Search Results for author: Yu Su

Found 81 papers, 49 papers with code

Bridging the Generalization Gap in Text-to-SQL Parsing with Schema Expansion

no code implementations ACL 2022 Chen Zhao, Yu Su, Adam Pauls, Emmanouil Antonios Platanios

Text-to-SQL parsers map natural language questions to programs that are executable over tables to generate answers, and are typically evaluated on large-scale datasets like Spider (Yu et al., 2018).

Domain Generalization SQL Parsing +1

MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions

no code implementations28 Mar 2024 Kai Zhang, Yi Luan, Hexiang Hu, Kenton Lee, Siyuan Qiao, Wenhu Chen, Yu Su, Ming-Wei Chang

Image retrieval, i. e., finding desired images given a reference image, inherently encompasses rich, multi-faceted search intents that are difficult to capture solely using image-based measures.

LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

1 code implementation7 Mar 2024 Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, Yu Su

We find that existing LLMs, including GPT-4 and open-source LLMs specifically fine-tuned for tool use, only reach a correctness rate in the range of 30% to 60%, far from reliable use in practice.

Continual Learning In-Context Learning

Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments

no code implementations22 Feb 2024 Yu Gu, Yiheng Shu, Hao Yu, Xiao Liu, Yuxiao Dong, Jie Tang, Jayanth Srinivasa, Hugo Latapie, Yu Su

The applications of large language models (LLMs) have expanded well beyond the confines of text processing, signaling a new era where LLMs are envisioned as generalist language agents capable of operating within complex real-world environments.

When is Tree Search Useful for LLM Planning? It Depends on the Discriminator

1 code implementation16 Feb 2024 Ziru Chen, Michael White, Raymond Mooney, Ali Payani, Yu Su, Huan Sun

In this paper, we examine how large language models (LLMs) solve multi-step problems under a language agent framework with three components: a generator, a discriminator, and a planning method.

Mathematical Reasoning Re-Ranking +2

A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents

1 code implementation15 Feb 2024 Lingbo Mo, Zeyi Liao, Boyuan Zheng, Yu Su, Chaowei Xiao, Huan Sun

There is a surprisingly large gap between the speed and scale of their development and deployment and our understanding of their safety risks.

Dual-View Visual Contextualization for Web Navigation

no code implementations6 Feb 2024 Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, Wei-Lun Chao

Automatic web navigation aims to build a web agent that can follow language instructions to execute complex and diverse tasks on real-world websites.

TravelPlanner: A Benchmark for Real-World Planning with Language Agents

1 code implementation2 Feb 2024 Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su

Are these language agents capable of planning in more complex settings that are out of the reach of prior AI agents?

Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning

1 code implementation31 Jan 2024 Tinghui Zhu, Kai Zhang, Jian Xie, Yu Su

Recent advancements have significantly augmented the reasoning capabilities of Large Language Models (LLMs) through various methodologies, especially chain-of-thought (CoT) reasoning.

GPT-4V(ision) is a Generalist Web Agent, if Grounded

1 code implementation3 Jan 2024 Boyuan Zheng, Boyu Gou, Jihyung Kil, Huan Sun, Yu Su

The recent development on large multimodal models (LMMs), especially GPT-4V(ision) and Gemini, has been quickly expanding the capability boundaries of multimodal models beyond traditional tasks like image captioning and visual question answering.

Image Captioning Question Answering +1

Bringing Back the Context: Camera Trap Species Identification as Link Prediction on Multimodal Knowledge Graphs

no code implementations31 Dec 2023 Vardaan Pahuja, Weidi Luo, Yu Gu, Cheng-Hao Tu, Hong-You Chen, Tanya Berger-Wolf, Charles Stewart, Song Gao, Wei-Lun Chao, Yu Su

In this work, we leverage the structured context associated with the camera trap images to improve out-of-distribution generalization for the task of species identification in camera traps.

Knowledge Graphs Link Prediction +1

MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following

no code implementations5 Dec 2023 Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Janice Ahn, Hanzi Xu, Yu Su, Wenpeng Yin

In the realm of large language models (LLMs), enhancing instruction-following capability often involves curating expansive training data.

