b'Wenhan Xiong'

research

∙ 08/30/2023

LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models

In recent years, there have been remarkable advancements in the performa...

0 Chi Han, et al. ∙

research

∙ 08/24/2023

Code Llama: Open Foundation Models for Code

We release Code Llama, a family of large language models for code based ...

0 Baptiste Roziere, et al. ∙

research

∙ 07/21/2023

Prompting Large Language Models with Speech Recognition Abilities

Large language models have proven themselves highly flexible, able to so...

0 Yassir Fathullah, et al. ∙

research

∙ 05/23/2023

Text-guided 3D Human Generation from 2D Collections

3D human modeling has been widely used for engaging interaction in gamin...

0 Tsu-Jui Fu, et al. ∙

research

∙ 05/23/2023

Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality

Contrastively trained vision-language models have achieved remarkable pr...

0 Harman Singh, et al. ∙

research

∙ 05/21/2023

Multi-Head State Space Model for Speech Recognition

State space models (SSMs) have recently shown promising results on small...

0 Yassir Fathullah, et al. ∙

research

∙ 05/04/2023

VideoOFA: Two-Stage Pre-Training for Video-to-Text Generation

We propose a new two-stage pre-training framework for video-to-text gene...

0 Xilun Chen, et al. ∙

research

∙ 03/09/2023

3DGen: Triplane Latent Diffusion for Textured Mesh Generation

Latent diffusion models for image generation have crossed a quality thre...

0 Anchit Gupta, et al. ∙

research

∙ 03/07/2023

CLIP-Layout: Style-Consistent Indoor Scene Synthesis with Semantic Furniture Embedding

Indoor scene synthesis involves automatically picking and placing furnit...

0 Jingyu Liu, et al. ∙

research

∙ 10/25/2022

Bridging the Training-Inference Gap for Dense Phrase Retrieval

Building dense retrievers requires a series of standard procedures, incl...

0 Gyuwan Kim, et al. ∙

research

∙ 09/21/2022

Adapting Pretrained Text-to-Text Models for Long Text Sequences

We present an empirical study of adapting an existing pretrained text-to...

5 Wenhan Xiong, et al. ∙

research

∙ 01/10/2022

SCROLLS: Standardized CompaRison Over Long Language Sequences

NLP benchmarks have largely focused on short texts, such as sentences an...

0 Uri Shaham, et al. ∙

research

∙ 12/14/2021

Boosted Dense Retriever

We propose DrBoost, a dense retrieval ensemble inspired by boosting. DrB...

0 Patrick Lewis, et al. ∙

research

∙ 12/14/2021

Simple Local Attentions Remain Competitive for Long-Context Tasks

Many NLP tasks require processing long contexts beyond the length limit ...

0 Wenhan Xiong, et al. ∙

research

∙ 12/10/2021

Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation

Most existing vision-language pre-training methods focus on understandin...

0 Tianyi Liu, et al. ∙

research

∙ 10/13/2021

Open-Domain Question-Answering for COVID-19 and Other Emergent Domains

Since late 2019, COVID-19 has quickly emerged as the newest biomedical d...

0 Sharon Levy, et al. ∙

research

∙ 05/31/2021

Zero-shot Fact Verification by Claim Generation

Neural models for automated fact verification have achieved promising re...

0 Liangming Pan, et al. ∙

research

∙ 10/23/2020

Unsupervised Multi-hop Question Answering by Question Generation

Obtaining training data for Multi-hop Question Answering (QA) is extreme...

0 Liangming Pan, et al. ∙

research

∙ 09/27/2020

Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

We propose a simple and efficient multi-hop dense retrieval approach for...

0 Wenhan Xiong, et al. ∙

research

∙ 04/30/2020

Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering

To extract answers from a large corpus, open-domain question answering (...

0 Wenhan Xiong, et al. ∙

research

∙ 04/15/2020

HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data

Existing question answering datasets focus on dealing with homogeneous i...

1 Wenhu Chen, et al. ∙

research

∙ 04/06/2020

Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games

We propose the new problem of learning to recover reasoning chains from ...

0 Yufei Feng, et al. ∙

research

∙ 12/20/2019

Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model

Recent breakthroughs of pretrained language models have shown the effect...

0 Wenhan Xiong, et al. ∙

research

∙ 10/31/2019

Do Multi-hop Readers Dream of Reasoning Chains?

General Question Answering (QA) systems over texts require the multi-hop...

0 Haoyu Wang, et al. ∙

research

∙ 09/17/2019

Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

A key challenge of multi-hop question answering (QA) in the open-domain ...

0 Wenhan Xiong, et al. ∙

research

∙ 09/13/2019

Towards Open-Domain Named Entity Recognition via Neural Correction Models

Named Entity Recognition (NER) plays an important role in a wide range o...

0 Mengdi Zhu, et al. ∙

research

∙ 09/09/2019

Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification

Many tasks in natural language processing can be viewed as multi-label c...

0 Jiawei Wu, et al. ∙

research

∙ 08/13/2019

Meta Reasoning over Knowledge Graphs

The ability to reason over learned knowledge is an innate ability for hu...

0 Hong Wang, et al. ∙

research

∙ 07/14/2019

TWEETQA: A Social Media Focused Question Answering Dataset

With social media becoming increasingly pop-ular on which lots of news a...

0 Wenhan Xiong, et al. ∙

research

∙ 06/11/2019

Self-Supervised Learning for Contextualized Extractive Summarization

Existing models for extractive summarization are usually trained from sc...

0 Hong Wang, et al. ∙

research

∙ 05/17/2019

Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

We propose a new end-to-end question answering model, which learns to ag...

5 Wenhan Xiong, et al. ∙

research

∙ 03/06/2019

Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

Existing entity typing systems usually exploit the type hierarchy provid...

0 Wenhan Xiong, et al. ∙

research

∙ 03/06/2019

Sentence Embedding Alignment for Lifelong Relation Extraction

Conventional approaches to relation extraction usually require a fixed s...

0 Hong Wang, et al. ∙

research

∙ 11/03/2018

SafeRoute: Learning to Navigate Streets Safely in an Urban Environment

Recent studies show that 85 avoid harassment and assault. Despite this, ...

0 Sharon Levy, et al. ∙

research

∙ 08/27/2018

One-Shot Relational Learning for Knowledge Graphs

Knowledge graphs (KGs) are the key components of various natural languag...

0 Wenhan Xiong, et al. ∙

research

∙ 06/16/2018

Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents

We investigate the task of learning to follow natural language instructi...

0 Wenhan Xiong, et al. ∙

research

∙ 03/21/2018

Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation

Existing research studies on vision and language grounding for robot nav...

0 Xin Wang, et al. ∙

research

∙ 03/17/2018

Variational Knowledge Graph Reasoning

Inferring missing links in knowledge graphs (KG) has attracted a lot of ...

0 Wenhu Chen, et al. ∙

research

∙ 07/20/2017

DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning

We study the problem of learning to reason in large scale knowledge grap...

0 Wenhan Xiong, et al. ∙

Wenhan Xiong

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