b'Yiming Yang'

research

∙ 08/12/2023

Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation

Graph-based diffusion models have shown promising results in terms of ge...

0 Junwei Huang, et al. ∙

research

∙ 08/07/2023

Efficient Temporal Sentence Grounding in Videos with Multi-Teacher Knowledge Distillation

Temporal Sentence Grounding in Videos (TSGV) aims to detect the event ti...

0 Renjie Liang, et al. ∙

research

∙ 07/22/2023

Balancing Exploration and Exploitation in Hierarchical Reinforcement Learning via Latent Landmark Graphs

Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) is a promis...

0 Qingyang Zhang, et al. ∙

research

∙ 05/24/2023

PESCO: Prompt-enhanced Self Contrastive Learning for Zero-shot Text Classification

We present PESCO, a novel contrastive learning framework that substantia...

0 Yau-Shian Wang, et al. ∙

research

∙ 05/22/2023

Policy Representation via Diffusion Probability Model for Reinforcement Learning

Popular reinforcement learning (RL) algorithms tend to produce a unimoda...

0 Long Yang, et al. ∙

research

∙ 05/19/2023

Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning with LLMs

A popular approach for improving the correctness of output from large la...

0 Pranjal Aggarwal, et al. ∙

research

∙ 05/11/2023

Active Retrieval Augmented Generation

Despite the remarkable ability of large language models (LMs) to compreh...

0 Zhengbao Jiang, et al. ∙

research

∙ 05/04/2023

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Recent AI-assistant agents, such as ChatGPT, predominantly rely on super...

0 Zhiqing Sun, et al. ∙

research

∙ 04/24/2023

Generation-driven Contrastive Self-training for Zero-shot Text Classification with Instruction-tuned GPT

Moreover, GPT-based zero-shot classification models tend to make indepen...

0 Ruohong Zhang, et al. ∙

research

∙ 03/30/2023

Self-Refine: Iterative Refinement with Self-Feedback

Like people, LLMs do not always generate the best text for a given gener...

2 Aman Madaan, et al. ∙

research

∙ 02/16/2023

DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization

Neural network-based Combinatorial Optimization (CO) methods have shown ...

0 Zhiqing Sun, et al. ∙

research

∙ 02/16/2023

A Neural PDE Solver with Temporal Stencil Modeling

Numerical simulation of non-linear partial differential equations plays ...

0 Zhiqing Sun, et al. ∙

research

∙ 02/15/2023

Learning Performance-Improving Code Edits

The waning of Moore's Law has shifted the focus of the tech industry tow...

2 Aman Madaan, et al. ∙

research

∙ 02/03/2023

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers

We propose a new class of linear Transformers called FourierLearner-Tran...

0 Krzysztof Marcin Choromanski, et al. ∙

research

∙ 11/18/2022

PAL: Program-aided Language Models

Large language models (LLMs) have recently demonstrated an impressive ab...

0 Luyu Gao, et al. ∙

research

∙ 10/13/2022

Language Models of Code are Few-Shot Commonsense Learners

We address the general task of structured commonsense reasoning: given a...

0 Aman Madaan, et al. ∙

research

∙ 10/08/2022

DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems

Recently, deep reinforcement learning (DRL) models have shown promising ...

0 Ruizhong Qiu, et al. ∙

research

∙ 10/04/2022

Recitation-Augmented Language Models

We propose a new paradigm to help Large Language Models (LLMs) generate ...

0 Zhiqing Sun, et al. ∙

research

∙ 07/15/2022

FLOWGEN: Fast and slow graph generation

We present FLOWGEN, a graph-generation model inspired by the dual-proces...

0 Aman Madaan, et al. ∙

research

∙ 05/25/2022

Conditional set generation using Seq2seq models

Conditional set generation learns a mapping from an input sequence of to...

0 Aman Madaan, et al. ∙

research

∙ 04/02/2022

Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions

Extreme Multi-label Text Classification (XMTC) has been a tough challeng...

0 Ruohong Zhang, et al. ∙

research

∙ 04/02/2022

Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification

Extreme multi-label text classification (XMTC) is the task of tagging ea...

0 Ruohong Zhang, et al. ∙

research

∙ 03/31/2022

Traffic4cast at NeurIPS 2021 – Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes

The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that...

4 Christian Eichenberger, et al. ∙

research

∙ 01/16/2022

Memory-assisted prompt editing to improve GPT-3 after deployment

Large LMs such as GPT-3, while powerful, are not immune to mistakes, but...

0 Aman Madaan, et al. ∙

research

∙ 12/16/2021

Improving scripts with a memory of natural feedback

How can an end-user provide feedback if a deployed structured prediction...

0 Niket Tandon, et al. ∙

research

∙ 12/15/2021

Interscript: A dataset for interactive learning of scripts through error feedback

How can an end-user provide feedback if a deployed structured prediction...

