b'Yingbo Zhou'

research

∙ 09/15/2023

Investigating Answerability of LLMs for Long-Form Question Answering

As we embark on a new era of LLMs, it becomes increasingly crucial to un...

0 Meghana Moorthy Bhat, et al. ∙

research

∙ 08/24/2023

Exploring the Integration Strategies of Retriever and Large Language Models

The integration of retrieved passages and large language models (LLMs), ...

0 Ye Liu, et al. ∙

research

∙ 07/27/2023

EqGAN: Feature Equalization Fusion for Few-shot Image Generation

Due to the absence of fine structure and texture information, existing f...

1 Yingbo Zhou, et al. ∙

research

∙ 05/23/2023

Few-shot Unified Question Answering: Tuning Models or Prompts?

Question-answering (QA) tasks often investigate specific question types,...

0 Srijan Bansal, et al. ∙

research

∙ 05/18/2023

UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild

Achieving machine autonomy and human control often represent divergent o...

0 Can Qin, et al. ∙

research

∙ 05/12/2023

Answering Complex Questions over Text by Hybrid Question Parsing and Execution

The dominant paradigm of textual question answering systems is based on ...

1 Ye Liu, et al. ∙

research

∙ 05/03/2023

CodeGen2: Lessons for Training LLMs on Programming and Natural Languages

Large language models (LLMs) have demonstrated remarkable abilities in r...

3 Erik Nijkamp, et al. ∙

research

∙ 04/03/2023

Efficiently Aligned Cross-Lingual Transfer Learning for Conversational Tasks using Prompt-Tuning

Cross-lingual transfer of language models trained on high-resource langu...

2 Lifu Tu, et al. ∙

research

∙ 01/28/2023

CyclicFL: A Cyclic Model Pre-Training Approach to Efficient Federated Learning

Since random initial models in Federated Learning (FL) can easily result...

1 Pengyu Zhang, et al. ∙

research

∙ 12/17/2022

Unsupervised Dense Retrieval Deserves Better Positive Pairs: Scalable Augmentation with Query Extraction and Generation

Dense retrievers have made significant strides in obtaining state-of-the...

0 Rui Meng, et al. ∙

research

∙ 11/22/2022

Best-k Search Algorithm for Neural Text Generation

Modern natural language generation paradigms require a good decoding str...

0 Jiacheng Xu, et al. ∙

research

∙ 11/09/2022

Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Database

Parsing natural language questions into executable logical forms is a us...

0 Ye Liu, et al. ∙

research

∙ 10/22/2022

Prompt-Tuning Can Be Much Better Than Fine-Tuning on Cross-lingual Understanding With Multilingual Language Models

Pre-trained multilingual language models show significant performance ga...

0 Lifu Tu, et al. ∙

research

∙ 08/20/2022

General-to-Specific Transfer Labeling for Domain Adaptable Keyphrase Generation

Training keyphrase generation (KPG) models requires a large amount of an...

3 Rui Meng, et al. ∙

research

∙ 07/21/2022

BigIssue: A Realistic Bug Localization Benchmark

As machine learning tools progress, the inevitable question arises: How ...

15 Paul Kassianik, et al. ∙

research

∙ 07/05/2022

Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control

Abstractive summarization systems leveraging pre-training language model...

0 Haopeng Zhang, et al. ∙

research

∙ 05/18/2022

Modeling Multi-hop Question Answering as Single Sequence Prediction

Fusion-in-decoder (Fid) (Izacard and Grave, 2020) is a generative questi...

3 Semih Yavuz, et al. ∙

research

∙ 05/17/2022

OneAligner: Zero-shot Cross-lingual Transfer with One Rich-Resource Language Pair for Low-Resource Sentence Retrieval

Aligning parallel sentences in multilingual corpora is essential to cura...

0 Tong Niu, et al. ∙

research

∙ 03/25/2022

A Conversational Paradigm for Program Synthesis

Program synthesis strives to generate a computer program as a solution t...

11 Erik Nijkamp, et al. ∙

research

∙ 03/15/2022

Long Document Summarization with Top-down and Bottom-up Inference

Text summarization aims to condense long documents and retain key inform...

11 Bo Pang, et al. ∙

research

∙ 03/14/2022

Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering

While both extractive and generative readers have been successfully appl...

4 Man Luo, et al. ∙

research

∙ 02/22/2022

Efficient and Differentiable Conformal Prediction with General Function Classes

Quantifying the data uncertainty in learning tasks is often done by lear...

0 Yu Bai, et al. ∙

research

∙ 10/28/2021

Dense Hierarchical Retrieval for Open-Domain Question Answering

Dense neural text retrieval has achieved promising results on open-domai...

0 Ye Liu, et al. ∙

research

∙ 10/21/2021

Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization

In Domain Generalization (DG) settings, models trained on a given set of...