Instruction Following

BioCLIP: A Vision Foundation Model for the Tree of Life

1 code implementation30 Nov 2023 Samuel Stevens, Jiaman Wu, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao, Yu Su

We then develop BioCLIP, a foundation model for the tree of life, leveraging the unique properties of biology captured by TreeOfLife-10M, namely the abundance and variety of images of plants, animals, and fungi, together with the availability of rich structured biological knowledge.

Solving the Right Problem is Key for Translational NLP: A Case Study in UMLS Vocabulary Insertion

1 code implementation25 Nov 2023 Bernal Jimenez Gutierrez, Yuqing Mao, Vinh Nguyen, Kin Wah Fung, Yu Su, Olivier Bodenreider

In this work, we study the case of UMLS vocabulary insertion, an important real-world task in which hundreds of thousands of new terms, referred to as atoms, are added to the UMLS, one of the most comprehensive open-source biomedical knowledge bases.

Language Modelling

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

1 code implementation7 Nov 2023 Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel Rubenstein, Charles Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao

Unlike mainstream classifiers that wait until the last fully-connected layer to incorporate class information to make predictions, we investigate a proactive approach, asking each class to search for itself in an image.

Fine-Grained Image Classification

FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows

1 code implementation20 Oct 2023 Yuxiao Qu, Jinmeng Rao, Song Gao, Qianheng Zhang, Wei-Lun Chao, Yu Su, Michelle Miller, Alfonso Morales, Patrick Huber

This paper proposes FLEE-GNN, a novel Federated Learning System for Edge-Enhanced Graph Neural Network, designed to overcome these challenges and enhance the analysis of geospatial resilience of multicommodity food flow network, which is one type of spatial networks.

Federated Learning

Multimodal Question Answering for Unified Information Extraction

1 code implementation4 Oct 2023 Yuxuan Sun, Kai Zhang, Yu Su

In addition, the effectiveness of our framework can successfully transfer to the few-shot setting, enhancing LMMs on a scale of 10B parameters to be competitive or outperform much larger language models such as ChatGPT and GPT-4.

Question Answering

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning

1 code implementation11 Sep 2023 Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen

The MAmmoTH models are trained on MathInstruct, our meticulously curated instruction tuning dataset.

Math Mathematical Reasoning

Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm

no code implementations1 Sep 2023 Jiatong Li, Qi Liu, Fei Wang, Jiayu Liu, Zhenya Huang, Fangzhou Yao, Linbo Zhu, Yu Su

However, we notice that this paradigm leads to the inevitable non-identifiability and explainability overfitting problem, which is harmful to the quantification of learners' cognitive states and the quality of web learning services.

cognitive diagnosis

AgentBench: Evaluating LLMs as Agents

1 code implementation7 Aug 2023 Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang

We present AgentBench, a multi-dimensional evolving benchmark that currently consists of 8 distinct environments to assess LLM-as-Agent's reasoning and decision-making abilities in a multi-turn open-ended generation setting.

Decision Making Instruction Following

Transformer-based Joint Source Channel Coding for Textual Semantic Communication

no code implementations23 Jul 2023 Shicong Liu, Zhen Gao, Gaojie Chen, Yu Su, Lu Peng

The Space-Air-Ground-Sea integrated network calls for more robust and secure transmission techniques against jamming.

Semantic Similarity Semantic Textual Similarity +1

Hybrid Knowledge-Data Driven Channel Semantic Acquisition and Beamforming for Cell-Free Massive MIMO

no code implementations6 Jul 2023 Zhen Gao, Shicong Liu, Yu Su, Zhongxiang Li, Dezhi Zheng

Moreover, based on the acquired channel semantic, we further propose a knowledge-driven deep-unfolding multi-user beamformer, which is capable of achieving good spectral efficiency with robustness to imperfect CSI in outdoor XR scenarios.

