Search Results for author: William Wang

Found 25 papers, 10 papers with code

Few-Shot Data-to-Text Generation via Unified Representation and Multi-Source Learning

no code implementations10 Aug 2023 Alexander Hanbo Li, Mingyue Shang, Evangelia Spiliopoulou, Jie Ma, Patrick Ng, Zhiguo Wang, Bonan Min, William Wang, Kathleen McKeown, Vittorio Castelli, Dan Roth, Bing Xiang

We present a novel approach for structured data-to-text generation that addresses the limitations of existing methods that primarily focus on specific types of structured data.

Data-to-Text Generation

Learning Concise and Descriptive Attributes for Visual Recognition

1 code implementation ICCV 2023 An Yan, Yu Wang, Yiwu Zhong, chengyu dong, Zexue He, Yujie Lu, William Wang, Jingbo Shang, Julian McAuley

Recent advances in foundation models present new opportunities for interpretable visual recognition -- one can first query Large Language Models (LLMs) to obtain a set of attributes that describe each class, then apply vision-language models to classify images via these attributes.


Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models

no code implementations23 May 2023 Alfonso Amayuelas, Liangming Pan, Wenhu Chen, William Wang

This paper investigates the capabilities of Large Language Models (LLMs) in the context of understanding their own knowledge and measuring their uncertainty.

Known Unknowns

Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks

2 code implementations27 Oct 2022 Edwin Zhang, Yujie Lu, William Wang, Amy Zhang

Training generalist agents is difficult across several axes, requiring us to deal with high-dimensional inputs (space), long horizons (time), and multiple and new tasks.

reinforcement-learning Reinforcement Learning (RL)

DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases

1 code implementation30 Sep 2022 Donghan Yu, Sheng Zhang, Patrick Ng, Henghui Zhu, Alexander Hanbo Li, Jun Wang, Yiqun Hu, William Wang, Zhiguo Wang, Bing Xiang

Question answering over knowledge bases (KBs) aims to answer natural language questions with factual information such as entities and relations in KBs.

Entity Linking Question Answering +2

Emotion Recognition in Conversation using Probabilistic Soft Logic

no code implementations14 Jul 2022 Eriq Augustine, Pegah Jandaghi, Alon Albalak, Connor Pryor, Charles Dickens, William Wang, Lise Getoor

Creating agents that can both appropriately respond to conversations and understand complex human linguistic tendencies and social cues has been a long standing challenge in the NLP community.

Emotion Recognition in Conversation Logical Reasoning +1

NeuPSL: Neural Probabilistic Soft Logic

no code implementations27 May 2022 Connor Pryor, Charles Dickens, Eriq Augustine, Alon Albalak, William Wang, Lise Getoor

In this paper, we introduce Neural Probabilistic Soft Logic (NeuPSL), a novel neuro-symbolic (NeSy) framework that unites state-of-the-art symbolic reasoning with the low-level perception of deep neural networks.

On the Opportunities and Risks of Foundation Models

3 code implementations16 Aug 2021 Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, aditi raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

AI is undergoing a paradigm shift with the rise of models (e. g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.

Transfer Learning

Open Question Answering over Tables and Text

1 code implementation ICLR 2021 Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Wang, William W. Cohen

In open question answering (QA), the answer to a question is produced by retrieving and then analyzing documents that might contain answers to the question.

Open-Ended Question Answering Retrieval

GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models

no code implementations18 Jun 2020 Farzan Farnia, William Wang, Subhro Das, Ali Jadbabaie

Motivated by optimal transport theory, we design the zero-sum game in GAT-GMM using a random linear generator and a softmax-based quadratic discriminator architecture, which leads to a non-convex concave minimax optimization problem.

Meta Module Network for Compositional Visual Reasoning

1 code implementation8 Oct 2019 Wenhu Chen, Zhe Gan, Linjie Li, Yu Cheng, William Wang, Jingjing Liu

To design a more powerful NMN architecture for practical use, we propose Meta Module Network (MMN) centered on a novel meta module, which can take in function recipes and morph into diverse instance modules dynamically.

MORPH Visual Reasoning

Fine-tune Bert for DocRED with Two-step Process

1 code implementation26 Sep 2019 Hong Wang, Christfried Focke, Rob Sylvester, Nilesh Mishra, William Wang

Modelling relations between multiple entities has attracted increasing attention recently, and a new dataset called DocRED has been collected in order to accelerate the research on the document-level relation extraction.

Document-level Relation Extraction Vocal Bursts Valence Prediction

Generalized Natural Language Grounded Navigation via Environment-agnostic Multitask Learning

no code implementations25 Sep 2019 Xin Wang, Vihan Jain, Eugene Ie, William Wang, Zornitsa Kozareva, Sujith Ravi

Recent research efforts enable study for natural language grounded navigation in photo-realistic environments, e. g., following natural language instructions or dialog.

Vision-Language Navigation

Scene Graph Generation via Conditional Random Fields

no code implementations20 Nov 2018 Weilin Cong, William Wang, Wang-Chien Lee

Scene graph, a graph representation of images that captures object instances and their relationships, offers a comprehensive understanding of an image.

Graph Generation Image Retrieval +4

A Variational Dirichlet Framework for Out-of-Distribution Detection

no code implementations ICLR 2019 Wenhu Chen, Yilin Shen, Hongxia Jin, William Wang

With the recently rapid development in deep learning, deep neural networks have been widely adopted in many real-life applications.

Out-of-Distribution Detection Variational Inference

MOHONE: Modeling Higher Order Network Effects in KnowledgeGraphs via Network Infused Embeddings

no code implementations1 Nov 2018 Hao Yu, Vivek Kulkarni, William Wang

First, we introduce methods that learn network representations of entities in the knowledge graph capturing these varied aspects of similarity.

Knowledge Graph Embedding Knowledge Graph Embeddings +2

Variational Knowledge Graph Reasoning

no code implementations NAACL 2018 Wenhu Chen, Wenhan Xiong, Xifeng Yan, William Wang

Inferring missing links in knowledge graphs (KG) has attracted a lot of attention from the research community.

Knowledge Graphs Link Prediction +1

Safer Classification by Synthesis

no code implementations22 Nov 2017 William Wang, Angelina Wang, Aviv Tamar, Xi Chen, Pieter Abbeel

We posit that a generative approach is the natural remedy for this problem, and propose a method for classification using generative models.

Classification General Classification

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