0 Devansh Arpit, et al. ∙

research

∙ 09/20/2021

Merlion: A Machine Learning Library for Time Series

We introduce Merlion, an open-source machine learning library for time s...

78 Aadyot Bhatnagar, et al. ∙

research

∙ 09/17/2021

RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

Existing KBQA approaches, despite achieving strong performance on i.i.d....

8 Xi Ye, et al. ∙

research

∙ 04/26/2021

Focused Attention Improves Document-Grounded Generation

Document grounded generation is the task of using the information provid...

26 Shrimai Prabhumoye, et al. ∙

research

∙ 10/24/2020

Unsupervised Paraphrase Generation via Dynamic Blocking

We propose Dynamic Blocking, a decoding algorithm which enables large-sc...

5 Tong Niu, et al. ∙

research

∙ 10/24/2020

CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers

Dialogue state trackers have made significant progress on benchmark data...

2 Shiyang Li, et al. ∙

research

∙ 10/22/2020

Online Structured Meta-learning

Learning quickly is of great importance for machine intelligence deploye...

6 Huaxiu Yao, et al. ∙

research

∙ 10/07/2020

Representation Learning for Sequence Data with Deep Autoencoding Predictive Components

We propose Deep Autoencoding Predictive Components (DAPC) – a self-super...

0 Junwen Bai, et al. ∙

research

∙ 06/05/2020

WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos

Online action detection in untrimmed videos aims to identify an action a...

0 Mingfei Gao, et al. ∙

research

∙ 05/04/2020

Fast and Robust Unsupervised Contextual Biasing for Speech Recognition

Automatic speech recognition (ASR) system is becoming a ubiquitous techn...

0 Young Mo Kang, et al. ∙

research

∙ 03/01/2020

Differentially Private Deep Learning with Smooth Sensitivity

Ensuring the privacy of sensitive data used to train modern machine lear...

14 Lichao Sun, et al. ∙

research

∙ 06/05/2019

Private Deep Learning with Teacher Ensembles

Privacy-preserving deep learning is crucial for deploying deep neural ne...

0 Lichao Sun, et al. ∙

research

∙ 03/31/2019

Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting

Addressing catastrophic forgetting is one of the key challenges in conti...

6 Xilai Li, et al. ∙

research

∙ 07/01/2018

Augmented Cyclic Adversarial Learning for Domain Adaptation

Training a model to perform a task typically requires a large amount of ...

2 Ehsan Hosseini-Asl, et al. ∙

research

∙ 04/03/2018

End-to-End Dense Video Captioning with Masked Transformer

Dense video captioning aims to generate text descriptions for all events...

0 Luowei Zhou, et al. ∙

research

∙ 03/27/2018

A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation

Domain adaptation plays an important role for speech recognition models,...

0 Ehsan Hosseini-Asl, et al. ∙

research

∙ 12/19/2017

Improved Regularization Techniques for End-to-End Speech Recognition

Regularization is important for end-to-end speech models, since the mode...

0 Yingbo Zhou, et al. ∙

research

∙ 12/19/2017

Improving End-to-End Speech Recognition with Policy Learning

Connectionist temporal classification (CTC) is widely used for maximum l...

0 Yingbo Zhou, et al. ∙

research

∙ 05/21/2017

Spelling Correction as a Foreign Language

In this paper, we reformulated the spell correction problem as a machine...

0 Yingbo Zhou, et al. ∙

research

∙ 05/23/2016

On Optimality Conditions for Auto-Encoder Signal Recovery

Auto-Encoders are unsupervised models that aim to learn patterns from ob...

0 Devansh Arpit, et al. ∙

research

∙ 03/04/2016

Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks

While the authors of Batch Normalization (BN) identify and address an im...

0 Devansh Arpit, et al. ∙

research

∙ 12/05/2015

Maximum Entropy Binary Encoding for Face Template Protection

In this paper we present a framework for secure identification using dee...

0 Rohit Kumar Pandey, et al. ∙

research

∙ 06/14/2015

Deep Secure Encoding: An Application to Face Recognition

In this paper we present Deep Secure Encoding: a framework for secure cl...

0 Rohit Pandey, et al. ∙

research

∙ 05/21/2015

Why Regularized Auto-Encoders learn Sparse Representation?

While the authors of Batch Normalization (BN) identify and address an im...

0 Devansh Arpit, et al. ∙

research

∙ 05/06/2014

Is Joint Training Better for Deep Auto-Encoders?

Traditionally, when generative models of data are developed via deep arc...

0 Yingbo Zhou, et al. ∙

research

∙ 07/01/2013

Challenges in Representation Learning: A report on three machine learning contests

The ICML 2013 Workshop on Challenges in Representation Learning focused ...

0 Ian J. Goodfellow, et al. ∙

Yingbo Zhou

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