Biomedical Language Models are Robust to Sub-optimal Tokenization

1 code implementation30 Jun 2023 Bernal Jiménez Gutiérrez, Huan Sun, Yu Su

As opposed to general English, many concepts in biomedical terminology have been designed in recent history by biomedical professionals with the goal of being precise and concise.

Entity Linking Language Modelling +4

MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing

1 code implementation NeurIPS 2023 Kai Zhang, Lingbo Mo, Wenhu Chen, Huan Sun, Yu Su

To address this issue, we introduce MagicBrush (https://osu-nlp-group. github. io/MagicBrush/), the first large-scale, manually annotated dataset for instruction-guided real image editing that covers diverse scenarios: single-turn, multi-turn, mask-provided, and mask-free editing.

text-guided-image-editing

Mind2Web: Towards a Generalist Agent for the Web

1 code implementation NeurIPS 2023 Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, Yu Su

We introduce Mind2Web, the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website.

Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms

1 code implementation26 May 2023 Tianshu Zhang, Changchang Liu, Wei-Han Lee, Yu Su, Huan Sun

By leveraging data from multiple clients, the FL paradigm can be especially beneficial for clients that have little training data to develop a data-hungry neural semantic parser on their own.

Federated Learning Semantic Parsing +1

Error Detection for Text-to-SQL Semantic Parsing

1 code implementation23 May 2023 Shijie Chen, Ziru Chen, Huan Sun, Yu Su

Despite remarkable progress in text-to-SQL semantic parsing in recent years, the performance of existing parsers is still far from perfect.

Language Modelling Semantic Parsing +1

Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts

1 code implementation22 May 2023 Jian Xie, Kai Zhang, Jiangjie Chen, Renze Lou, Yu Su

By providing external information to large language models (LLMs), tool augmentation (including retrieval augmentation) has emerged as a promising solution for addressing the limitations of LLMs' static parametric memory.

Retrieval

Text-to-SQL Error Correction with Language Models of Code

1 code implementation22 May 2023 Ziru Chen, Shijie Chen, Michael White, Raymond Mooney, Ali Payani, Jayanth Srinivasa, Yu Su, Huan Sun

Thus, we propose a novel representation for SQL queries and their edits that adheres more closely to the pre-training corpora of language models of code.

SQL Parsing Text-To-SQL

Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors

1 code implementation18 May 2023 Kai Zhang, Bernal Jiménez Gutiérrez, Yu Su

Recent work has shown that fine-tuning large language models (LLMs) on large-scale instruction-following datasets substantially improves their performance on a wide range of NLP tasks, especially in the zero-shot setting.

Instruction Following Question Answering +2

Memorization for Good: Encryption with Autoregressive Language Models

1 code implementation15 May 2023 Samuel Stevens, Yu Su

Over-parameterized neural language models (LMs) can memorize and recite long sequences of training data.

Cryptanalysis Memorization

Automatic Evaluation of Attribution by Large Language Models

1 code implementation10 May 2023 Xiang Yue, Boshi Wang, Ziru Chen, Kai Zhang, Yu Su, Huan Sun

We manually curate a set of test examples covering 12 domains from a generative search engine, New Bing.

Fact Checking Language Modelling +3

PiML Toolbox for Interpretable Machine Learning Model Development and Diagnostics

1 code implementation7 May 2023 Agus Sudjianto, Aijun Zhang, Zebin Yang, Yu Su, Ningzhou Zeng

PiML (read $\pi$-ML, /`pai`em`el/) is an integrated and open-access Python toolbox for interpretable machine learning model development and model diagnostics.

Fairness Interpretable Machine Learning

Quiz-based Knowledge Tracing

no code implementations5 Apr 2023 Shuanghong Shen, Enhong Chen, Bihan Xu, Qi Liu, Zhenya Huang, Linbo Zhu, Yu Su

In this paper, we present the Quiz-based Knowledge Tracing (QKT) model to monitor students' knowledge states according to their quiz-based learning interactions.

Decision Making Knowledge Tracing

Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments

2 code implementations19 Dec 2022 Yu Gu, Xiang Deng, Yu Su

Most existing work for grounded language understanding uses LMs to directly generate plans that can be executed in the environment to achieve the desired effects.