0 Niket Tandon, et al. ∙

research

∙ 10/21/2021

Dual Encoding U-Net for Spatio-Temporal Domain Shift Frame Prediction

The landscape of city-wide mobility behaviour has altered significantly ...

0 Jay Santokhi, et al. ∙

research

∙ 10/08/2021

KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering

Current Open-Domain Question Answering (ODQA) model paradigm often conta...

0 Donghan Yu, et al. ∙

research

∙ 04/18/2021

Improving Neural Model Performance through Natural Language Feedback on Their Explanations

A class of explainable NLP models for reasoning tasks support their deci...

0 Aman Madaan, et al. ∙

research

∙ 04/16/2021

Improving Hyper-Relational Knowledge Graph Completion

Different from traditional knowledge graphs (KGs) where facts are repres...

0 Donghan Yu, et al. ∙

research

∙ 04/06/2021

General Robot Dynamics Learning and Gen2Real

Acquiring dynamics is an essential topic in robot learning, but up-to-da...

0 Dengpeng Xing, et al. ∙

research

∙ 02/15/2021

Meta Back-translation

Back-translation is an effective strategy to improve the performance of ...

0 Hieu Pham, et al. ∙

research

∙ 11/25/2020

Handling Noisy Labels via One-Step Abductive Multi-Target Learning

Learning from noisy labels is an important concern because of the lack o...

13 Yongquan Yang, et al. ∙

research

∙ 11/21/2020

Rethinking Transformer-based Set Prediction for Object Detection

DETR is a recently proposed Transformer-based method which views object ...

0 Zhiqing Sun, et al. ∙

research

∙ 11/02/2020

On the Sentence Embeddings from Pre-trained Language Models

Pre-trained contextual representations like BERT have achieved great suc...

0 Bohan Li, et al. ∙

research

∙ 10/20/2020

Neural Language Modeling for Contextualized Temporal Graph Generation

This paper presents the first study on using large-scale pre-trained lan...

0 Aman Madaan, et al. ∙

research

∙ 10/02/2020

JAKET: Joint Pre-training of Knowledge Graph and Language Understanding

Knowledge graphs (KGs) contain rich information about world knowledge, e...

0 Donghan Yu, et al. ∙

research

∙ 09/18/2020

Unsupervised Parallel Corpus Mining on Web Data

With a large amount of parallel data, neural machine translation systems...

0 Guokun Lai, et al. ∙

research

∙ 07/06/2020

Kernel Stein Generative Modeling

We are interested in gradient-based Explicit Generative Modeling where s...

11 Wei-Cheng Chang, et al. ∙

research

∙ 06/29/2020

An EM Approach to Non-autoregressive Conditional Sequence Generation

Autoregressive (AR) models have been the dominating approach to conditio...

0 Zhiqing Sun, et al. ∙

research

∙ 06/12/2020

Generalized Multi-Relational Graph Convolution Network

Graph Convolutional Networks (GCNs) have received increasing attention i...

0 Donghan Yu, et al. ∙

research

∙ 06/05/2020

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

With the success of language pretraining, it is highly desirable to deve...

0 Zihang Dai, et al. ∙

research

∙ 05/02/2020

Predicting Performance for Natural Language Processing Tasks

Given the complexity of combinations of tasks, languages, and domains in...

0 Mengzhou Xia, et al. ∙

research

∙ 04/29/2020

Politeness Transfer: A Tag and Generate Approach

This paper introduces a new task of politeness transfer which involves c...

0 Aman Madaan, et al. ∙

research

∙ 04/24/2020

Practical Comparable Data Collection for Low-Resource Languages via Images

We propose a method of curating high-quality comparable training data fo...

0 Aman Madaan, et al. ∙

research

∙ 04/24/2020

Explainable Unsupervised Change-point Detection via Graph Neural Networks

Change-point detection (CPD) aims at detecting the abrupt property chang...

14 Ruohong Zhang, et al. ∙

research

∙ 04/06/2020

MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

Natural Language Processing (NLP) has recently achieved great success by...

0 Zhiqing Sun, et al. ∙

research

∙ 03/25/2020

VIOLIN: A Large-Scale Dataset for Video-and-Language Inference

We introduce a new task, Video-and-Language Inference, for joint multimo...

17 Jingzhou Liu, et al. ∙

research

∙ 03/17/2020

An Algorithm for Computing a Minimal Comprehensive Gröbner Basis of a Parametric Polynomial System

An algorithm to generate a minimal comprehensive Gröbner basis of a par...

0 Deepak Kapur, et al. ∙

research

∙ 02/10/2020

Pre-training Tasks for Embedding-based Large-scale Retrieval

We consider the large-scale query-document retrieval problem: given a qu...

4 Wei-Cheng Chang, et al. ∙

Yiming Yang

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