraining

Masked language modeling is widely used for pretraining large language m...

0 Nafis Sadeq, et al. ∙

research

∙ 10/21/2022

Efficiently Tuned Parameters are Task Embeddings

Intermediate-task transfer can benefit a wide range of NLP tasks with pr...

4 Wangchunshu Zhou, et al. ∙

research

∙ 10/14/2022

Controlling Bias Exposure for Fair Interpretable Predictions

Recent work on reducing bias in NLP models usually focuses on protecting...

0 Zexue He, et al. ∙

research

∙ 10/14/2022

InterFair: Debiasing with Natural Language Feedback for Fair Interpretable Predictions

Debiasing methods in NLP models traditionally focus on isolating informa...

0 Bodhisattwa Prasad Majumder, et al. ∙

research

∙ 10/11/2022

CLIP also Understands Text: Prompting CLIP for Phrase Understanding

Contrastive Language-Image Pretraining (CLIP) efficiently learns visual ...

6 An Yan, et al. ∙

research

∙ 09/28/2022

UCEpic: Unifying Aspect Planning and Lexical Constraints for Explainable Recommendation

Personalized natural language generation for explainable recommendations...

0 Jiacheng Li, et al. ∙

research

∙ 09/12/2022

On Faithfulness and Coherence of Language Explanations for Recommendation Systems

Reviews contain rich information about product characteristics and user ...

0 Zhouhang Xie, et al. ∙

research

∙ 09/12/2022

Factual and Informative Review Generation for Explainable Recommendation

Recent models can generate fluent and grammatical synthetic reviews whil...

0 Zhouhang Xie, et al. ∙

research

∙ 09/07/2022

Improving Choral Music Separation through Expressive Synthesized Data from Sampled Instruments

Choral music separation refers to the task of extracting tracks of voice...

0 Ke Chen, et al. ∙

research

∙ 08/20/2022

Representing Knowledge by Spans: A Knowledge-Enhanced Model for Information Extraction

Knowledge-enhanced pre-trained models for language representation have b...

0 Jiacheng Li, et al. ∙

research

∙ 08/10/2022

Deep Reinforcement Learning for Dynamic Recommendation with Model-agnostic Counterfactual Policy Synthesis

Recent advances in recommender systems have proved the potential of Rein...

0 Siyu Wang, et al. ∙

research

∙ 08/07/2022

Generating Negative Samples for Sequential Recommendation

To make Sequential Recommendation (SR) successful, recent works focus on...

2 Yongjun Chen, et al. ∙

research

∙ 07/26/2022

Bundle MCR: Towards Conversational Bundle Recommendation

Bundle recommender systems recommend sets of items (e.g., pants, shirt, ...

0 Zhankui He, et al. ∙

research

∙ 07/25/2022

Contrastive Learning for Interactive Recommendation in Fashion

Recommender systems and search are both indispensable in facilitating pe...

0 Karin Sevegnani, et al. ∙

research

∙ 07/14/2022

Multitrack Music Transformer: Learning Long-Term Dependencies in Music with Diverse Instruments

Existing approaches for generating multitrack music with transformer mod...

0 Hao-Wen Dong, et al. ∙

research

∙ 06/30/2022

Personalized Showcases: Generating Multi-Modal Explanations for Recommendations

Existing explanation models generate only text for recommendations but s...

0 An Yan, et al. ∙

research

∙ 06/03/2022

Infinite Recommendation Networks: A Data-Centric Approach

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

0 Noveen Sachdeva, et al. ∙

research

∙ 05/05/2022

Assistive Recipe Editing through Critiquing

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

6 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...

6 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...

0 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...

3 Paarth Neekhara, et al. ∙

research

∙ 04/04/2022

Coarse-to-Fine Sparse Sequential Recommendation

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

0 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...

0 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...

0 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...

0 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 ...

0 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...

0 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 ...

0 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...

0 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...

0 Yashar Deldjoo, et al. ∙

Julian McAuley

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