In-Context Learning Knowledge Base Question Answering +1

A Retrieve-and-Read Framework for Knowledge Graph Link Prediction

1 code implementation19 Dec 2022 Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su

To address the limitations of existing KG link prediction frameworks, we propose a novel retrieve-and-read framework, which first retrieves a relevant subgraph context for the query and then jointly reasons over the context and the query with a high-capacity reader.

Knowledge Graph Completion Link Prediction

LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models

no code implementations ICCV 2023 Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M. Sadler, Wei-Lun Chao, Yu Su

In this work, we propose a novel method, LLM-Planner, that harnesses the power of large language models to do few-shot planning for embodied agents.

Hand Hygiene Assessment via Joint Step Segmentation and Key Action Scorer

no code implementations25 Sep 2022 Chenglong Li, Qiwen Zhu, Tubiao Liu, Jin Tang, Yu Su

To address this issue, we design a multi-stage convolution-transformer network for step segmentation.

Action Assessment Segmentation

Knowledge Base Question Answering: A Semantic Parsing Perspective

no code implementations12 Sep 2022 Yu Gu, Vardaan Pahuja, Gong Cheng, Yu Su

In this survey, we situate KBQA in the broader literature of semantic parsing and give a comprehensive account of how existing KBQA approaches attempt to address the unique challenges.

Attribute Knowledge Base Question Answering +2

Bootstrapping a User-Centered Task-Oriented Dialogue System

no code implementations11 Jul 2022 Shijie Chen, Ziru Chen, Xiang Deng, Ashley Lewis, Lingbo Mo, Samuel Stevens, Zhen Wang, Xiang Yue, Tianshu Zhang, Yu Su, Huan Sun

We present TacoBot, a task-oriented dialogue system built for the inaugural Alexa Prize TaskBot Challenge, which assists users in completing multi-step cooking and home improvement tasks.

Data Augmentation Dialogue Management +2

When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems

1 code implementation24 May 2022 Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls, Sam Thomson, Hao Fang, Benjamin Van Durme, Jason Eisner, Yu Su

Rejecting class imbalance as the sole culprit, we reveal that the trend is closely associated with an effect we call source signal dilution, where strong lexical cues for the new symbol become diluted as the training dataset grows.

Intent Recognition Natural Language Understanding +1

ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering

1 code implementation COLING 2022 Yu Gu, Yu Su

Question answering on knowledge bases (KBQA) poses a unique challenge for semantic parsing research due to two intertwined challenges: large search space and ambiguities in schema linking.

Knowledge Base Question Answering Program induction +1

Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again

1 code implementation16 Mar 2022 Bernal Jiménez Gutiérrez, Nikolas McNeal, Clay Washington, You Chen, Lang Li, Huan Sun, Yu Su

In this paper, we present the first systematic and comprehensive study to compare the few-shot performance of GPT-3 in-context learning with fine-tuning smaller (i. e., BERT-sized) PLMs on two highly representative biomedical information extraction tasks, named entity recognition and relation extraction.

In-Context Learning Model Selection +5

One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones

1 code implementation CVPR 2022 Chan Hee Song, Jihyung Kil, Tai-Yu Pan, Brian M. Sadler, Wei-Lun Chao, Yu Su

We study the problem of developing autonomous agents that can follow human instructions to infer and perform a sequence of actions to complete the underlying task.

Vision and Language Navigation

Compositional Generalization for Natural Language Interfaces to Web APIs

no code implementations9 Dec 2021 Saghar Hosseini, Ahmed Hassan Awadallah, Yu Su

We define new compositional generalization tasks for NL2API which explore the models' ability to extrapolate from simple API calls in the training set to new and more complex API calls in the inference phase.

Semantic Parsing

ReasonBERT: Pre-trained to Reason with Distant Supervision

1 code implementation EMNLP 2021 Xiang Deng, Yu Su, Alyssa Lees, You Wu, Cong Yu, Huan Sun

We present ReasonBert, a pre-training method that augments language models with the ability to reason over long-range relations and multiple, possibly hybrid contexts.

Extractive Question-Answering Question Answering +1

A Systematic Investigation of KB-Text Embedding Alignment at Scale

1 code implementation ACL 2021 Vardaan Pahuja, Yu Gu, Wenhu Chen, Mehdi Bahrami, Lei Liu, Wei-Peng Chen, Yu Su

Knowledge bases (KBs) and text often contain complementary knowledge: KBs store structured knowledge that can support long range reasoning, while text stores more comprehensive and timely knowledge in an unstructured way.

Link Prediction

Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing

no code implementations15 Jan 2021 Haoyang Bi, Haiping Ma, Zhenya Huang, Yu Yin, Qi Liu, Enhong Chen, Yu Su, Shijin Wang

In this paper, we study a novel model-agnostic CAT problem, where we aim to propose a flexible framework that can adapt to different cognitive models.

Active Learning

Explainable Recommendation Systems by Generalized Additive Models with Manifest and Latent Interactions

no code implementations15 Dec 2020 Yifeng Guo, Yu Su, Zebin Yang, Aijun Zhang

In this paper, we propose the explainable recommendation systems based on a generalized additive model with manifest and latent interactions (GAMMLI).

Additive models Collaborative Filtering +2

An Investigation of Language Model Interpretability via Sentence Editing

2 code implementations EMNLP (BlackboxNLP) 2021 Samuel Stevens, Yu Su

Pre-trained language models (PLMs) like BERT are being used for almost all language-related tasks, but interpreting their behavior still remains a significant challenge and many important questions remain largely unanswered.

General Classification Language Modelling +1

Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases

1 code implementation16 Nov 2020 Yu Gu, Sue Kase, Michelle Vanni, Brian Sadler, Percy Liang, Xifeng Yan, Yu Su

To facilitate the development of KBQA models with stronger generalization, we construct and release a new large-scale, high-quality dataset with 64, 331 questions, GrailQA, and provide evaluation settings for all three levels of generalization.

Knowledge Base Question Answering

Marcus' electron transfer rate revisited via a Rice-Ramsperger-Kassel-Marcus analogue: A unified formalism for linear and nonlinear solvation scenarios

no code implementations10 Oct 2020 Yao Wang, Yu Su, Rui-Xue Xu, Xiao Zheng, YiJing Yan

In this work, on the basis of the thermodynamic solvation potentials analysis, we reexamine Marcus' formula with respect to the Rice-Ramsperger-Kassel-Marcus (RRKM) theory.

Chemical Physics

KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation

1 code implementation EMNLP 2020 Wenhu Chen, Yu Su, Xifeng Yan, William Yang Wang

We propose a knowledge-grounded pre-training (KGPT), which consists of two parts, 1) a general knowledge-grounded generation model to generate knowledge-enriched text.

General Knowledge KG-to-Text Generation +1

Document Classification for COVID-19 Literature

1 code implementation NLP-COVID19 (ACL) 2020 Bernal Jiménez Gutiérrez, Juncheng Zeng, Dong-dong Zhang, Ping Zhang, Yu Su

The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields.

Classification Document Classification +1

An Imitation Game for Learning Semantic Parsers from User Interaction

1 code implementation EMNLP 2020 Ziyu Yao, Yiqi Tang, Wen-tau Yih, Huan Sun, Yu Su

Despite the widely successful applications, bootstrapping and fine-tuning semantic parsers are still a tedious process with challenges such as costly data annotation and privacy risks.

Imitation Learning Text-To-SQL

Logical Natural Language Generation from Open-Domain Tables

1 code implementation ACL 2020 Wenhu Chen, Jianshu Chen, Yu Su, Zhiyu Chen, William Yang Wang

To facilitate the study of the proposed logical NLG problem, we use the existing TabFact dataset \cite{chen2019tabfact} featured with a wide range of logical/symbolic inferences as our testbed, and propose new automatic metrics to evaluate the fidelity of generation models w. r. t.\ logical inference.

Text Generation

Decision Propagation Networks for Image Classification

no code implementations27 Nov 2019 Keke Tang, Peng Song, Yuexin Ma, Zhaoquan Gu, Yu Su, Zhihong Tian, Wenping Wang

High-level (e. g., semantic) features encoded in the latter layers of convolutional neural networks are extensively exploited for image classification, leaving low-level (e. g., color) features in the early layers underexplored.

Classification General Classification +1

Model-based Interactive Semantic Parsing: A Unified Framework and A Text-to-SQL Case Study

2 code implementations IJCNLP 2019 Ziyu Yao, Yu Su, Huan Sun, Wen-tau Yih

As a promising paradigm, interactive semantic parsing has shown to improve both semantic parsing accuracy and user confidence in the results.

Semantic Parsing Text-To-SQL

EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction

1 code implementation7 Jun 2019 Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Hui Xiong, Yu Su, Guoping Hu

In EERNN, we simply summarize each student's state into an integrated vector and trace it with a recurrent neural network, where we design a bidirectional LSTM to learn the encoding of each exercise's content.

Knowledge Tracing

Global Textual Relation Embedding for Relational Understanding

1 code implementation ACL 2019 Zhiyu Chen, Hanwen Zha, Honglei Liu, Wenhu Chen, Xifeng Yan, Yu Su

Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks.

Action Classification Relation +3

QuesNet: A Unified Representation for Heterogeneous Test Questions

no code implementations27 May 2019 Yu Yin, Qi Liu, Zhenya Huang, Enhong Chen, Wei Tong, Shijin Wang, Yu Su

Then we propose a two-level hierarchical pre-training algorithm to learn better understanding of test questions in an unsupervised way.

Language Modelling

Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning

no code implementations7 Nov 2018 Xin Wang, Jiawei Wu, Da Zhang, Yu Su, William Yang Wang

Although promising results have been achieved in video captioning, existing models are limited to the fixed inventory of activities in the training corpus, and do not generalize to open vocabulary scenarios.

Video Captioning

What It Takes to Achieve 100\% Condition Accuracy on WikiSQL

no code implementations EMNLP 2018 Semih Yavuz, Izzeddin Gur, Yu Su, Xifeng Yan

The SQL queries in WikiSQL are simple: Each involves one relation and does not have any join operation.

Translation

XL-NBT: A Cross-lingual Neural Belief Tracking Framework

1 code implementation EMNLP 2018 Wenhu Chen, Jianshu Chen, Yu Su, Xin Wang, Dong Yu, Xifeng Yan, William Yang Wang

Then, we pre-train a state tracker for the source language as a teacher, which is able to exploit easy-to-access parallel data.

Transfer Learning

DialSQL: Dialogue Based Structured Query Generation

no code implementations ACL 2018 Izzeddin Gur, Semih Yavuz, Yu Su, Xifeng Yan

The recent advance in deep learning and semantic parsing has significantly improved the translation accuracy of natural language questions to structured queries.

Semantic Parsing Translation

Aggregated Channels Network for Real-Time Pedestrian Detection

no code implementations1 Jan 2018 Farzin Ghorban, Javier Marín, Yu Su, Alessandro Colombo, Anton Kummert

Convolutional neural networks (CNNs) have demonstrated their superiority in numerous computer vision tasks, yet their computational cost results prohibitive for many real-time applications such as pedestrian detection which is usually performed on low-consumption hardware.

Pedestrian Detection

Recovering Question Answering Errors via Query Revision

no code implementations EMNLP 2017 Semih Yavuz, Izzeddin Gur, Yu Su, Xifeng Yan

The existing factoid QA systems often lack a post-inspection component that can help models recover from their own mistakes.

Question Answering Semantic Parsing

An End-to-End Deep Framework for Answer Triggering with a Novel Group-Level Objective

no code implementations EMNLP 2017 Jie Zhao, Yu Su, Ziyu Guan, Huan Sun

Given a question and a set of answer candidates, answer triggering determines whether the candidate set contains any correct answers.

Multiple Instance Learning Question Answering

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